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Journal articles on the topic 'Microgrid optimization'
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1
Lei, Bingyin, Yue Ren, Huiyu Luan, Ruonan Dong, Xiuyuan Wang, Junli Liao, Shu Fang, and Kaiye Gao. "A Review of Optimization for System Reliability of Microgrid." Mathematics 11, no. 4 (February 6, 2023): 822. http://dx.doi.org/10.3390/math11040822.
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Clean and renewable energy is the only way to achieve sustainable energy development, with considerable social and economic benefits. As a key technology for clean and renewable energy, it is very important to research the reliability optimization of microgrids. This paper reviews the research progress in microgrid reliability optimization. This paper first classifies and summarizes the existing research on microgrid control strategies and reliability assessment. Then, the system reliability optimization framework is summarized in terms of both microgrid systems and optimization objectives. Next, we summarize the most commonly used optimization algorithms for microgrid reliability for different microgrid systems. Finally, we provide a bibliometric analysis of the literature on the reliability research of microgrids. In addition, we propose some research challenges in the future for the reliability of microgrids.
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Twaisan, Kumail, and Necaattin Barışçı. "Integrated Distributed Energy Resources (DER) and Microgrids: Modeling and Optimization of DERs." Electronics 11, no. 18 (September 6, 2022): 2816. http://dx.doi.org/10.3390/electronics11182816.
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In the near future, the notion of integrating distributed energy resources (DERs) to build a microgrid will be extremely important. The DERs comprise several technologies, such as diesel engines, micro turbines, fuel cells, photovoltaic, small wind turbines, etc. The coordinated operation and control of DER together with controllable loads and storage devices, such as flywheels, energy capacitors and batteries, are central to the concept of microgrid. Microgrids can operate interconnected to the main distribution grid, or in an islanded mode. This paper reviews the studies on microgrid technologies. The modeling and optimization methodologies of DERs are also presented and discussed in this paper along with system control approaches for DERs and microgrids. The review findings indicate that the use of multimodal indicators that take into consideration the financial, technological, ecological, and social elements of microgrids increased the community’s and stakeholders’ reaction capability. The microgrid structure under consideration comprises several types of combined heat power devices, boilers, and various types of DERs, including FC units, distributed generators, and MTs. Moreover, compared to grid-connected mode, the microgrid’s total operation cost is significantly higher in isolated mode.
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Azeem, Omar, Mujtaba Ali, Ghulam Abbas, Muhammad Uzair, Ayman Qahmash, Abdulmohsen Algarni, and Mohammad Rashid Hussain. "A Comprehensive Review on Integration Challenges, Optimization Techniques and Control Strategies of Hybrid AC/DC Microgrid." Applied Sciences 11, no. 14 (July 6, 2021): 6242. http://dx.doi.org/10.3390/app11146242.
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The depletion of natural resources and the intermittence of renewable energy resources have pressed the need for a hybrid microgrid, combining the benefits of both AC and DC microgrids, minimizing the overall deficiency shortcomings and increasing the reliability of the system. The hybrid microgrid also supports the decentralized grid control structure, aligning with the current scattered and concentrated load scenarios. Hence, there is an increasing need to explore and reveal the integration, optimization, and control strategies regarding the hybrid microgrid. A comprehensive study of hybrid microgrid’s performance parameters, efficiency, reliability, security, design flexibility, and cost-effectiveness is required. This paper discusses major issues regarding the hybrid microgrids, the integration of AC and DC microgrids, their security and reliability, the optimization of power generation and load management in different scenarios, the efficient management regarding uncertainty for renewable energy resources, the optimal placement of feeders, and the cost-effective control methodologies for the hybrid microgrid. The major research areas are briefly explained, aiming to find the research gap that can further improve the performance of the grid. In light of the recent trends in research, novel strategies are proposed that are found most effective and cost-friendly regarding the hybrid microgrid. This paper will serve as a baseline for future research, comparative analysis, and further development of novel techniques regarding hybrid microgrids.
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Gao, Kaiye, Tianshi Wang, Chenjing Han, Jinhao Xie, Ye Ma, and Rui Peng. "A Review of Optimization of Microgrid Operation." Energies 14, no. 10 (May 14, 2021): 2842. http://dx.doi.org/10.3390/en14102842.
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Clean and renewable energy is developing to realize the sustainable utilization of energy and the harmonious development of the economy and society. Microgrids are a key technique for applying clean and renewable energy. The operation optimization of microgrids has become an important research field. This paper reviews the developments in the operation optimization of microgrids. We first summarize the system structure and provide a typical system structure, which includes an energy generation system, an energy distribution system, an energy storage system and energy end users. Then, we summarize the optimization framework for microgrid operation, which contains the optimization objective, decision variables and constraints. Next, we systematically review the optimization algorithms for microgrid operations, of which genetic algorithms and simulated annealing algorithms are the most commonly used. Lastly, a literature bibliometric analysis is provided; the results show that the operation optimization of microgrids has received increasing attention in recent years, and developing countries have shown more interest in this field than developed countries have. Finally, we highlight future research challenges for the optimization of the operation of microgrids.
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Liu, Jicheng, Fangqiu Xu, Shuaishuai Lin, Hua Cai, and Suli Yan. "A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization." Energies 11, no. 12 (November 25, 2018): 3286. http://dx.doi.org/10.3390/en11123286.
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The optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and microgrid control element agent is proposed considering energy storage units and demand response. Then, based on this multi-agent system and with the objective of cost minimization, an operation optimization model for microgrids is constructed from three aspects: operation cost, environmental impact and security. To solve this model, dynamic guiding chaotic search particle swarm optimization is adopted and three scenarios including basic scenario, energy storage participation and demand response participation are simulated and analyzed. The results show that both energy storage unit and demand response can effectively reduce the cost of microgrid, improve the operation and management level and ensure the safety and stability of power supply and utilization.
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Rokicki, Łukasz. "Optimization of the Configuration and Operating States of Hybrid AC/DC Low Voltage Microgrid Using a Clonal Selection Algorithm with a Modified Hypermutation Operator." Energies 14, no. 19 (October 5, 2021): 6351. http://dx.doi.org/10.3390/en14196351.
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The issue of optimization of the configuration and operating states in low voltage microgrids is important both from the point of view of the proper operation of the microgrid and its impact on the medium voltage distribution network to which such microgrid is connected. Suboptimal microgrid configuration may cause problems in networks managed by distribution system operators, as well as for electricity consumers and owners of microsources and energy storage systems connected to the microgrid. Structures particularly sensitive to incorrect determination of the operating states of individual devices are hybrid microgrids that combine an alternating current and direct current networks with the use of a bidirectional power electronic converter. An analysis of available literature shows that evolutionary and swarm optimization algorithms are the most frequently chosen for the optimization of power systems. The research presented in this article concerns the assessment of the possibilities of using artificial immune systems, operating on the basis of the CLONALG algorithm, as tools enabling the effective optimization of low voltage hybrid microgrids. In his research, the author developed a model of a hybrid low voltage microgrid, formulated three optimization tasks, and implemented an algorithm for solving the formulated tasks based on an artificial immune system using the CLONALG algorithm. The conducted research consisted of performing a 24 h simulation of microgrid operation for each of the formulated optimization tasks (divided into 10 min independent optimization periods). A novelty in the conducted research was the modification of the hypermutation operator, which is the key mechanism for the functioning of the CLONALG algorithm. In order to verify the changes introduced in the CLONALG algorithm and to assess the effectiveness of the artificial immune system in solving optimization tasks, optimization was also carried out with the use of an evolutionary algorithm, commonly used in solving such tasks. Based on the analysis of the obtained results of optimization calculations, it can be concluded that the artificial immune system proposed in this article, operating on the basis of the CLONALG algorithm with a modified hypermutation operator, in most of the analyzed cases obtained better results than the evolutionary algorithm. In several cases, both algorithms obtained identical results, which also proves that the CLONALG algorithm can be considered as an effective tool for optimizing modern power structures, such as low voltage microgrids, including hybrid AC/DC microgrids.
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Silva, Vanderlei Aparecido, Alexandre Rasi Aoki, and Germano Lambert-Torres. "Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System." Energies 13, no. 19 (October 5, 2020): 5188. http://dx.doi.org/10.3390/en13195188.
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Optimal scheduling is a requirement for microgrids to participate in current and future energy markets. Although the number of research articles on this subject is on the rise, there is a shortage of papers containing detailed mathematical modeling of the distributed energy resources available in a microgrid. To address this gap, this paper presents in detail how to mathematically model resources such as battery energy storage systems, solar generation systems, directly controllable loads, load shedding, scheduled intentional islanding, and generation curtailment in the microgrid optimal scheduling problem. The proposed modeling also includes a methodology to determine the availability cost of battery and solar systems assets. Simulations were carried out considering energy prices from an actual time-of-use tariff, costs based on real market data, and scenarios with scheduled islanding. Simulation results provide support to validate the proposed model. Data illustrate how energy arbitrage can reduce microgrid costs in a time-of-use tariff. Results also show how the microgrid’s self-sufficiency and the storage system’s capacity can impact the microgrid’s energy bill. The findings also bring out the need to consider the scheduled islanding event in the day-ahead optimization for microgrids.
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Shezan, Sk A., Kazi Nazmul Hasan, Akhlaqur Rahman, Manoj Datta, and Ujjwal Datta. "Selection of Appropriate Dispatch Strategies for Effective Planning and Operation of a Microgrid." Energies 14, no. 21 (November 2, 2021): 7217. http://dx.doi.org/10.3390/en14217217.
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The power system responsiveness may be improved by determining the ideal size of each component and performing a reliability analysis. This study evaluated the design and optimization of an islanded hybrid microgrid system with multiple dispatch algorithms. As the penetration of renewable power increases in microgrids, the importance and influence of efficient design and operation of islanded hybrid microgrids grow. The Kangaroo Island in South Australia served as the study’s test microgrid. The sizing of the Kangaroo Island hybrid microgrid system, which includes solar PV, wind, a diesel engine, and battery storage, was adjusted for four dispatch schemes. In this study, the following dispatch strategies were used: (i) load following, (ii) cycle charging, (iii) generator order, and (iv) combination dispatch. The CO2 emissions, net present cost (NPC), and energy cost of the islanded microgrid were all optimized (COE). The HOMER microgrid software platform was used to build all four dispatch algorithms, and DIgSILENT PowerFactory was used to analyze the power system’s responsiveness and dependability. The findings give a framework for estimating the generation mix and required resources for an islanded microgrid’s optimal functioning under various dispatch scenarios. According to the simulation results, load following is the optimum dispatch technique for an islanded hybrid microgrid that achieves the lowest cost of energy (COE) and net present cost (NPC).
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langchao, He, Wu Lizhen, Chen Wei, and Hao Xiaohong. "Research on Bi-level Coordinated Optimal Dispatching Strategy for Microgrid Cluster." E3S Web of Conferences 256 (2021): 01045. http://dx.doi.org/10.1051/e3sconf/202125601045.
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The interconnection of multiple microgrids can form a microgrid cluster (MGC). The economic benefit and operation reliability of the whole system can be improved through the energy mutual-aid and coordination control between microgrids. This paper proposes a bi-level coordinated optimal dispatching strategy for microgrid clusters. The upper layer aims to minimize the operating costs of the microgrid cluster system and the power fluctuation of the tie lines. The exchange power and generation power of each sub-microgrid are coordinated and controlled, which are sent to the lower level model as scheduling instructions. The lower layer takes a single microgrid as the research object. By optimizing the output of power generation unit, the operation cost of single microgrid can be minimized. Iterative solution is adopted between the bi-level optimization models. In order to avoid the premature and local convergence of the algorithm in the optimization process, the improved artificial bee colony algorithm (ABC) is used to solve the objective function. Finally, simulation examples verify the effectiveness and feasibility of the proposed strategy.
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Wu, Xiaomin, Weihua Cao, Dianhong Wang, and Min Ding. "A Multi-Objective Optimization Dispatch Method for Microgrid Energy Management Considering the Power Loss of Converters." Energies 12, no. 11 (June 5, 2019): 2160. http://dx.doi.org/10.3390/en12112160.
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With the spreading and applying of microgrids, the economic and environment friendly microgrid operations are required eagerly. For the dispatch of practical microgrids, power loss from energy conversion devices should be considered to improve the efficiency. This paper presents a two-stage dispatch (TSD) model based on the day-ahead scheduling and the real-time scheduling to optimize dispatch of microgrids. The power loss cost of conversion devices is considered as one of the optimization objectives in order to reduce the total cost of microgrid operations and improve the utility efficiency of renewable energy. A hybrid particle swarm optimization and opposition-based learning gravitational search algorithm (PSO-OGSA) is proposed to solve the optimization problem considering various constraints. Some improvements of PSO-OGSA, such as the distribution optimization of initial populations, the improved inertial mass update rule, and the acceleration mechanism combining the memory and community of PSO, have been integrated into the proposed approach to obtain the best solution for the optimization dispatch problem. The simulation results for several benchmark test functions and an actual test microgrid are employed to show the effectiveness and validity of the proposed model and algorithm.
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Takano, Hirotaka, Ryota Goto, Ryosuke Hayashi, and Hiroshi Asano. "Optimization Method for Operation Schedule of Microgrids Considering Uncertainty in Available Data." Energies 14, no. 9 (April 27, 2021): 2487. http://dx.doi.org/10.3390/en14092487.
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Operation scheduling in electric power grids is one of the most practical optimization problems as it sets a target for the efficient management of the electric power supply and demand. Advancement of a method to solve this issue is crucially required, especially in microgrids. This is because the operational capability of microgrids is generally lower than that of conventional bulk power grids, and therefore, it is extremely important to develop an appropriate, coordinated operation schedule of the microgrid components. Although various techniques have been developed to solve the problem, there is no established solution. The authors propose a problem framework and a solution method that finds the optimal operation schedule of the microgrid components considering the uncertainty in the available data. In the authors’ proposal, the objective function of the target problem is formulated as the expected cost of the microgrid’s operations. Since the risk of imbalance in the power supply and demand is evaluated as a part of the objective function, the necessary operational reserve power is automatically calculated. The usefulness of the proposed problem framework and its solution method was verified through numerical simulations and the results are discussed.
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Abdelsalam, Mahmoud, Hatem Y. Diab, and A. A. El-Bary. "A Metaheuristic Harris Hawk Optimization Approach for Coordinated Control of Energy Management in Distributed Generation Based Microgrids." Applied Sciences 11, no. 9 (April 29, 2021): 4085. http://dx.doi.org/10.3390/app11094085.
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Cost management of microgrids represents a real challenge since the power generation of microgrids is usually composed of different renewable and non-renewable sources. Additionally, it is always desired to make a connection between the microgrid and national grid to secure the load demand and to fit the regulations of liberated energy markets. Because of all these reasons, it is essential to develop a smart energy management unit to control different energy resources within the microgrid to achieve minimum operation costs. This paper presents a proposal for a smart unit for the cost management and operation of multi-source based microgrids. The proposed unit utilizes the Harris hawk optimization (HHO) algorithm which is used to optimize the cost of operation based on current load demand, energy prices and generation capacities. The proposed unit is tested on a microgrid with different energy resources using MATLAB while applying different operation scenarios. All simulation results show that the proposed unit succeeds in operating the microgrid at minimum cost. Obtained results are compared with other optimization algorithms and the proposed Harris hawk algorithm gives superior performance.
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Dong, Jun, Yuanyuan Wang, Xihao Dou, Zhengpeng Chen, Yaoyu Zhang, and Yao Liu. "Research on Decision Optimization Model of Microgrid Participating in Spot Market Transaction." Sustainability 13, no. 12 (June 9, 2021): 6577. http://dx.doi.org/10.3390/su13126577.
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The development of electricity spot trading provides an opportunity for microgrids to participate in the spot market transaction, which is of great significance to the research of microgrids participating in the electricity spot market. Under the background of spot market construction, this paper takes the microgrid including wind power, photovoltaic (PV), gas turbine, battery storage, and demand response as the research object, uses the stochastic optimization method to deal with the uncertainty of wind and PV power, and constructs a decision optimization model with the goal of maximizing the expected revenue of microgrids in the spot market. Through the case study, the optimal bidding electricity of microgrid operators in the spot market is obtained, and the revenue is USD 923.07. Then, this paper further investigates the effects of demand response, meteorological factors, market price coefficients, and cost coefficients on the expected revenue of microgrids. The results demonstrate that the demand response adopted in this paper has better social–economic benefits, which can reduce the peak load while ensuring the reliability of the microgrid, and the optimization model also ensure profits while extreme weather and related economic coefficients change, providing a set of scientific quantitative analysis tools for microgrids to trade electricity in the spot market.
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Vegunta, Sarat Chandra, Michael J. Higginson, Yashar E. Kenarangui, George Tsai Li, David W. Zabel, Mohammad Tasdighi, and Azadeh Shadman. "AC Microgrid Protection System Design Challenges—A Practical Experience." Energies 14, no. 7 (April 6, 2021): 2016. http://dx.doi.org/10.3390/en14072016.
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Alternating current (AC) microgrids are the next step in the evolution of the electricity distribution systems. They can operate in a grid-tied or island mode. Depending on the services they are designed to offer, their grid-tied or island modes could have several sub-operational states and or topological configurations. Short-circuit current levels and protection requirements between different microgrid modes and configurations can vary significantly. Designing a microgrid’s protection system, therefore, requires a thorough understanding of all microgrid operational modes, configurations, transitional states, and how transitions between those modes are managed. As part of the microgrid protection design, speed and reliability of information flow between the microprocessor-based relays and the microgrid controller, including during microgrid failure modes, must be considered. Furthermore, utility protection practices and customer requirements are not always inclusive of the protection schemes that are unique to microgrids. These and other aspects contribute to the overall complexity and challenge of designing effective microgrid protection systems. Following a review of microgrid protection system design challenges, this paper discusses a few real-world experiences, based on the authors’ own engineering, design, and field experience, in using several approaches to address microgrid protection system design, engineering, and implementation challenges.
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Albaker, Abdullah, Mansoor Alturki, Rabeh Abbassi, and Khalid Alqunun. "Zonal-Based Optimal Microgrids Identification." Energies 15, no. 7 (March 26, 2022): 2446. http://dx.doi.org/10.3390/en15072446.
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Even though many studies have been deployed to determine the optimal planning and operation of microgrids, limited research was discussed to determine the optimal microgrids’ geographical boundaries. This paper proposes a zonal-based optimal microgrid identification model aiming at identifying the optimal microgrids topology in the current distribution systems through zoning the network into several clusters. In addition, the proposed model was developed as a mixed-integer linear programming (MILP) problem that identifies the optimal capacity and location of installing distributed energy resources (DERs), including but not limited to renewable energy resources and Battery Energy Storage Systems (BESS), within the determined microgrid’s boundaries. Moreover, it investigates the impact of incorporating the BESS in boosting the DERs’ penetration on the optimal centralized microgrid. Numerical simulations on the IEEE-33 bus test system demonstrate the features and effectiveness of the proposed model on identifying the optimal microgrid geographical boundaries on current distribution grids as well as its capability on defining the optimal sizes and locations of installing DERs within the microgrid’s zonal area.
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Wu, Haotian, Hang Li, and Xueping Gu. "Optimal Energy Management for Microgrids Considering Uncertainties in Renewable Energy Generation and Load Demand." Processes 8, no. 9 (September 2, 2020): 1086. http://dx.doi.org/10.3390/pr8091086.
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This paper proposes an efficient power management approach for the 24 h-ahead optimal maneuver of Mega–scale grid–connected microgrids containing a huge penetration of wind power, dispatchable distributed generation (diesel generator), energy storage system and local loads. The proposed energy management optimization objective aims to minimize the microgrid expenditure for fuel, operation and maintenance and main grid power import. It also aims to maximize the microgrid revenue by exporting energy to the upstream utility grid. The optimization model considers the uncertainties of the wind energy and power consumptions in the microgrids, and appropriate forecasting techniques are implemented to handle the uncertainties. The optimization model is formulated for a day-ahead optimization timeline with one-hour time steps, and it is solved using the ant colony optimization (ACO)-based metaheuristic approach. Actual data and parameters obtained from a practical microgrid platform in Atlanta, GA, USA are employed to formulate and validate the proposed energy management approach. Several simulations considering various operational scenarios are achieved to reveal the efficacy of the devised methodology. The obtained findings show the efficacy of the devised approach in various operational cases of the microgrids. To further confirm the efficacy of the devised approach, the achieved findings are compared to a pattern search (PS) optimization-based energy management approach and demonstrate outperformed performances with respect to solution optimality and computing time.
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Kharrich, Mohammed, Salah Kamel, Ali S. Alghamdi, Ahmad Eid, Mohamed I. Mosaad, Mohammed Akherraz, and Mamdouh Abdel-Akher. "Optimal Design of an Isolated Hybrid Microgrid for Enhanced Deployment of Renewable Energy Sources in Saudi Arabia." Sustainability 13, no. 9 (April 22, 2021): 4708. http://dx.doi.org/10.3390/su13094708.
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Hybrid microgrids are presented as a solution to many electrical energetic problems. These microgrids contain some renewable energy sources such as photovoltaic (PV), wind and biomass, or a hybrid of these sources, in addition to storage systems. Using these microgrids in electric power generation has many advantages such as clean energy, stability in supplying power, reduced grid congestion and a new investment field. Despite all these microgrids advantages, they are not widely used due to some economic aspects. These aspects are represented in the net present cost (NPC) and the levelized cost of energy (LCOE). To handle these economic aspects, the proper microgrids configuration according to the quantity, quality and availability of the sustainable source of energy in installing the microgrid as well as the optimal design of the microgrid components should be investigated. The objective of this paper is to design an economic microgrid system for the Yanbu region of Saudi Arabia. This design aims to select the best microgrid configuration while minimizing both NPC and LCOE considering some technical conditions, including loss of power supply probability and availability index. The optimization algorithm used is Giza Pyramids Construction (GPC). To prove the GPC algorithm’s effectiveness in solving the studied optimization problem, artificial electric field and grey wolf optimizer algorithms are used for comparison purposes. The obtained results demonstrate that the best configuration for the selected area is a PV/biomass hybrid microgrid with a minimum NPC and LCOE of $319,219 and $0.208/kWh, respectively.
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Vadi, Seyfettin, Sanjeevikumar Padmanaban, Ramazan Bayindir, Frede Blaabjerg, and Lucian Mihet-Popa. "A Review on Optimization and Control Methods Used to Provide Transient Stability in Microgrids." Energies 12, no. 18 (September 19, 2019): 3582. http://dx.doi.org/10.3390/en12183582.
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Microgrids are distribution networks consisting of distributed energy sources such as photovoltaic and wind turbines, that have traditionally been one of the most popular sources of energy. Furthermore, microgrids consist of energy storage systems and loads (e.g., industrial and residential) that may operate in grid-connected mode or islanded mode. While microgrids are an efficient source in terms of inexpensive, clean and renewable energy for distributed renewable energy sources that are connected to the existing grid, these renewable energy sources also cause many difficulties to the microgrid due to their characteristics. These difficulties mainly include voltage collapses, voltage and frequency fluctuations and phase difference faults in both islanded mode and in the grid-connected mode operations. Stability of the microgrid structure is necessary for providing transient stability using intelligent optimization methods to eliminate the abovementioned difficulties that affect power quality. This paper presents optimization and control techniques that can be used to provide transient stability in the islanded or grid-connected mode operations of a microgrid comprising renewable energy sources. The results obtained from these techniques were compared, analyzing studies in the literature and finding the advantages and disadvantages of the various methods presented. Thus, a comprehensive review of research on microgrid stability is presented to identify and guide future studies.
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Muqeet, Hafiz Abdul, Haseeb Javed, Muhammad Naveed Akhter, Muhammad Shahzad, Hafiz Mudassir Munir, Muhammad Usama Nadeem, Syed Sabir Hussain Bukhari, and Mikulas Huba. "Sustainable Solutions for Advanced Energy Management System of Campus Microgrids: Model Opportunities and Future Challenges." Sensors 22, no. 6 (March 18, 2022): 2345. http://dx.doi.org/10.3390/s22062345.
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Distributed generation connected with AC, DC, or hybrid loads and energy storage systems is known as a microgrid. Campus microgrids are an important load type. A university campus microgrids, usually, contains distributed generation resources, energy storage, and electric vehicles. The main aim of the microgrid is to provide sustainable, economical energy, and a reliable system. The advanced energy management system (AEMS) provides a smooth energy flow to the microgrid. Over the last few years, many studies were carried out to review various aspects such as energy sustainability, demand response strategies, control systems, energy management systems with different types of optimization techniques that are used to optimize the microgrid system. In this paper, a comprehensive review of the energy management system of campus microgrids is presented. In this survey, the existing literature review of different objective functions, renewable energy resources and solution tools are also reviewed. Furthermore, the research directions and related issues to be considered in future microgrid scheduling studies are also presented.
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Wang, Lin, and Anke Xue. "Equivalent Modeling of Microgrids Based on Optimized Broad Learning System." Energies 14, no. 23 (November 25, 2021): 7911. http://dx.doi.org/10.3390/en14237911.
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The DC microgrid is an important structure of microgrids. Aiming at the problem of the grid-connected DC microgrid modeling, a grid-connected DC microgrid equivalent modeling method based on the optimized Broad Learning System (BLS) is proposed. Taking the electrical parameter data of the grid-connected DC microgrid access point as the training data set of BLS, the equivalent model of the grid-connected equivalent model is constructed. In order to further improve the accuracy and generalization performance of the model, the shark smell optimization (SSO) algorithm is used to optimize the input weights and thresholds of the BLS. Furthermore, the shark smell optimization-Broad Learning System (SSO-BLS) algorithm is proposed. SSO-BLS is compared with RBF, BLS, BFO-ELM, and other algorithms. The results show that the grid-connected DC microgrid model based on SSO-BLS has good accuracy and generalization characteristics.
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Nguyen, Trong-The, Truong-Giang Ngo, Thi-Kien Dao, and Thi-Thanh-Tan Nguyen. "Microgrid Operations Planning Based on Improving the Flying Sparrow Search Algorithm." Symmetry 14, no. 1 (January 15, 2022): 168. http://dx.doi.org/10.3390/sym14010168.
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Microgrid operations planning is crucial for emerging energy microgrids to enhance the share of clean energy power generation and ensure a safe symmetry power grid among distributed natural power sources and stable functioning of the entire power system. This paper suggests a new improved version (namely, ESSA) of the sparrow search algorithm (SSA) based on an elite reverse learning strategy and firefly algorithm (FA) mutation strategy for the power microgrid optimal operations planning. Scheduling cycles of the microgrid with a distributed power source’s optimal output and total operation cost is modeled based on variables, e.g., environmental costs, electricity interaction, investment depreciation, and maintenance system, to establish grid multi-objective economic optimization. Compared with other literature methods, such as Genetic algorithm (GA), Particle swarm optimization (PSO), Firefly algorithm (FA), Bat algorithm (BA), Grey wolf optimization (GWO), and SSA show that the proposed plan offers higher performance and feasibility in solving microgrid operations planning issues.
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Barnes, Arthur K., Jose E. Tabarez, Adam Mate, and Russell W. Bent. "Optimization-Based Formulations for Short-Circuit Studies with Inverter-Interfaced Generation in PowerModelsProtection.jl." Energies 14, no. 8 (April 13, 2021): 2160. http://dx.doi.org/10.3390/en14082160.
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Protecting inverter-interfaced microgrids is challenging as conventional time-overcurrent protection becomes unusable due to the lack of fault current. There is a great need for novel protective relaying methods that enable the application of protection coordination on microgrids, thereby allowing for microgrids with larger areas and numbers of loads while not compromising reliable power delivery. Tools for modeling and analyzing such microgrids under fault conditions are necessary in order to help design such protective relaying and operate microgrids in a configuration that can be protected, though there is currently a lack of tools applicable to inverter-interfaced microgrids. This paper introduces the concept of applying an optimization problem formulation to the topic of inverter-interfaced microgrid fault modeling, and discusses how it can be employed both for simulating short-circuits and as a set of constraints for optimal microgrid operation to ensure protective device coordination.
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Almaleh, Abdulaziz, David Tipper, Saad F. Al-Gahtani, and Ragab El-Sehiemy. "A Novel Model for Enhancing the Resilience of Smart MicroGrids’ Critical Infrastructures with Multi-Criteria Decision Techniques." Applied Sciences 12, no. 19 (September 28, 2022): 9756. http://dx.doi.org/10.3390/app12199756.
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Microgrids have the potential to provide reliable electricity to key components of a smart city’s critical infrastructure after a disaster, hence boosting the microgrid power system’s resilience. Policymakers and electrical grid operators are increasingly concerned about the appropriate configuration and location of microgrids to sustain post-disaster critical infrastructure operations in smart cities. In this context, this paper presents a novel method for the microgrid allocation problem that considers several technical and economic infrastructure factors such as critical infrastructure components, geospatial positioning of infrastructures, power requirements, and microgrid cost. In particular, the geographic allocation of a microgrid is presented as an optimization problem to optimize a weighted combination of the relative importance of nodes across all key infrastructures and the associated costs. Furthermore, the simulation results of the formulated optimization problem are compared with a modified version of the heuristic method based on the critical node identification of an interdependent infrastructure for positioning microgrids in terms of the resilience of multiple smart critical infrastructures. Numerical results using infrastructure in the city of Pittsburgh in the USA are given as a practical case study to illustrate the methodology and trade-offs. The proposed method provides an effective method for localizing renewable energy resources based on infrastructural requirements.
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Henao-Muñoz, Andrés, Andrés Saavedra-Montes, and Carlos Ramos-Paja. "Optimal Power Dispatch of Small-Scale Standalone Microgrid Located in Colombian Territory." Energies 11, no. 7 (July 19, 2018): 1877. http://dx.doi.org/10.3390/en11071877.
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An optimal power dispatch of a small-scale standalone microgrid for remote area power supply in Colombian territory is proposed in this paper. The power dispatch is generated by an energy management system based on a mixed-integer linear programming, which minimizes the cost of operating the microgrid while fulfilling the technical constraints of its elements. The energy management system solves an optimization problem using the algebraic representation of the generators and its constraints. Basic steady-state models of the generators are selected to solve the optimization problem. The small-scale microgrid is considered for a remote area power supply in Taroa, a small settlement in La Guajira, Colombia. The microgrid is composed of photovoltaic modules, a wind generator, a diesel generator, a battery bank, and residential loads. To validate the solution, the elements of the microgrids are parameterized with information from commercial equipment. Moreover, the power dispatch obtained with the proposed solution is compared with a power dispatch generated by a heuristic algorithm, which has been previously used to dispatch power in a small-scale standalone microgrid. Results show that the cost of operating the microgrid is minimized using the proposed optimization approach: a reduction of the operating cost equal to 25.5% of the cost imposed by the heuristic algorithm is obtained.
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Muzzammel, Raheel, Rabia Arshad, Sobia Bashir, Uzma Mushtaq, Fariha Durrani, and Sadaf Noshin. "Comparative analysis of optimal power flow in renewable energy sources based microgrids." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 2 (April 1, 2023): 1241. http://dx.doi.org/10.11591/ijece.v13i2.pp1241-1259.
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<span lang="EN-US">Adaptation of renewable energy is inevitable. The idea of microgrid offers integration of renewable energy sources with conventional power generation sources. In this research, an operative approach was proposed for microgrids comprising of four different power generation sources. The microgrid is a way that mixes energy locally and empowers the end-users to add useful power to the network. IEEE-14 bus system-based microgrid was developed in MATLAB/Simulink to demonstrate the optimal power flow. Two cases of battery charging and discharging were also simulated to evaluate its realization. The solution of power flow analysis was obtained from the Newton–Raphson method and particle swarm optimization method. A comparison was drawn between these methods for the proposed model of the microgrid on the basis of transmission line losses and voltage profile. Transmission line losses are reduced to about 17% in the case of battery charging and 19 to 20% in the case of battery discharging when system was analyzed with the particle swarm optimization. Particle swarm optimization was found more promising for the deliverance of optimal power flow in the renewable energy sources-based microgrid.</span>
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Jadoun, Vinay Kumar, Nipun Sharma, Piyush Jha, Jayalakshmi N. S., Hasmat Malik, and Fausto Pedro Garcia Márquez. "Optimal Scheduling of Dynamic Pricing Based V2G and G2V Operation in Microgrid Using Improved Elephant Herding Optimization." Sustainability 13, no. 14 (July 6, 2021): 7551. http://dx.doi.org/10.3390/su13147551.
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The unpredictable nature of the loads and non-linearity of the components of microgrid systems make optimal scheduling more complex. In this paper, a deterministic optimal load-scheduling problem is developed for microgrids operating in both islanding and grid-connected mode under different energy scenarios. Various cases are considered in this research, based on the interaction and dynamic behavior of the microgrid, considering electric vehicles (EVs) in the scenario. The aim of this research is to minimize the overall cost of microgrid operations. The concept of dynamic pricing has also been introduced in order to optimize the energy cost for the consumers. For ensuring the stability of the microgrids, a load variance index has been considered, and the fuzzy-based approach has been used for cost and load variance minimization to reduce the operation cost without compromising the stability of the microgrid. The grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations of EVs are integrated into the microgrid, which would help in valley filling and peak shaving of the loads during the off-peak and peak hours, respectively. In order to solve the proposed complex combinatorial optimization problem, elephant herding optimization (EHO) is modified and implemented. The performance of the proposed improved EHO (IEHO) is first tested on the latest CEC test functions. The results obtained by IEHO after 100 different trials are compared with the latest published methods and are found to be better based on the average value and the standard deviation for different CEC test functions. In addition, the simulation results obtained by particle swarm optimization (PSO), EHO, and proposed IEHO on a microgrid test system for different scenarios with all cases reveal that the proposed model with a mix of energy resources in the dynamic load dispatch environment bring the maximum benefits of microgrid systems. Furthermore, the results obtained from the simulation verifies that if free trade of power is allowed between the microgrids and the main grid, the process of power generation can be more economical, and further introduction of dynamic pricing into the scenario proves to be even cheaper. The implementation of the G2V and V2G operations of EVs operations in the proposed scenario not only helped in cost minimization but also helped in stabilizing the grid.
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Ullah, Kalim, Jiang Quanyuan, Guangchao Geng, Rehan Ali Khan, Sheraz Aslam, and Wahab Khan. "Optimization of Demand Response and Power-Sharing in Microgrids for Cost and Power Losses." Energies 15, no. 9 (April 29, 2022): 3274. http://dx.doi.org/10.3390/en15093274.
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The number of microgrids within a smart distribution grid can be raised in the future. Microgrid-based distribution network reconfiguration is analyzed in this research by taking demand response programs and power-sharing into account to optimize costs and reduce power losses. The suggested method determined the ideal distribution network configuration to fulfil the best scheduling goals. The ideal way of interconnecting switches between microgrids and the main grid was also identified. For each hour of operation, the ideal topology of microgrid-based distribution networks was determined using optimal power flow. The results were produced with and without the use of a demand response program and power-sharing in each microgrid. Different load profiles, such as residential, industrial, commercial, and academic, were taken into account and modified using appropriate demand response programs and power-sharing using the Artificial Bee Colony algorithm. Various scenarios were explored independently to suit the diverse aims considered by the distribution network operator for improved observation. The ABC optimization in this research attempted to reduce the system’s total operation costs and power losses through efficient networked microgrid reconfiguration. The results of optimal microgrid topology revealed the effects of power-sharing and demand response (TOU) programs. The results obtained in the proposed idea shows that costs were reduced by 8.3% and power losses were reduced by 4%. The IEEE 33-bus test system was used to demonstrate the effectiveness of the proposed approach.
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Shafiullah, Md, Akib Mostabe Refat, Md Ershadul Haque, Dewan Mabrur Hasan Chowdhury, Md Sanower Hossain, Abdullah G. Alharbi, Md Shafiul Alam, Amjad Ali, and Shorab Hossain. "Review of Recent Developments in Microgrid Energy Management Strategies." Sustainability 14, no. 22 (November 9, 2022): 14794. http://dx.doi.org/10.3390/su142214794.
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The grid integration of microgrids and the selection of energy management systems (EMS) based on robustness and energy efficiency in terms of generation, storage, and distribution are becoming more challenging with rising electrical power demand. The problems regarding exploring renewable energy resources with efficient and durable energy storage systems demand side management and sustainable solutions to microgrid development to maintain the power system’s stability and security. This article mainly focuses on the overview of the recent developments of microgrid EMS within the control strategies and the implementation challenges of the microgrid. First, it provides energy management strategies for the major microgrid components, including load, generation, and energy storage systems. Then, it presents the different optimization approaches employed for microgrid energy management, such as classical, metaheuristic, and artificial intelligence. Moreover, this article sheds light on the major implementation challenges of microgrids. Overall, this article provides interactive guidelines for researchers to assist them in deciding on their future research.
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Halu, Arda, Antonio Scala, Abdulaziz Khiyami, and Marta C. González. "Data-driven modeling of solar-powered urban microgrids." Science Advances 2, no. 1 (January 2016): e1500700. http://dx.doi.org/10.1126/sciadv.1500700.
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Distributed generation takes center stage in today’s rapidly changing energy landscape. Particularly, locally matching demand and generation in the form of microgrids is becoming a promising alternative to the central distribution paradigm. Infrastructure networks have long been a major focus of complex networks research with their spatial considerations. We present a systemic study of solar-powered microgrids in the urban context, obeying real hourly consumption patterns and spatial constraints of the city. We propose a microgrid model and study its citywide implementation, identifying the self-sufficiency and temporal properties of microgrids. Using a simple optimization scheme, we find microgrid configurations that result in increased resilience under cost constraints. We characterize load-related failures solving power flows in the networks, and we show the robustness behavior of urban microgrids with respect to optimization using percolation methods. Our findings hint at the existence of an optimal balance between cost and robustness in urban microgrids.
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Nagarajan, Karthik, Arul Rajagopalan, S. Angalaeswari, L. Natrayan, and Wubishet Degife Mammo. "Combined Economic Emission Dispatch of Microgrid with the Incorporation of Renewable Energy Sources Using Improved Mayfly Optimization Algorithm." Computational Intelligence and Neuroscience 2022 (April 18, 2022): 1–22. http://dx.doi.org/10.1155/2022/6461690.
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Electricity can be provided to small-scale communities like commercial areas and villages through microgrid, one of the small-scale, advanced, and independent electricity systems out of the grid. Microgrid is an appropriate choice for specific purposes reducing emission and generation cost and increasing efficiency, reliability, and the utilization of renewable energy sources. The main objective of this paper is to elucidate the combined economic emission dispatch CEED problem in the microgrid to attain optimal generation cost. A combined cost optimization approach is examined to minimize operational cost and emission levels while satisfying the load demand of the microgrid. With this background, the authors proposed a novel improved mayfly algorithm incorporating Levy flight to resolve the combined economic emission dispatch problem encountered in microgrids. The islanded mode microgrid test system considered in this study comprises thermal power, solar-powered, and wind power generating units. The simulation results were considered for 24 hours with varying power demands. The minimization of total cost and emission is attained for four different scenarios. Optimization results obtained for all scenarios using IMA give a comparatively better reduction in system cost than MA and other optimization algorithms considered revealing the efficacy of IMA taken for comparison with the same data. The proposed IMA algorithm can solve the CEED problem in a grid-connected microgrid.
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Stadler, Michael, Zack Pecenak, Patrick Mathiesen, Kelsey Fahy, and Jan Kleissl. "Performance Comparison between Two Established Microgrid Planning MILP Methodologies Tested On 13 Microgrid Projects." Energies 13, no. 17 (August 28, 2020): 4460. http://dx.doi.org/10.3390/en13174460.
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Mixed Integer Linear Programming (MILP) optimization algorithms provide accurate and clear solutions for Microgrid and Distributed Energy Resources projects. Full-scale optimization approaches optimize all time-steps of data sets (e.g., 8760 time-step and higher resolutions), incurring extreme and unpredictable run-times, often prohibiting such approaches for effective Microgrid designs. To reduce run-times down-sampling approaches exist. Given that the literature evaluates the full-scale and down-sampling approaches only for limited numbers of case studies, there is a lack of a more comprehensive study involving multiple Microgrids. This paper closes this gap by comparing results and run-times of a full-scale 8760 h time-series MILP to a peak preserving day-type MILP for 13 real Microgrid projects. The day-type approach reduces the computational time between 85% and almost 100% (from 2 h computational time to less than 1 min). At the same time the day-type approach keeps the objective function (OF) differences below 1.5% for 77% of the Microgrids. The other cases show OF differences between 6% and 13%, which can be reduced to 1.5% or less by applying a two-stage hybrid approach that designs the Microgrid based on down-sampled data and then performs a full-scale dispatch algorithm. This two stage approach results in 20–99% run-time savings.
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Srinivas, Nirupama P., and Sangeeta Modi. "A Comprehensive Review of Microgrids, Control Strategies, and Microgrid Protection Schemes." ECS Transactions 107, no. 1 (April 24, 2022): 13345–70. http://dx.doi.org/10.1149/10701.13345ecst.
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For the greater part of a century, the world has moved to sustainable energy production, with increased dependence on renewable energy resources to meet growing energy demand. Reserves of conventional sources are rapidly depleting, with an environmental crisis due to profligate consumption. Distributed generation through renewable sources and microgrids have proved as sustainable alternatives. Microgrids provide versatile topologies with dispersed generation and provision for expansion. However, the nonconventionality of microgrids pose challenges and the conventional control and protection strategy have proven unsuitable. This paper attempts to be a review of microgrids, challenges, and existing protection schemes. The first segment of this paper presents the definition and overview of the microgrid market scenario. The next segment discusses microgrid classification and control strategies, following which challenges, and protection schemes are reviewed. The paper concludes with an overview of relay coordination, optimization algorithms, and an outline of few international microgrid standards and codes.
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Zhong, Xianjing, Xianbo Sun, and Yuhan Wu. "A Capacity Optimization Method for a Hybrid Energy Storage Microgrid System Based on an Augmented ε-Constraint Method." Energies 15, no. 20 (October 14, 2022): 7593. http://dx.doi.org/10.3390/en15207593.
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In general, microgrids have a high renewable energy abandonment rate and high grid construction and operation costs. To improve the microgrid renewable energy utilization rate, the economic advantages, and environmental safety of power grid operation, we propose a hybrid energy storage capacity optimization method for a wind–solar–diesel grid-connected microgrid system, based on an augmented ε- constraint method. First, the battery is coupled with a seasonal hydrogen energy storage system to establish a hybrid energy storage model that avoids the shortcomings of traditional microgrid systems, such as a single energy storage mode and a small capacity. Second, by considering the comprehensive cost and carbon emissions of the power grid within the planning period as the objective function, the abandonment rate of renewable energy as the evaluation index, and the electric energy storage and seasonal hydrogen energy storage system operating conditions as the main constraints, the capacity allocation model of the microgrid can be constructed. Finally, an augmented ε- constraint method is implemented to optimize the model above; the entropy–TOPSIS method is used to select the configuration scheme. By comparative analysis, the results show that the optimization method can effectively improve the local absorption rate of wind and solar radiation, and significantly reduce the carbon emissions of microgrids.
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Pan, Hao, Ming Ding, Anwei Chen, Rui Bi, Lei Sun, and Shengliang Shi. "Research on Distributed Power Capacity and Site Optimization Planning of AC/DC Hybrid Micrograms Considering Line Factors." Energies 11, no. 8 (July 24, 2018): 1930. http://dx.doi.org/10.3390/en11081930.
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With the rapid development of AC/DC hybrid microgrids and the widespread use of distributed power resources, planning strategies for microgrids with high-density distributed power generation have become an urgent problem. Because current research on microgrid planning has not considered line factors, this paper analyses the planning of an AC/DC hybrid microgrid based on an AC microgrid. The capacity and siting of the distributed power resources are optimized, taking into account the influence of the line investment cost and the interactive power upper limit on the planning results. In the proposed model, the objective is aimed at minimizing the sum of investment cost, load-loss economic cost, and system losses, taking into consideration power balance constraints and feeder number constraints. The commercial solver CPLEX is applied to attain the optimal distributed power capacity and site. The theoretical results are verified by an actual system.
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Chen, Jin, Changsong Chen, and Shanxu Duan. "Cooperative Optimization of Electric Vehicles and Renewable Energy Resources in a Regional Multi-Microgrid System." Applied Sciences 9, no. 11 (May 31, 2019): 2267. http://dx.doi.org/10.3390/app9112267.
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By integrating renewable energy sources (RESs) with electric vehicles (EVs) in microgrids, we are able to reduce carbon emissions as well as alleviate the dependence on fossil fuels. In order to improve the economy of an integrated system and fully exploit the potentiality of EVs’ mobile energy storage while achieving a reasonable configuration of RESs, a cooperative optimization method is proposed to cooperatively optimize the economic dispatching and capacity allocation of both RESs and EVs in the context of a regional multi-microgrid system. An across-time-and-space energy transmission (ATSET) of the EVs was considered, and the impact of ATSET of EVs on economic dispatching and capacity allocation of multi-microgrid system was analyzed. In order to overcome the difficulty of finding the global optimum of the non-smooth total cost function, an improved particle swarm optimization (IPSO) algorithm was used to solve the cooperative optimization problem. Case studies were performed, and the simulation results show that the proposed cooperative optimization method can significantly decrease the total cost of a multi-microgrid system.
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Baumann, Manuel, Sara Grundel, Philipp Sauerteig, and Karl Worthmann. "Surrogate models in bidirectional optimization of coupled microgrids." at - Automatisierungstechnik 67, no. 12 (November 18, 2019): 1035–46. http://dx.doi.org/10.1515/auto-2019-0075.
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Abstract The energy transition entails a rapid uptake of renewable energy sources. Besides physical changes within the grid infrastructure, energy storage devices and their smart operation are key measures to master the resulting challenges like, e. g., a highly fluctuating power generation. For the latter, optimization based control has demonstrated its potential on a microgrid level. However, if a network of coupled microgrids is considered, iterative optimization schemes including several communication rounds are typically used. Here, we propose to replace the optimization on the microgrid level by using surrogate models either derived from radial basis functions or neural networks to avoid this iterative procedure. We prove well-posedness of our approach and demonstrate its efficiency by numerical simulations based on real data provided by an Australian grid operator.
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Ali, Sadaqat, Zhixue Zheng, Michel Aillerie, Jean-Paul Sawicki, Marie-Cécile Péra, and Daniel Hissel. "A Review of DC Microgrid Energy Management Systems Dedicated to Residential Applications." Energies 14, no. 14 (July 17, 2021): 4308. http://dx.doi.org/10.3390/en14144308.
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The fast depletion of fossil fuels and the growing awareness of the need for environmental protection have led us to the energy crisis. Positive development has been achieved since the last decade by the collective effort of scientists. In this regard, renewable energy sources (RES) are being deployed in the power system to meet the energy demand. The microgrid concept (AC, DC) is introduced, in which distributed energy resources (DERs), the energy storage system (ESS) and loads are interconnected. DC microgrids are appreciated due to their high efficiency and reliability performance. Despite its significant growth, the DC microgrid is still relatively novel in terms of grid architecture and control systems. In this context, an energy management system (EMS) is essential for the optimal use of DERs in secure, reliable, and intelligent ways. Therefore, this paper strives to shed light on DC microgrid architecture, control structure, and EMS. With an extensive literature survey on EMSs’ role, different methods and strategies related to microgrid energy management are covered in this article. More attention is centered on the EMS for DC microgrids in terms of size and cost optimization. A very concise analysis of multiple optimization methods and techniques has been presented exclusively for residential applications.
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Tomoiaga, Bogdan, Mircea D. Chindris, Andreas Sumper, and Mousa Marzband. "The Optimization of Microgrids Operation through a Heuristic Energy Management Algorithm." Advanced Engineering Forum 8-9 (June 2013): 185–94. http://dx.doi.org/10.4028/www.scientific.net/aef.8-9.185.
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The concept of microgrid was first introduced in 2001 as a solution for reliable integration of distributed generation and for harnessing their multiple advantages. Specific control and energy management systems must be designed for the microgrid operation in order to ensure reliable, secure and economical operation; either in grid-connected or stand-alone operating mode. The problem of energy management in microgrids consists of finding the optimal or near optimal unit commitment and dispatch of the available sources and energy storage systems so that certain selected criteria are achieved. In most cases, energy management problem do not satisfy the Bellman's principle of optimality because of the energy storage systems. Consequently, in this paper, an original fast heuristic algorithm for the energy management on stand-alone microgrids, which avoids wastage of the existing renewable potential at each time interval, is presented. A typical test microgrid has been analysed in order to demonstrate the accuracy and the promptness of the proposed algorithm. The obtained cost of energy is low (the quality of the solution is high), the primary adjustment reserve is correspondingly assured by the energy storage system and the execution runtime is very short (a fast algorithm). Furthermore, the proposed algorithm can be used for real-time energy management systems.
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Liu, Guangyu, Haonan Zhang, Ruiheng Shang, Zhenyu Wu, and Qingdong Song. "Hierarchical Optimization Scheduling of Active Demand Response for Distribution Networks in 5G Base Stations." Wireless Communications and Mobile Computing 2022 (April 13, 2022): 1–15. http://dx.doi.org/10.1155/2022/8666749.
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The study aims to solve the problem that the traditional scheduling optimization model does not apply to the multimicrogrid systems in the 5th generation mobile networks (5G). First, the response characteristics of the 5G base station energy storage demand are analyzed. Second, a microgrid hybrid power supply system is proposed. Third, a multimicrogrid demand response hierarchical optimal scheduling model based on the game is constructed, and the game interaction mechanism between various stakeholders in the demand response is studied. Finally, the strategy of each microgrid in the IEEE-9 bus system in the game bidding is simulated by a genetic algorithm (GA), and the simulation experiment is carried out by Matlab. The results show that (1) after the optimization of the multimicrogrid system, the overall load of the microgrid is reduced, the independent energy optimization is carried out according to the energy access of each microgrid, and renewable energy is fully used. (2) Based on the game-based time-sharing bidding strategy, the system gives priority to the low-cost microgrid for power supply and saves the cost. (3) The load transfer capacity of the three microgrids obtained by the model are 132.7 kW, 47.1 kW, and 46.4 kW, which is within the actual load range of each microgrid; their electricity sales are 665.8 kWh, 2053.3 kWh, and 1668.2 kWh; and their income is 132.45 CNY, 411.72 CNY, and 354.63 CNY, respectively. This shows that the game equilibrium index makes the power sales of each microgrid proportional to its income, which ensures the fair and effective scheduling in the bidding process. The study provides technical support for the construction of a 5G base station and the active demand response scheduling optimization of distribution networks.
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Saleh, Amr, Walid A. Omran, Hany M. Hasanien, Marcos Tostado-Véliz, Abdulaziz Alkuhayli, and Francisco Jurado. "Manta Ray Foraging Optimization for the Virtual Inertia Control of Islanded Microgrids Including Renewable Energy Sources." Sustainability 14, no. 7 (April 1, 2022): 4189. http://dx.doi.org/10.3390/su14074189.
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Nowadays, the penetration level of renewable energy sources (RESs) has increased dramatically in electrical networks, especially in microgrids. Due to the replacement of conventional synchronous generators by RESs, the inertia of the microgrid is significantly reduced. This has a negative impact on the dynamics and performance of the microgrid in the face of uncertainties, resulting in a weakening of microgrid stability, especially in an islanded operation. Hence, this paper focuses on enhancing the dynamic security of an islanded microgrid using a frequency control concept based on virtual inertia control. The control in the virtual inertia control loop was based on a proportional-integral (PI) controller optimally designed by the Manta Ray Foraging Optimization (MRFO) algorithm. The performance of the MRFO-based PI controller was investigated considering various operating conditions and compared with that of other evolutionary optimization algorithm-based PI controllers. To achieve realistic simulations conditions, actual wind data and solar power data were used, and random load fluctuations were implemented. The results show that the MRFO-based PI controller has a superior performance in frequency disturbance alleviation and reference frequency tracking compared with the other considered optimization techniques.
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Ramli, Makbul A. M., H. R. E. H. Bouchekara, and Abdulsalam S. Alghamdi. "Efficient Energy Management in a Microgrid with Intermittent Renewable Energy and Storage Sources." Sustainability 11, no. 14 (July 14, 2019): 3839. http://dx.doi.org/10.3390/su11143839.
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Substituting a single large power grid into various manageable microgrids is the emerging form for maintaining power systems. A microgrid is usually comprised of small units of renewable energy sources, battery storage, combined heat and power (CHP) plants and most importantly, an energy management system (EMS). An EMS is responsible for the core functioning of a microgrid, which includes establishing continuous and reliable communication among all distributed generation (DG) units and ensuring well-coordinated activities. This research focuses on improving the performance of EMS. The problem at hand is the optimal scheduling of the generation units and battery storage in a microgrid. Therefore, EMS should ensure that the power is shared among different sources following an imposed scenario to meet the load requirements, while the operational costs of the microgrid are kept as low as possible. This problem is formulated as an optimization problem. To solve this problem, this research proposes an enhanced version of the most valuable player algorithm (MVPA) which is a new metaheuristic optimization algorithm, inspired by actual sporting events. The obtained results are compared with numerous well-known optimization algorithms to validate the efficiency of the proposed EMS.
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Marchand, Sophie, Cristian Monsalve, Thorsten Reimann, Wolfram Heckmann, Jakob Ungerland, Hagen Lauer, Stephan Ruhe, and Christoph Krauß. "Microgrid Systems: Towards a Technical Performance Assessment Frame." Energies 14, no. 8 (April 13, 2021): 2161. http://dx.doi.org/10.3390/en14082161.
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A microgrid is an independent power system that can be connected to the grid or operated in an islanded mode. This single grid entity is widely used for furthering access to energy and ensuring reliable energy supply. However, if islanded, microgrids do not benefit from the high inertia of the main grid and can be subject to high variations in terms of voltage and frequency, which challenge their stability. In addition, operability and interoperability requirements, standards as well as directives have addressed main concerns regarding a microgrid’s reliability, use of distributed local resources and cybersecurity. Nevertheless, microgrid systems are quickly evolving through digitalization and have a large range of applications. Thus, a consensus over their testing must be further developed with the current technological development. Here, we describe existing technical requirements and assessment criteria for a microgrid’s main functionalities to foster harmonization of functionality-level testing and an international conception of system-level one. This framework is proposed as a reference document for assessment frame development serving both microgrid research and implementation for a comprehensive understanding of technical microgrid performance and its current assessment challenges, such as lack of standardization and evolving technology.
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Lainfiesta, Maximiliano, and Xuewei Zhang. "Frequency Stability and Economic Operation of Transactive Multi-Microgrid Systems with Variable Interconnection Configurations." Energies 13, no. 10 (May 14, 2020): 2485. http://dx.doi.org/10.3390/en13102485.
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With the progressive addition of microgrids at the distribution level, complex networks of interconnected microgrids and the utility grid are likely to emerge. In such a scenario, advanced microgrid controllers are required to achieve operational stability objectives while maintaining a cost-effective operation. This paper investigates the control strategies, trading mechanisms, and interconnection configurations of a multi-microgrid and utility grid system for frequency stability analysis and operational cost optimization. The analysis is performed on a model of two interconnected microgrids and the utility grid, all possible interconnection configurations are tested. A robust controller is designed and the control parameters are later optimized to ensure that the frequency stability of the system is maintained under normal operating conditions and under various disturbances. A new control element based on switching between interconnection configurations is introduced to handle the power that flows between microgrids, aiming to minimize inter-microgrid energy trading cost while maintaining the system frequency fluctuations within tolerance levels. The effectiveness of the designed controller is demonstrated in this work. This work is expected to provide new insights in the field of multi-microgrid system design.
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Rezaei, Omid, Omid Mirzapour, Mohammad Panahazari, and Hassan Gholami. "Hybrid AC/DC Provisional Microgrid Planning Model Considering Converter Aging." Electricity 3, no. 2 (June 7, 2022): 236–50. http://dx.doi.org/10.3390/electricity3020014.
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Renewable energy deployment through distributed energy resources is among the central goals of future power systems. Microgrids have proven to be an economically viable solution for distributed energy resources’ integration into the power system and benefits customers with uninterrupted power supply. In this context, provisional microgrids have been introduced with the main goal of rapid renewable energy resource deployment. Since a considerable portion of renewable energy resources, as well as residential loads, are DC, and this portion is expected to grow even further, hybrid AC/DC design of provisional microgrids can improve both efficiency and economic benefit through an optimal arrangement of AC/DC feeders and converters. This paper presents a planning model for hybrid provisional microgrids considering the long-term influence of energy storage and the aging process of converters on economic revenues. Due to several intrinsic uncertainties involved in provisional microgrid operation, robust optimization is applied to the problem to ensure optimality under worst-case conditions. Results show the economic benefits of a hybrid provisional microgrid compared to a provisional microgrid and independent microgrid. Several sensitivity analyses are carried out to identify critical factors in planning.
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Oyekanlu, Emmanuel. "FUZZY INFERENCE BASED STABILITY OPTIMIZATION FOR IOT DATA CENTERS DC MICROGRIDS: IMPACT OF CONSTANT POWER LOADS ON SMART GRID COMMUNICATION OVER THE POWERLINE." Journal of Energy - Energija 68, no. 1 (February 23, 2019): 11–21. http://dx.doi.org/10.37798/20196811.
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Direct Current (dc) microgrids due to their efficiency and energy savings are being deployed to provide power for servers in Internet of Things (IoT) data centers, in more electric aircrafts (MEA), electric ships and in rail systems round the word. In this paper, Takagi-Sugeno fuzzy inference method is used to establish a Lyapunov stability candidate for a 380 V ring bus dc microgrid modeled with Matlab. To determine suitability of using powerline communication (PLC) to monitor stability condition on the 380 V dc microgrid, impact of distortion caused by microgrid constant power loads (CPL) on signals transmitted over the dc microgrid PLC channel is examined. It is shown in this paper that while Lyapunov asymptotic stability is maintained on the dc bus, increasing CPL on the microgrid causes the dc microgrid PLC channel to experience growing signal distortion.
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Li, Shuyi, Xifeng Zhou, and Qiangang Guo. "Research on Microgrid Optimization Based on Simulated Annealing Particle Swarm Optimization." E3S Web of Conferences 118 (2019): 01038. http://dx.doi.org/10.1051/e3sconf/201911801038.
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Based on the pursuit of different goals in the operation of the microgrid, it is not possible to meet the lowest cost and the least pollution at the same time. From the perspective of economy and environmental protection, a microgrid model including photovoltaic power generation, wind power generation, micro gas turbine, fuel cell and energy storage device is proposed. This paper establishes a comprehensive benefit objective function that considers both microgrid fuel cost, maintenance management cost, depreciation cost, interaction cost with public grid and pollutant treatment cost. In order to avoid the defect that the traditional particle swarm optimization algorithm is easy to fall into the local optimal solution, this paper uses the combination of simulated annealing algorithm and particle swarm optimization algorithm to compare with the traditional particle swarm optimization algorithm to obtain a more suitable method for microgrid operation. Finally, a typical microgrid in China is taken as an example to verify the feasibility of the algorithm.
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Zulu, Musawenkosi Lethumcebo Thanduxolo, Rudiren Pillay Carpanen, and Remy Tiako. "A Comprehensive Review: Study of Artificial Intelligence Optimization Technique Applications in a Hybrid Microgrid at Times of Fault Outbreaks." Energies 16, no. 4 (February 10, 2023): 1786. http://dx.doi.org/10.3390/en16041786.
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The use of fossil-fueled power stations to generate electricity has had a damaging effect over the years, necessitating the need for alternative energy sources. Microgrids consisting of renewable energy source concepts have gained a lot of consideration in recent years as an alternative because they use advances in information and communication technology (ICT) to increase the quality and efficiency of services and distributed energy resources (DERs), which are environmentally friendly. Nevertheless, microgrids are constrained by the outbreaks of faults, which have an impact on their performance and necessitate dynamic energy management and optimization strategies. The application of artificial intelligence (AI) is gaining momentum as a vital key at this point. This study focuses on a comprehensive review of applications of artificial intelligence strategies on hybrid renewable microgrids for optimization, power quality enhancement, and analyses of fault outbreaks in microgrids. The use of techniques such as machine learning (ML), genetic algorithms (GA), artificial neural networks (ANN), fuzzy logic (FL), particle swarm optimization (PSO), heuristic optimization, artificial bee colony (ABC), and others is reviewed for various microgrid strategies such as regression and classification in this study. Applications of AI in microgrids are reviewed together with their benefits, drawbacks, and prospects for the future. The coordination and maximum penetration of renewable energy, solar PV, and wind in a hybrid microgrid under fault outbreaks are furthermore reviewed.
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García-Vera, Yimy, Rodolfo Dufo-López, and José Bernal-Agustín. "Optimization of Isolated Hybrid Microgrids with Renewable Energy Based on Different Battery Models and Technologies." Energies 13, no. 3 (January 26, 2020): 581. http://dx.doi.org/10.3390/en13030581.
Full textAbstract:
Energy supply in remote areas (mainly in developing countries such as Colombia) has become a challenge. Hybrid microgrids are local and reliable sources of energy for these areas where access to the power grid is generally limited or unavailable. These systems generally include a diesel generator, solar modules, wind turbines, and storage devices such as batteries. Battery life estimation is an essential factor in the optimization of a hybrid microgrid since it determines the system’s final costs, including future battery replacements. This article presents a comparison of different technologies and battery models in a hybrid microgrid. The optimization is achieved using the iHOGA software, based on data from a real microgrid in Colombia. The simulation results allowed the comparison of prediction models for lifespan calculation for both lead–acid and lithium batteries in a hybrid microgrid, showing that the most accurate models are more realistic in predicting battery life by closely estimating real lifespans that are shorter, unlike other simplified methods that obtain much longer and unrealistic lifetimes.
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Wang, Peng, Yu Zhang, and Hongwan Yang. "Research on Economic Optimization of Microgrid Cluster Based on Chaos Sparrow Search Algorithm." Computational Intelligence and Neuroscience 2021 (March 10, 2021): 1–18. http://dx.doi.org/10.1155/2021/5556780.
Full textAbstract:
With the deepening of the power market reform on the retail side, it is of great significance to study the economic optimization of the microgrid cluster system. Aiming at the economics of the microgrid cluster, comprehensively considering the degradation cost of energy storage battery, the compensation cost of demand-side controllable loads dispatch, the electricity transaction cost between the microgrids, and the electricity transaction cost between the microgrid and the power distribution network of the microgrid cluster, we establish an optimal dispatch model for the microgrid cluster including wind turbines, photovoltaics, and energy storage batteries. At the same time, in view of the problem that the population diversity of the basic sparrow search algorithm decreases and it is easy to fall into local extremes in the later iterations of the basic sparrow search algorithm, a chaos sparrow search algorithm based on Bernoulli chaotic mapping, dynamic adaptive weighting, Cauchy mutation, and reverse learning is proposed, and different types of test functions are used to analyze the convergence effect of the algorithm, and the calculation effects of the sparrow algorithm, the particle swarm algorithm, the chaotic particle swarm, and the genetic algorithm are compared. The algorithm has higher convergence speed, higher accuracy, and better global optimization ability. Finally, through the calculation example, it is concluded that the benefit of the microgrid cluster is increased by nearly 20%, which verifies the effectiveness of the improvement.
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Pan, Tinglong, Hui Liu, Dinghui Wu, and Zeliang Hao. "Dual-Layer Optimal Dispatching Strategy for Microgrid Energy Management Systems considering Demand Response." Mathematical Problems in Engineering 2018 (July 8, 2018): 1–14. http://dx.doi.org/10.1155/2018/2695025.
Full textAbstract:
The continuous development of microgrid’s technology creates favorable conditions for the access of distributed energy. Firstly, in order to consider the interests of the demand side and the power side, this paper presents a dual-layer optimal dispatching model of microgrid based on demand response. The objective of the first-layer optimization is to obtain the maximum load satisfaction and to optimize the load curve. The objective of the second-layer optimization is to make the microgrid system economical and environmentally friendly and to optimize the power utilization ratio. And a microsource control strategy based on the isolated microgrid is proposed, which can optimize the operation state of battery and improve the economy of the system. Finally, the Nondominated Sorting Genetic Algorithm-II (NSGA-II) is adopted to solve the optimal scheduling problem of the isolated microgrid. The simulation results indicate that the microsource scheduling strategy proposed in this paper can improve the operation economy and environmental conservation of the system. It can improve the reliability of microgrid power supply and reduce energy waste.