Journal articles: 'Virtual Power Plants'

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Kumagai, Jean. "Virtual power plants, real power." IEEE Spectrum 49, no. 3 (March 2012): 13–14. http://dx.doi.org/10.1109/mspec.2012.6156852.

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Newman, Guy, and Joseph Mutale. "Characterising Virtual Power Plants." International Journal of Electrical Engineering & Education 46, no. 4 (October 2009): 307–18. http://dx.doi.org/10.7227/ijeee.46.4.1.

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Dall'Anese, Emiliano, Swaroop S. Guggilam, Andrea Simonetto, Yu Christine Chen, and Sairaj V. Dhople. "Optimal Regulation of Virtual Power Plants." IEEE Transactions on Power Systems 33, no. 2 (March 2018): 1868–81. http://dx.doi.org/10.1109/tpwrs.2017.2741920.

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Paniah, Crédo, Cédric Herpson, and Javier Gil-Quijano. "A Markov Decision Model for Cooperative Virtual Power Plants Market Participation." Journal of Clean Energy Technologies 3, no. 4 (2015): 302–11. http://dx.doi.org/10.7763/jocet.2015.v3.213.

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Przychodzień, Arkadiusz. "Virtual power plants - types and development opportunities." E3S Web of Conferences 137 (2019): 01044. http://dx.doi.org/10.1051/e3sconf/201913701044.

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Modern power engineering meets new challenges. With the development of new energy production and storage technologies, creates new demands for energy services. To support this development, it is necessary to implement new teleinformatic systems that will allow for resource management. Such systems are called Virtual Power Plants (VPP). There are many definitions of this type of solutions due to the very wide range of possible applications. VPPs can be developed by many types of entities, e.g. distribution system operators, electricity generators, energy clusters. The ability to build a system based on modules allows you to customize the system to user’s needs. An opportunity for the development of VPP will be a package “Clean energy for all Europeans” (so called “Winter package”) that introduces regulations that allow for the development of renewable energy sources, including prosumers, and enables an active participation in the energy market for energy consumers. In addition, more stringent requirements for balancing production and energy consumption are introduced, requiring greater balancing accuracy.

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Sadeghian, Omid, Amin Mohammadpour Shotorbani, and Behnam Mohammadi-Ivatloo. "Generation maintenance scheduling in virtual power plants." IET Generation, Transmission & Distribution 13, no. 12 (June 18, 2019): 2584–96. http://dx.doi.org/10.1049/iet-gtd.2018.6751.

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Caixia, Tan, Tan Zhongfu, Wu Jianbin, Qi Huiwen, Zhang Xiangyu, and Xu Zhenbo. "Benefit analysis and evaluation of virtual power plants considering electric vehicles." E3S Web of Conferences 248 (2021): 02024. http://dx.doi.org/10.1051/e3sconf/202124802024.

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Under the background of increasingly serious environmental pollution, virtual power plants have become an effective way to solve environmental pollution due to the characteristics of integrating a large number of clean distributed energy generation. At the same time, electric vehicles with dual attributes of power supply and load bring opportunities for the further development of virtual power plants. In this paper, the ideal matter-element comprehensive benefit evaluation model of virtual power plants is constructed by constructing the index system and weighting model of virtual power plants considering electric vehicles. The virtual power plants connected with different proportion of electric vehicles are taken as an example analysis. The results of the example analysis show that the comprehensive benefit of virtual power plants is the highest when the proportion of electric vehicles access reaches 120%.

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Tan, Zhongfu, Qingkun Tan, and Yuwei Wang. "Bidding Strategy of Virtual Power Plant with Energy Storage Power Station and Photovoltaic and Wind Power." Journal of Engineering 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/6139086.

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For the virtual power plants containing energy storage power stations and photovoltaic and wind power, the output of PV and wind power is uncertain and virtual power plants must consider this uncertainty when they participate in the auction in the electricity market. In this context, this paper studies the bidding strategy of the virtual power plant with photovoltaic and wind power. Assuming that the upper and lower limits of the combined output of photovoltaic and wind power are stochastically variable, the fluctuation range of the day-ahead energy market and capacity price is stochastically variable. If the capacity of the storage station is large enough to stabilize the fluctuation of the output of the wind and photovoltaic power, virtual power plants can participate in the electricity market bidding. This paper constructs a robust optimization model of virtual power plant bidding strategy in the electricity market, which considers the cost of charge and discharge of energy storage power station and transmission congestion. The model proposed in this paper is solved by CPLEX; the example results show that the model is reasonable and the method is valid.

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Wu, Yungao, Jing Wu, and Gejirifu De. "Research on Trading Optimization Model of Virtual Power Plant in Medium- and Long-Term Market." Energies 15, no. 3 (January 20, 2022): 759. http://dx.doi.org/10.3390/en15030759.

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In the medium- and long-term market, the power generation side and the power purchase side ensure to avoid the fluctuation of delivery prices through the medium- and long-term power contract, to avoid some market risks. This paper combines virtual power plants to aggregate distributed renewable energy to participate in market transactions. Firstly, this paper analyzes the two operation modes of power markets and combs the transaction varieties and modes in the medium- and long-term market. Secondly, the common contract power decomposition methods in the medium- and long-term market are analyzed, and the revenue model of virtual power plants is established. Then, combined with the renewable energy quota system and the green certificate trading mechanism, this paper constructs an optimization model of medium- and long-term contract trading of virtual power plants considering renewable energy derivatives. Finally, different renewable energy output scenarios are designed to analyze the benefits of virtual power plants in centralized and decentralized power markets. The example analysis shows the effectiveness of price difference contract for virtual power plants to ensure the renewable power revenue, which provides a certain reference for virtual power plants to participate in the power market.

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Zhong, Weilin, Georgios Tzounas, Muyang Liu, and Federico Milano. "On-line inertia estimation of Virtual Power Plants." Electric Power Systems Research 212 (November 2022): 108336. http://dx.doi.org/10.1016/j.epsr.2022.108336.

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Barbosa, J. A., R. P. S. Leao, C. F. P. Lima, and M. C. O. Rego. "Decentralised Energy Management System to Virtual Power Plants." Renewable Energy and Power Quality Journal 1, no. 08 (April 2010): 1079–85. http://dx.doi.org/10.24084/repqj08.590.

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Mourik, Ruth, Sylvia Breukers, LFM Summeren, and A. C. Wieczorek. "Community-Based Virtual Power Plants: Against All Odds?" Proceedings 20, no. 1 (August 20, 2019): 25. http://dx.doi.org/10.3390/proceedings2019020025.

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Based on a European project entitled “Community-based Virtual Power Plants’ (Interreg 2017–2010) this paper discusses opportunities for community energy projects—focusing on the example of community-based virtual power plants. Using a business model canvas as heuristic and the Dutch demonstration case as an example, we show how a business model following a community logic is unfeasible in practice. The current institutional context compels community based cVPP initiatives to partially abandon such community-based values, in order to be able to survive in the energy services market. It is concluded that more attention is needed for institutional change since the current institutional bias that hinders cVPP projects is also hindering a more inclusive energy transition.

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Adu-Kankam, Kankam O., and Luis M. Camarinha-Matos. "Towards collaborative Virtual Power Plants: Trends and convergence." Sustainable Energy, Grids and Networks 16 (December 2018): 217–30. http://dx.doi.org/10.1016/j.segan.2018.08.003.

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Wille-Haussmann, Bernhard, Thomas Erge, and Christof Wittwer. "Decentralised optimisation of cogeneration in virtual power plants." Solar Energy 84, no. 4 (April 2010): 604–11. http://dx.doi.org/10.1016/j.solener.2009.10.009.

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Liu, Chengyang, Rebecca Jing Yang, Xinghuo Yu, Chayn Sun, Peter S. P. Wong, and Hongying Zhao. "Virtual power plants for a sustainable urban future." Sustainable Cities and Society 65 (February 2021): 102640. http://dx.doi.org/10.1016/j.scs.2020.102640.

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Okuneva, V. V., A. A. Agamirzoev, and K. B. Korneev. "IMPLEMENTING DISTRIBUTED GENERATION BY CREATING VIRTUAL POWER PLANTS." Bulletin of the Tver State Technical University. Series «Building. Electrical engineering and chemical technology», no. 3 (2020): 51–59. http://dx.doi.org/10.46573/2658-7459-2020-3-51-59.

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We consider one of the most promising technologies for solving the problem of balancing a system with distributed generation is a virtual substation. It is noted that using the technologies of distributed computing and the «Internet of things», it is possible to implement an effective mechanism for decentralized control of power system elements.

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Moreno, Guillermo, Carlos Santos, Pedro Martín, Francisco Javier Rodríguez, Rafael Peña, and Branislav Vuksanovic. "Intra-Day Solar Power Forecasting Strategy for Managing Virtual Power Plants." Sensors 21, no. 16 (August 22, 2021): 5648. http://dx.doi.org/10.3390/s21165648.

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Solar energy penetration has been on the rise worldwide during the past decade, attracting a growing interest in solar power forecasting over short time horizons. The increasing integration of these resources without accurate power forecasts hinders the grid operation and discourages the use of this renewable resource. To overcome this problem, Virtual Power Plants (VPPs) provide a solution to centralize the management of several installations to minimize the forecasting error. This paper introduces a method to efficiently produce intra-day accurate Photovoltaic (PV) power forecasts at different locations, by using free and available information. Prediction intervals, which are based on the Mean Absolute Error (MAE), account for the forecast uncertainty which provides additional information about the VPP node power generation. The performance of the forecasting strategy has been verified against the power generated by a real PV installation, and a set of ground-based meteorological stations in geographical proximity have been used to emulate a VPP. The forecasting approach is based on a Long Short-Term Memory (LSTM) network and shows similar errors to those obtained with other deep learning methods published in the literature, offering a MAE performance of 44.19 W/m2 under different lead times and launch times. By applying this technique to 8 VPP nodes, the global error is reduced by 12.37% in terms of the MAE, showing huge potential in this environment.

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Gong, Jinxia, Da Xie, Chuanwen Jiang, and Yanchi Zhang. "Multiple Objective Compromised Method for Power Management in Virtual Power Plants." Energies 4, no. 4 (April 21, 2011): 700–716. http://dx.doi.org/10.3390/en4040700.

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Cioara, Tudor, Marcel Antal, Vlad T. Mihailescu, Claudia D. Antal, Ionut M. Anghel, and Dan Mitrea. "Blockchain-Based Decentralized Virtual Power Plants of Small Prosumers." IEEE Access 9 (2021): 29490–504. http://dx.doi.org/10.1109/access.2021.3059106.

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Venkatachary, Sampath Kumar, Jagdish Prasad, Ravi Samikannu, Annamalai Alagappan, and Leo John Baptist Andrews. "Cybersecurity infrastructure challenges in IoT based virtual power plants." Journal of Statistics and Management Systems 23, no. 2 (February 17, 2020): 263–76. http://dx.doi.org/10.1080/09720510.2020.1724625.

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21

Alahyari, Arman, Mehdi Ehsan, David Pozo, and Meisam Farrokhifar. "Hybrid uncertainty-based offering strategy for virtual power plants." IET Renewable Power Generation 14, no. 13 (October 5, 2020): 2359–66. http://dx.doi.org/10.1049/iet-rpg.2020.0249.

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Podder, Amit Kumer, Sayemul Islam, Nallapaneni Manoj Kumar, Aneesh A. Chand, Pulivarthi Nageswara Rao, Kushal A. Prasad, T. Logeswaran, and Kabir A. Mamun. "Systematic Categorization of Optimization Strategies for Virtual Power Plants." Energies 13, no. 23 (November 27, 2020): 6251. http://dx.doi.org/10.3390/en13236251.

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Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development.

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Asmus, Peter. "Microgrids, Virtual Power Plants and Our Distributed Energy Future." Electricity Journal 23, no. 10 (December 2010): 72–82. http://dx.doi.org/10.1016/j.tej.2010.11.001.

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Shabanzadeh, Morteza, Mohammad-Kazem Sheikh-El-Eslami, and Mahmoud-Reza Haghifam. "An interactive cooperation model for neighboring virtual power plants." Applied Energy 200 (August 2017): 273–89. http://dx.doi.org/10.1016/j.apenergy.2017.05.066.

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Löschenbrand, Markus. "Modeling competition of virtual power plants via deep learning." Energy 214 (January 2021): 118870. http://dx.doi.org/10.1016/j.energy.2020.118870.

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Thomas, Duerr, Miller Iain, and Geach Dale. "Virtual power plants leveraging energy flexibility in regional markets." CIRED - Open Access Proceedings Journal 2017, no. 1 (October 1, 2017): 2939–43. http://dx.doi.org/10.1049/oap-cired.2017.0867.

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Ying, Zhiwei, Tao Yu, Yupeng Huang, Dunnan Liu, Heping Jia, and Chunyi Chen. "Market Status and Development Prospects of Virtual Power Plants." IOP Conference Series: Earth and Environmental Science 603 (December 1, 2020): 012027. http://dx.doi.org/10.1088/1755-1315/603/1/012027.

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Gholami, Khalil, Behnaz Behi, Ali Arefi, and Philip Jennings. "Grid-Forming Virtual Power Plants: Concepts, Technologies and Advantages." Energies 15, no. 23 (November 29, 2022): 9049. http://dx.doi.org/10.3390/en15239049.

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Virtual Power Plants (VPPs) are efficient structures for attracting private investment, increasing the penetration of renewable energy and reducing the cost of electricity for consumers. It is expected that the number of VPPs will increase rapidly as their financial return is attractive to investors. VPPs will provide added value to consumers, to power systems and to electricity markets by contributing to different services such as the energy and load-following services. One of the capabilities that will become critical in the near future, when large power plants are retired, is grid-forming capability. This review paper introduces the concept of grid-forming VPPs along with their corresponding technologies and their advantages for the new generation of power systems with many connected VPPs.

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Candra, Dodiek, Kilian Hartmann, and Michael Nelles. "Economic Optimal Implementation of Virtual Power Plants in the German Power Market." Energies 11, no. 9 (September 7, 2018): 2365. http://dx.doi.org/10.3390/en11092365.

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The burden of excess energy from the high renewable energy sources (RES) share creates a significant reduction of residual load for the future, resulting in reduced market prices. The higher the share of stochastic RES, the more often the price will be 0 €/MWh. The power market needs new methods to solve these problems. The development of virtual power plants (VPPs) is aimed at solving techno-economic problems with an increasing share of RES in the power market. This study analyses a possible implementation of stochastic and deterministic RES in a VPP to generate secured power, which can be implemented in the European Power Exchange (EPEX)/European Energy Exchange (EEX) power market using existing market products. In this study, the optimal economic VPP configuration for an RES-based power plant is investigated and implemented into standard power market products. The results show that the optimal economic VPP configuration for different market products varies, depending on the energy availability and the marginal costs of the VPP components. The size of the VPP components is positively correlated to the components’ share of the energy generated. It was also found that projecting or implementing VPPs in Germany at current market prices (EPEX/EEX prices) is not yet economically feasible for a small share of market products. However, the secured power can be marketed on the SPOT and in the futures market with higher and more stable prices compared with the status quo.

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Zhong, Weilin, Mohammed Ahsan Adib Murad, Muyang Liu, and Federico Milano. "Impact of Virtual Power Plants on Power System Short-Term Transient Response." Electric Power Systems Research 189 (December 2020): 106609. http://dx.doi.org/10.1016/j.epsr.2020.106609.

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Zhang, Wei, Xuemei Wu, Xiao Zhang, Fang Li, Zhenan Xu, Yurong Yan, Hongmin Meng, and Zesan Liu. "Optimal Scheduling Research for Day Ahead Market Transaction of Virtual Power Plant Considering Uncertainty and CVaR." Journal of Physics: Conference Series 2354, no. 1 (October 1, 2022): 012011. http://dx.doi.org/10.1088/1742-6596/2354/1/012011.

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Abstract Considering the uncertainty of renewable energy generation and the market transaction risk in the day ahead market of virtual power plants, an optimal scheduling model of virtual power plant in the day ahead market was presented. Firstly, this study modeled and analyzed the uncertainty of wind and photovoltaic power generation fluctuations in the virtual power plant. In addition, based on the conditional value at risk theory and the day ahead market clearing rules, the optimal scheduling model of virtual power plants in the day ahead market was established aiming at minimizing the implementation deviation and maximizing the operating income. Finally, the transaction data of a typical region was selected for case study to verify the effectiveness and the feasibility of the optimal scheduling strategy of virtual power plant in day ahead market transaction.

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Han, Shuai, Leping Sun, Xiaoxuan Guo, and Jianbin Lu. "Multi-objective Interval Optimization of Virtual Power Plant Considering the Uncertainty of Source and Load." E3S Web of Conferences 299 (2021): 01011. http://dx.doi.org/10.1051/e3sconf/202129901011.

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As the proportion of electric vehicles and distributed power sources connected to the power grid continues to increase, virtual power plants provide new ideas for effectively solving electric vehicles and distributed power sources connected to the grid. Considering that there are obvious uncertainties in the number of dispatchable electric vehicles and the output of distributed power sources, this paper focuses on the multi-objective interval optimization problem of virtual power plants considering the uncertainty of source load. Based on the analysis of the virtual power plant architecture, aiming at the uncertainty of the source load, a multi-objective interval optimization model of the virtual power plant was established using the interval number theory; in order to verify the validity of the established model, a virtual power plant in a certain area was selected as an example for analysis. The results show that the uncertainty of distributed power sources and electric vehicles can be better avoided in the interval optimization process, and the proposed scheme has strong robustness.

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Zhong, Weilin, Junru Chen, Muyang Liu, Mohammed Ahsan Adib Murad, and Federico Milano. "Coordinated Control of Virtual Power Plants to Improve Power System Short-Term Dynamics." Energies 14, no. 4 (February 23, 2021): 1182. http://dx.doi.org/10.3390/en14041182.

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The paper proposes a coordinated frequency control strategy for Virtual Power Plant (VPPs), with the inclusion of Distributed Energy Resource (DERs), e.g., Solar Photo-Voltaic Generation (SPVG), Wind Generator (WG) as well as Energy Storage System (ESS). The objective is to improve the short-term dynamic response of the overall power system. The robustness of the proposed control is evaluated through a Monte Carlo analysis and a detailed modeling of stochastic disturbances of loads, wind speed, and solar irradiance. The impact of communication delays of a variety of realistic communication networks with different bandwidths is also discussed and evaluated. The case study is based on a modified version of the WSCC 9-bus test system with inclusion of a VPP. This is modeled as a distribution network with inclusion of a variety of DERs.

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Moutis, Panayiotis, and Nikos D. Hatziargyriou. "Decision trees aided scheduling for firm power capacity provision by virtual power plants." International Journal of Electrical Power & Energy Systems 63 (December 2014): 730–39. http://dx.doi.org/10.1016/j.ijepes.2014.06.038.

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Lei, Shaofeng, Zheng Liu, Qingliang Wang, Shengbin Wang, Dunnan Liu, Min Yan, and Yaxuan Han. "Research on green development framework of the virtual power plants." IOP Conference Series: Earth and Environmental Science 687, no. 1 (March 1, 2021): 012201. http://dx.doi.org/10.1088/1755-1315/687/1/012201.

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Guangwei Yan, Ruihua Wang, and Miao Li. "Virtual Inspection System of Nuclear Power Plants with Nuclear Radiation." International Journal of Digital Content Technology and its Applications 6, no. 10 (June 30, 2012): 385–93. http://dx.doi.org/10.4156/jdcta.vol6.issue10.45.

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Gough, Matthew, Sergio F. Santos, Artur Almeida, Mohamed Lotfi, Mohammad S. Javadi, Desta Z. Fitiwi, Gerardo J. Osorio, Rui Castro, and Joao P. S. Catalao. "Blockchain-Based Transactive Energy Framework for Connected Virtual Power Plants." IEEE Transactions on Industry Applications 58, no. 1 (January 2022): 986–95. http://dx.doi.org/10.1109/tia.2021.3131537.

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Feng, Cheng, Yi Wang, Xuanyuan Wang, and Qixin Chen. "Device Access Optimization for Virtual Power Plants in Heterogeneous Networks." IEEE Transactions on Smart Grid 13, no. 2 (March 2022): 1478–89. http://dx.doi.org/10.1109/tsg.2021.3125042.

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Wang, Xuanyuan, Jianlei Shi, Hao Zhang, Zhen Liu, Dunnan Liu, and Hua Li. "Comprehensive evaluation method for energy efficiency of virtual power plants." IOP Conference Series: Earth and Environmental Science 267 (June 8, 2019): 042149. http://dx.doi.org/10.1088/1755-1315/267/4/042149.

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Xu, Helin, Lin Cheng, Ning Qi, and Xuyan Zhou. "Peak shaving potential analysis of distributed load virtual power plants." Energy Reports 6 (December 2020): 515–25. http://dx.doi.org/10.1016/j.egyr.2020.11.204.

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Ko, Rakkyung, and Sung-Kwan Joo. "Stochastic Mixed-Integer Programming (SMIP)-Based Distributed Energy Resource Allocation Method for Virtual Power Plants." Energies 13, no. 1 (December 21, 2019): 67. http://dx.doi.org/10.3390/en13010067.

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Virtual power plants (VPPs) have been widely researched to handle the unpredictability and variable nature of renewable energy sources. The distributed energy resources are aggregated to form into a virtual power plant and operate as a single generator from the perspective of a system operator. Power system operators often utilize the incentives to operate virtual power plants in desired ways. To maximize the revenue of virtual power plant operators, including its incentives, an optimal portfolio needs to be identified, because each renewable energy source has a different generation pattern. This study proposes a stochastic mixed-integer programming based distributed energy resource allocation method. The proposed method attempts to maximize the revenue of VPP operators considering market incentives. Furthermore, the uncertainty in the generation pattern of renewable energy sources is considered by the stochastic approach. Numerical results show the effectiveness of the proposed method.

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Adabi, M. Ebrahim, and Bogdan Marinescu. "Direct Participation of Dynamic Virtual Power Plants in Secondary Frequency Control." Energies 15, no. 8 (April 10, 2022): 2775. http://dx.doi.org/10.3390/en15082775.

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This paper proposes a novel control strategy in which Renewable Energy Sources (RES) considered in a new Dynamic Virtual Power Plant (DVPP) concept directly participate to Secondary Frequency Control (SFC). This allows full participation of these generators to SFC, i.e., in the same manner as classic synchronous generators by fulfilling identical specifications from both control and contractual points of view. An internal real-time redispatch has been proposed to account in DVPP in order to determine the amount of active power injection by each RES unit for the provision of frequency support at the secondary level. The whole control scheme is designed to take into account both rapid and slow dynamics of modern power systems which contain both classic synchronous generators and rapid power electronics for renewable energy sources in which DVPP is supposed to be inserted. The performance of secondary frequency control strategy has been validated through simulation studies on a two-area benchmark with mixed wind power plants and classic synchronous generators. This work is part of the H2020 POSYTYF project

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Alhelou, Hassan Haes, Pierluigi Siano, Massimo Tipaldi, Raffaele Iervolino, and Feras Mahfoud. "Primary Frequency Response Improvement in Interconnected Power Systems Using Electric Vehicle Virtual Power Plants." World Electric Vehicle Journal 11, no. 2 (May 16, 2020): 40. http://dx.doi.org/10.3390/wevj11020040.

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The smart grid concept enables demand-side management, including electric vehicles (EVs). Thus way, some ancillary services can be provided in order to improve the power system stability, reliability, and security. The high penetration level of renewable energy resources causes some problems to independent system operators, such as lack of primary reserve and active power balance problems. Nowadays, many countries are encouraging the use of EVs which provide a good chance to utilize them as a virtual power plant (VPP) in order to contribute to frequency event. This paper proposes a new control method to use EV as VPP for providing primary reserve in smart grids. The primary frequency reserve helps the power system operator to intercept the frequency decline and to improve the frequency response of the whole system. The proposed method calculates the electric vehicles’ primary reserve based on EVs’ information, such as the state of charge (SOC), the arriving time and the vehicle’s departure time. The effectiveness of the proposed scheme is verified by several simulation scenarios on a real-world modern power system with different generating units, such as conventional power plants, renewable energy resources, and electric vehicles.

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Nezamabadi, Hossein, and Mehrdad Setayesh Nazar. "Arbitrage strategy of virtual power plants in energy, spinning reserve and reactive power markets." IET Generation, Transmission & Distribution 10, no. 3 (February 18, 2016): 750–63. http://dx.doi.org/10.1049/iet-gtd.2015.0402.

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Subramanya, Rakshith, Matti Yli-Ojanperä, Seppo Sierla, Taneli Hölttä, Jori Valtakari, and Valeriy Vyatkin. "A Virtual Power Plant Solution for Aggregating Photovoltaic Systems and Other Distributed Energy Resources for Northern European Primary Frequency Reserves." Energies 14, no. 5 (February 24, 2021): 1242. http://dx.doi.org/10.3390/en14051242.

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Primary frequency reserves in Northern Europe have traditionally been provided with hydro plants and fossil fuel-burning spinning reserves. Recently, smart distributed energy resources have been equipped with functionality needed to participate on frequency reserves. Key categories of such resources include photovoltaic systems, batteries, and smart loads. Most of these resources are small and cannot provide the minimum controllable power required to participate on frequency reserves. Thus, virtual power plants have been used to aggregate the resources and trade them on the frequency reserves markets. The information technology aspects of virtual power plants are proprietary and many of the details have not been made public. The first contribution of this article is to propose a generic data model and application programming interface for a virtual power plant with the above-mentioned capabilities. The second contribution is to use the application programming interface to cope with the unpredictability of the frequency reserve capacity that the photovoltaic systems and other distributed energy resources are able to provide to the frequency reserves markets in the upcoming bidding period. The contributions are demonstrated with an operational virtual power plant installation at a Northern European shopping center, aggregating photovoltaic Primary Frequency Reserves resources.

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Dong, Jun, Lin Peng Nie, and Hui Juan Huo. "A bi-level optimal scheduling model for virtual power plants and conventional power plants considering environmental constraints and uncertainty." International Journal of Applied Decision Sciences 13, no. 3 (2020): 313. http://dx.doi.org/10.1504/ijads.2020.10030034.

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Dong, Jun, Lin Peng Nie, and Hui Juan Huo. "A bi-level optimal scheduling model for virtual power plants and conventional power plants considering environmental constraints and uncertainty." International Journal of Applied Decision Sciences 13, no. 3 (2020): 313. http://dx.doi.org/10.1504/ijads.2020.108477.

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Yu, Changle, Wenwen Li, Nian Liu, Lin Yang, Su Zhang, and Jia Wan. "Double-layer Optimization Study of Virtual Power Plants with Source-load-storage." Journal of Physics: Conference Series 2401, no. 1 (December 1, 2022): 012056. http://dx.doi.org/10.1088/1742-6596/2401/1/012056.

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Abstract In order to effectively solve the supply-demand imbalance of the grid caused by intermittent new energy penetration and improve the scheduling flexibility of virtual power plants, a two-layer optimization model of virtual power plants with source-load-storage is proposed. The upper layer of the model is designed to reduce the forecast error of wind power output and improve the revenue of the virtual power plant. On the basis of the maximum wind power consumption, distributed energy storage and fuel cells are used to coordinate and compensate for the deviation between the planned and actual output of renewable energy. The active output of the upper layer is transferred to the lower layer. The lower layer of the model is solved by using the improved linear decreasing inertia weight particle swarm algorithm for the output of the gas turbine unit. The analysis results show that the model can absorb the excess new energy generation in the grid, achieve the balance of supply and demand regulation in the grid, and effectively reduce the economic operation cost of the system.

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Xue, Qingshui, Zhen Xue, Haifeng Ma, Yue Sun, and Xuelei Shi. "Design of Virtual Power Plant System Model under Master-Slave Multi-chain." Journal of Physics: Conference Series 2166, no. 1 (January 1, 2022): 012043. http://dx.doi.org/10.1088/1742-6596/2166/1/012043.

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Abstract The emergence and development of new technology provides a new way of thinking for solving the problems in the traditional energy industry. Introducing block chain technology into virtual power plant can solve the problems existing in virtual power plant such as. to improve the safety, reliability and operation efficiency of virtual power plant. At present, the research on the application of block chain technology in virtual power plants is mostly based on single-chain structure, which makes the system not extensible. Based on this problem, a virtual power plant model with main and multi-chain structure is presented, which improves the scalability of virtual power plant with block chain technology. The use of block chain technology improves the security and fairness of power transactions. It can allocate power more efficiently to improve energy utilization.

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Wei, Hei, and Rasyidah Mohamed Idris. "Optimal Operation Model for Virtual Power Plant in Datong Area." Applied Mechanics and Materials 785 (August 2015): 627–31. http://dx.doi.org/10.4028/www.scientific.net/amm.785.627.

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Datong area has abundant wind energy. Due to problem in large scale of wind power grid connection, this paper introduces virtual power plant concept. As for beginning, power source characteristics of the wind farm, pumped storage power station and the thermal power plant are taken for analysis. Three types of different power plants are chosen to represent the virtual power plant modeling as well as adopting the NSGA2 optimization. As a conclusion, this case study proved that virtual power plant can increase the benefits of each power plant and the wind power plant output power curve become smoother.

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Journal articles on the topic 'Virtual Power Plants'

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