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Artykuły w czasopismach na temat „Electricity network peak demands”

Autor: Grafiati

Data publikacji: 20 grudnia 2024

Data aktualizacji: 31 lipca 2025

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1

Marwan, Marwan, and Pirman Pirman. "Mitigating Electricity a Price Spike under Pre-Cooling Method." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 3 (2016): 1281. http://dx.doi.org/10.11591/ijece.v6i3.9597.

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The growing demand for air-conditioning is one of the largest contributors to Australia overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop a consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The proposed model allows consumers to independently and proactively manage air conditioning peak electricity demand. The main contribution of this research is how to show consumers can mitigate peak demands by opti

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Marwan, Marwan, and Pirman Pirman. "Mitigating Electricity a Price Spike under Pre-Cooling Method." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 3 (2016): 1281. http://dx.doi.org/10.11591/ijece.v6i3.pp1281-1293.

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The growing demand for air-conditioning is one of the largest contributors to Australia overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop a consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The proposed model allows consumers to independently and proactively manage air conditioning peak electricity demand. The main contribution of this research is how to show consumers can mitigate peak demands by opti

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3

Rokamwar, Kaustubh. "Feed- Forward Neural Network based Day Ahead Nodal Pricing." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (2021): 1029–33. http://dx.doi.org/10.22214/ijraset.2021.36352.

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An electricity locational marginal pricing prediction normally recognized by 24-hour day-ahead nodal price forecast. In this paper first collected all physical and technical data i.e. availability of generation and their cost characteristics, real and reactive demands at various buses, transmission capacity availability at various conditions like peak and off-peak conditions. All these input data are used as input for computation of optimal power flow. The nodal prices are calculated with AC-DC optimal power flow methodology for IEEE 30 bus system. The resulted optimal real electricity bus vol

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4

Kim, Hyunsoo, Jiseok Jeong, and Changwan Kim. "Daily Peak-Electricity-Demand Forecasting Based on Residual Long Short-Term Network." Mathematics 10, no. 23 (2022): 4486. http://dx.doi.org/10.3390/math10234486.

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Forecasting the electricity demand of buildings is a key step in preventing a high concentration of electricity demand and optimizing the operation of national power systems. Recently, the overall performance of electricity-demand forecasting has been improved through the application of long short-term memory (LSTM) networks, which are well-suited to processing time-series data. However, previous studies have focused on improving the accuracy in forecasting only overall electricity demand, but not peak demand. Therefore, this study proposes adding residual learning to the LSTM approach to impr

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Ifaei, P., J. K. Park, T. Y. Woo, C. H. Jeong, and C. K. Yoo. "Leveraging media for demand control in an optimal network of renewable microgrids with hydrogen facilities in South Korea." IOP Conference Series: Earth and Environmental Science 1372, no. 1 (2024): 012005. http://dx.doi.org/10.1088/1755-1315/1372/1/012005.

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Abstract In pursuit of a sustainable 2030 strategy in the Republic of Korea, this study addresses the oversight in recent optimal renewable energy microgrid designs, which, despite encompassing all feasible renewable sources, neglected the pivotal role of hydrogen as an energy carrier. This research explores the feasibility of reprogramming media platforms to dynamically shape energy consumption during peak intervals. It further proposes the retrofitting of microgrids with industrial hydrogen production and storage facilities, aligning with controlled electricity demand. A comprehensive social

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Gupta, Rajat, and Sahar Zahiri. "Examining daily electricity demand and indoor temperature profiles in UK social housing flats retrofitted with heat pumps." IOP Conference Series: Earth and Environmental Science 1363, no. 1 (2024): 012093. http://dx.doi.org/10.1088/1755-1315/1363/1/012093.

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Abstract The UK Government has announced decarbonisation of domestic heating thorough low carbon heat pumps. This will result in the deployment of 5 million heat pumps by 2030, and over 25 million by 2050, thereby increasing seasonal and daily peak electricity demand and putting a strain on local electricity networks. Despite this, there is limited evidence on the impact of heat pump operation on daily electricity demand profiles. This paper empirically examines the impact of retrofitted ground source heat pump (GSHP) on daily electricity demand of six social housing flats co-located in a soci

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Nafkha, Rafik, Tomasz Ząbkowski, and Krzysztof Gajowniczek. "Deep Learning-Based Approaches to Optimize the Electricity Contract Capacity Problem for Commercial Customers." Energies 14, no. 8 (2021): 2181. http://dx.doi.org/10.3390/en14082181.

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The electricity tariffs available to customers in Poland depend on the connection voltage level and contracted capacity, which reflect the customer demand profile. Therefore, before connecting to the power grid, each consumer declares the demand for maximum power. This amount, referred to as the contracted capacity, is used by the electricity provider to assign the proper connection type to the power grid, including the size of the security breaker. Maximum power is also the basis for calculating fixed charges for electricity consumption, which is controlled and metered through peak meters. If

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Dejvises, Jackravut. "Energy Storage System Sizing for Peak Shaving in Thailand." ECTI Transactions on Electrical Engineering, Electronics, and Communications 14, no. 1 (2015): 49–55. http://dx.doi.org/10.37936/ecti-eec.2016141.171094.

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This paper presents a mathematical model of energy storage systems (ESSs) to minimise daily electrical peak power demand in Thailand. A daily electrical load curve on a peak day obtained from Electricity Generating Authority of Thailand (EGAT) is used to analyse the capability of energy storage system for electrical peak power demand reduction with different ESS sizes. It is found that with power rate of 50 percent of the difference between the minimum and the maximum demands of the daily load curve and with energy capacity of 50 percent of the sum of each time step absolute energy difference

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Sasi Bhushan, M. A., M. Sudhakaran, Sattianadan Dasarathan, and Mariappane E. "Integration of a Heterogeneous Battery Energy Storage System into the Puducherry Smart Grid with Time-Varying Loads." Energies 18, no. 2 (2025): 428. https://doi.org/10.3390/en18020428.

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A peak shaving approach in selected industrial loads helps minimize power usage during high demand hours, decreasing total energy expenses while improving grid stability. A battery energy storage system (BESS) can reduce peak electricity demand in distribution networks. Quasi-dynamic load flow analysis (QLFA) accurately assesses the maximum loading conditions in distribution networks by considering factors such as load profiles, system topology, and network constraints. Achieving maximum peak shaving requires optimizing battery charging and discharging cycles based on real-time energy generati

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Kauko, Hanne, Daniel Rohde, and Armin Hafner. "Local Heating Networks with Waste Heat Utilization: Low or Medium Temperature Supply?" Energies 13, no. 4 (2020): 954. http://dx.doi.org/10.3390/en13040954.

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District heating enables an economical use of energy sources that would otherwise be wasted to cover the heating demands of buildings in urban areas. For efficient utilization of local waste heat and renewable heat sources, low distribution temperatures are of crucial importance. This study evaluates a local heating network being planned for a new building area in Trondheim, Norway, with waste heat available from a nearby ice skating rink. Two alternative supply temperature levels have been evaluated with dynamic simulations: low temperature (40 °C), with direct utilization of waste heat and d

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Gutiérrez-Villegas, Juan Carlos, Set Vejar Ruíz, and Agustín Escamilla Martínez. "PV system interconnected to the electricity grid with hourly control of energy injection." DYNA 88, no. 217 (2021): 84–90. http://dx.doi.org/10.15446/dyna.v88n217.88789.

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Implementing Photovoltaic Systems (SFV) Interconnected to the electrical network, the energy consumption of the network is reduced, thus the SVF is a good alternative in rates where the charge is solely for energy consumption. In this work is presented the analysis of the Great Demand rate in Medium Hourly Voltage (GDMTH) that will allow designing SFV interconnected to the network helping to reduce the maximum demand for peak hours and increase the impact of the generation of energy through the PV system at rates where hourly consumption is considered. The consumption of energy by the user is

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12

Amin, Adil, Wajahat Ullah Khan Tareen, Muhammad Usman, et al. "A Review of Optimal Charging Strategy for Electric Vehicles under Dynamic Pricing Schemes in the Distribution Charging Network." Sustainability 12, no. 23 (2020): 10160. http://dx.doi.org/10.3390/su122310160.

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This study summarizes a critical review on EVs’ optimal charging and scheduling under dynamic pricing schemes. A detailed comparison of these schemes, namely, Real Time Pricing (RTP), Time of Use (ToU), Critical Peak Pricing (CPP), and Peak Time Rebates (PTR), is presented. Globally, the intention is to reduce the carbon emissions (CO2) has motivated the extensive practice of Electric Vehicles (EVs). The uncoordinated charging and uncontrolled integration however of EVs to the distribution network deteriorates the system performance in terms of power quality issues. Therefore, the EVs’ chargin

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Cahyo, Mukti Dwi, Sri Heranurweni, and Harmini Harmini. "PREDIKSI BEBAN ENERGI LISTRIK APJ KOTA SEMARANG MENGGUNAKAN METODE RADIAL BASIS FUNCTION (RBF)." Elektrika 11, no. 2 (2019): 21. http://dx.doi.org/10.26623/elektrika.v11i2.1699.

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Electric power is one of the main needs of society today, ranging from household consumers to industry. The demand for electricity increases every year. So as to achieve adjustments between power generation and power demand, the electricity provider (PLN) must know the load needs or electricity demand for some time to come. There are many studies on the prediction of electricity loads in electricity, but they are not specific to each consumer sector. One of the predictions of this electrical load can be done using the Radial Basis Function Artificial Neural Network (ANN) method. This method us

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14

Muhammad Ahsan Niazi, Syed Abid Ali Shah Bukhari, Vikram Kumar, Khalil Muhammad Zuhaib, and Usama Aslam. "Optimal Scheduling of Electric Vehicle Aggregators in Residential Areas: A Cost Minimization Approach." Sukkur IBA Journal of Emerging Technologies 8, no. 1 (2025): 62–69. https://doi.org/10.30537/sjet.v8i1.1602.

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This study presents an optimization method for scheduling electric vehicle (EV) charging in residential areas, aimed at minimizing costs associated with peak demand periods. As the adoption of EVs increases, effective management of their charging demands becomes crucial for both utilities and EV owners. This research develops a mathematical model for a combined EV aggregator that coordinates charging and discharging activities among residential, commercial, and industrial users. Using a Multi-Agent Charging and Discharging (MACD) algorithm, the study shifts EV charging from peak to off-peak ho

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15

Sattar, Mahroo, Mahmoud Samiei Moghaddam, Azita Azarfar, Nasrin Salehi, and Mojtaba Vahedi. "Co-optimization of integrated energy systems in the presence of renewable energy, electric vehicles, power-to-gas systems and energy storage systems with demand-side management." Clean Energy 7, no. 2 (2023): 426–35. http://dx.doi.org/10.1093/ce/zkad011.

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Abstract With the widespread penetration of renewable energy sources and energy storage systems, the problem of energy management has received increasing attention. One of the systems that network owners consider today is the power-to-gas (P2G) system. This system causes surplus electricity generated from renewable energy resources or batteries in the network to be converted into gas and sold to the gas network. Two reasons for the existence of gas distributed generation resources and P2G systems cause the two power and gas networks to interact. Energy management and profit making considering

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16

Zhao, Mengchen, Santiago Gomez-Rosero, Hooman Nouraei, Craig Zych, Miriam A. M. Capretz, and Ayan Sadhu. "Toward Prediction of Energy Consumption Peaks and Timestamping in Commercial Supermarkets Using Deep Learning." Energies 17, no. 7 (2024): 1672. http://dx.doi.org/10.3390/en17071672.

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Building energy consumption takes up over 30% of global final energy use and 26% of global energy-related emissions. In addition, building operations represent nearly 55% of global electricity consumption. The management of peak demand plays a crucial role in optimizing building electricity usage, consequently leading to a reduction in carbon footprint. Accurately forecasting peak demand in commercial buildings provides benefits to both the suppliers and consumers by enhancing efficiency in electricity production and minimizing energy waste. Precise predictions of energy peaks enable the imple

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17

Mohammad, Mirzaei Talabari. "Optimization of grid-connected MicroGrid demand considering demand response." National Security and Strategic Planning 2024, no. 1 (2024): 60–65. http://dx.doi.org/10.37468/2307-1400-2024-1-60-65.

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Electricity grid is a product of urbanization expansion and rapid development of various infrastructures worldwide and over the past centuries. Although power companies are located in diverse regions, they typically use the same technologies to generate and distribute electricity. Proper implementation of the demand response (DR) program should be provided with some equipment to make subscribers aware of electricity price at any time and accordingly provide a proper response to the grid to reduce costs. This, in turn, reduces demand during peak hours. The intelligent grid, using the two-way co

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Sara Alimammadova, Sara Alimammadova. "ANALYSIS REDUCTION OF ENERGY LOSSES IN DISTRIBUTION NETWORKS." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 38, no. 03 (2024): 297–305. http://dx.doi.org/10.36962/pahtei38032024-297.

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The article analyzes the reduction of energy losses in distribution networks, which is a serious problem requiring an integrated approach, including technological, regulatory, and behavioral interventions. Some measures that can be developed and implemented to solve this problem are given, such as infrastructure modernization, taking into account investments in the modernization of distribution infrastructure, affecting a significant reduction in energy loss, and the introduction of load management strategies that optimize energy distribution and reduce losses. This includes measures such as l

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19

Deng, Minghui, Jie Zhao, Wentao Huang, Bo Wang, Xintai Liu, and Zejun Ou. "Optimal Layout Planning of Electric Vehicle Charging Stations Considering Road–Electricity Coupling Effects." Electronics 14, no. 1 (2024): 135. https://doi.org/10.3390/electronics14010135.

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With the advancement of dual-carbon goals and the construction of new types of power systems, the proportion of electric vehicle charging stations (EVCSs) in the coupling system of power distribution and transportation networks is gradually increasing. However, the surge in charging demand not only causes voltage fluctuations and a decline in power quality but also leads to tension in the power grid load in some areas. The complexity of urban road networks further increases the challenge of charging station planning. Although laying out charging stations in areas with high traffic flow can bet

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Rouhani, Anise, Habib Rajabi Mashhadi, and Mehdi Feizi. "Estimating the Short-term Price Elasticity of Residential Electricity Demand in Iran." International Transactions on Electrical Energy Systems 2022 (August 13, 2022): 1–8. http://dx.doi.org/10.1155/2022/4233407.

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Excessive electricity consumption causes severe problems in the electricity sector and consequently in load curtailment. This paper estimates the short-term price elasticity of electricity demand for the Iranian household sector by monthly panel dataset. The estimated short-term price elasticity of electricity demand was −0.048. We use abrupt change in electricity price due to targeting subsidy on December 18th, 2010. The results show significant heterogeneity in electricity price elasticity between the various levels of consumption. Due to the heterogeneity of consumers’ electricity price ela

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Byk, Felix, Yuri Kakosha, and Lyudmila Myshkina. "Distributed power generation and power supply reliability improvement." E3S Web of Conferences 216 (2020): 01013. http://dx.doi.org/10.1051/e3sconf/202021601013.

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The appearance of distributed generation in the power supply systems of industrial enterprises leads to the emergence of requirements for networks to increase their redundancy functions. The introduction of network redundancy fees will lead to an increase in electricity supply costs for such enterprises. The source of additional revenue may be the provision of regulatory resources to the aggregator of electricity demand management in the UES of Russia. But this requires changes that allow active consumers to supply the distribution network with excess capacity during peak hours in the UES of R

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Arabi, Marzieh Sadat, and Anjali Awasthi. "A PSO-Based Approach for the Optimal Allocation of Electric Vehicle Parking Lots to the Electricity Distribution Network." Algorithms 18, no. 3 (2025): 175. https://doi.org/10.3390/a18030175.

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Electric vehicles can serve as controllable loads, storing energy during off-peak periods and acting as generation units during peak periods or periods with high electricity prices. They function as distributed generation resources within distribution systems, requiring controlled charging and discharging of batteries. In this paper, we address the problem of the optimal allocation of parking lots within a distribution system to efficiently supply electric vehicle loads. The goal is to determine the best capacity and size of parking lots to meet peak hour demands while considering constraints

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Tan, Yetuo, Yongming Zhi, Zhengbin Luo, Honggang Fan, Jun Wan, and Tao Zhang. "Optimal Scheduling of Virtual Power Plant with Flexibility Margin Considering Demand Response and Uncertainties." Energies 16, no. 15 (2023): 5833. http://dx.doi.org/10.3390/en16155833.

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The emission reduction of global greenhouse gases is one of the key steps towards sustainable development. Demand response utilizes the resources of the demand side as an alternative of power supply which is very important for the power network balance, and the virtual power plant (VPP) could overcome barriers to participate in the electricity market. In this paper, the optimal scheduling of a VPP with a flexibility margin considering demand response and uncertainties is proposed. Compared with a conventional power plant, the cost models of VPPs considering the impact of uncertainty and the op

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Hj Osman, Muhamad Suhaimi, Ho Wai Shin, Arfah Diyanah Nizamuddin, Zarina Ab Muis, Wong Keng Yinn, and Tan Huiyi. "Vehicle To Building (V2b) Peak Load Shaving and Tariff Analysis." IOP Conference Series: Earth and Environmental Science 1395, no. 1 (2024): 012019. http://dx.doi.org/10.1088/1755-1315/1395/1/012019.

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Abstract Commercial buildings are essentially important energy consumers for national electricity grid provider as it’s owned by businesses owners that directly keep up the national gross domestic product (GDP). Soaring load demand from commercial buildings usually occurs within few hours on peak business hour. Electricity grid infrastructure designed to support maximum demand of the system but underutilize most of the time outside the peak session. Growing number of EV penetration in local market can serve as mobile energy storage for Vehicle to Building (V2B) energy integration thus enable p

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Ivanov, Ovidiu, Samiran Chattopadhyay, Soumya Banerjee, Bogdan-Constantin Neagu, Gheorghe Grigoras, and Mihai Gavrilas. "A Novel Algorithm with Multiple Consumer Demand Response Priorities in Residential Unbalanced LV Electricity Distribution Networks." Mathematics 8, no. 8 (2020): 1220. http://dx.doi.org/10.3390/math8081220.

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Demand Side Management (DSM) is becoming necessary in residential electricity distribution networks where local electricity trading is implemented. Amongst the DSM tools, Demand Response (DR) is used to engage the consumers in the market by voluntary disconnection of high consumption receptors at peak demand hours. As a part of the transition to Smart Grids, there is a high interest in DR applications for residential consumers connected in intelligent grids which allow remote controlling of receptors by electricity distribution system operators and Home Energy Management Systems (HEMS) at cons

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Valeriya, Azarova, Engel Dominik, Ferner Cornelia, Kollmann Andrea, and Reichl Johannes. "Transition to peak-load-based tariffs can be disruptive for different groups of consumers." Nature Energy 4 (October 11, 2019): 829–30. https://doi.org/10.1038/s41560-019-0479-y.

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New network tariffs designed to recover grid operating costs can introduce up to a 500% increase in charges for some households. A transition from volumetric to peak-load-based tariffs will require targeted policy measures such as clear price signals, information about household electricity consumption and temporary compensation or mitigation mechanisms.

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Ge, Xiaoxue, Zhijie Liu, Kejun Li, Chenxian Guo, Gang Shen, and Zichen Wang. "Economic Scheduling Strategy for Multi-Energy-Integrated Highway Service Centers Considering Carbon Trading and Critical Peak Pricing Mechanism." Symmetry 16, no. 9 (2024): 1110. http://dx.doi.org/10.3390/sym16091110.

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This study proposes an optimized economic scheduling strategy for multi-energy-integrated highway service centers (MEIHSCs) within a 24 h operational timeframe. With the imperative of carbon peaking and carbon neutrality, highway areas are increasingly incorporating renewable energy systems, such as photovoltaic arrays, to capitalize on abundant resources along highways. Considering the diverse load demands of new energy vehicles and the mismatch between energy supply and demand on the highway, MEIHSCs must adapt to these trends by establishing integrated networks for electricity, natural gas,

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Borghini, Eugenio, Cinzia Giannetti, James Flynn, and Grazia Todeschini. "Data-Driven Energy Storage Scheduling to Minimise Peak Demand on Distribution Systems with PV Generation." Energies 14, no. 12 (2021): 3453. http://dx.doi.org/10.3390/en14123453.

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The growing adoption of decentralised renewable energy generation (such as solar photovoltaic panels and wind turbines) and low-carbon technologies will increase the strain experienced by the distribution networks in the near future. In such a scenario, energy storage is becoming a key alternative to traditional expensive reinforcements to network infrastructure, due to its flexibility, decreasing costs and fast deployment capabilities. In this work, an end-to-end data-driven solution to optimally design the control of a battery unit with the aim of reducing the peak electricity demand is pres

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Senchilo, Nikita Dmitrievich, and Denis Anatolievich Ustinov. "Method for Determining the Optimal Capacity of Energy Storage Systems with a Long-Term Forecast of Power Consumption." Energies 14, no. 21 (2021): 7098. http://dx.doi.org/10.3390/en14217098.

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The unevenness of the electricity consumption schedule at enterprises leads to a peak power increase, which leads to an increase in the cost of electricity supply. Energy storage devices can optimize the energy schedule by compensating the planned schedule deviations, as well as reducing consumption from the external network when participating in a demand response. However, during the day, there may be several peaks in consumption, which lead to a complete discharge of the battery to one of the peaks; as a result, total peak power consumption does not decrease. To optimize the operation of sto

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El-Hafez, Omar Jouma, Tarek Y. ElMekkawy, Mohamed Kharbeche, and Ahmed Massoud. "Impact of COVID-19 Pandemic on Qatar Electricity Demand and Load Forecasting: Preparedness of Distribution Networks for Emerging Situations." Sustainability 14, no. 15 (2022): 9316. http://dx.doi.org/10.3390/su14159316.

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The COVID-19 pandemic has brought several global challenges, one of which is meeting the electricity demand. Millions of people are confined to their homes, in each of which a reliable electricity supply is needed, to support teleworking, e-commerce, and electrical appliances such as HVAC, lighting, fridges, water heaters, etc. Furthermore, electricity is also required to operate medical equipment in hospitals and perhaps temporary quarantine hospitals/shelters. Electricity demand forecasting is a crucial input into decision-making for electricity providers. Without an accurate forecast of ele

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Ramsebner, Jasmine, Albert Hiesl, and Reinhard Haas. "Efficient Load Management for BEV Charging Infrastructure in Multi-Apartment Buildings." Energies 13, no. 22 (2020): 5927. http://dx.doi.org/10.3390/en13225927.

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Interest in and demand for battery electric vehicles (BEVs) is growing strongly due to the increasing awareness of climate change and specific decarbonization goals. One of the largest challenges remains the provision of large-scale, efficient charging infrastructure in multi-apartment buildings. Successful load management (LM) for BEV charging directly influences the technical requirements and the economic and environmental aspects of charging infrastructure and can prevent costly distribution grid expansion. The main objective of this paper is to evaluate potential LM approaches in multi-apa

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Bunnoon, Pituk. "Electricity Peak Load Demand using De-noising Wavelet Transform integrated with Neural Network Methods." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (2016): 12. http://dx.doi.org/10.11591/ijece.v6i1.8901.

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One of most important elements in electric power system planning is load forecasts. So, in this paper proposes the load demand forecasts using de-noising wavelet transform (DNWT) integrated with neural network (NN) methods. This research, the case study uses peak load demand of Thailand (Electricity Generating Authority of Thailand: EGAT). The data of demand will be analyzed with many influencing variables for selecting and classifying factors. In the research, the de-noising wavelet transform uses for decomposing the peak load signal into 2 components these are detail and trend components. Th

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Bunnoon, Pituk. "Electricity Peak Load Demand using De-noising Wavelet Transform integrated with Neural Network Methods." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (2016): 12. http://dx.doi.org/10.11591/ijece.v6i1.pp12-20.

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One of most important elements in electric power system planning is load forecasts. So, in this paper proposes the load demand forecasts using de-noising wavelet transform (DNWT) integrated with neural network (NN) methods. This research, the case study uses peak load demand of Thailand (Electricity Generating Authority of Thailand: EGAT). The data of demand will be analyzed with many influencing variables for selecting and classifying factors. In the research, the de-noising wavelet transform uses for decomposing the peak load signal into 2 components these are detail and trend components. Th

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Wang, Dawei, Hanqi Dai, Yuan Jin, Zhuoqun Li, Shanna Luo, and Xuebin Li. "Employing Quantum Entanglement for Real-Time Coordination of Distributed Electric Vehicle Charging Stations: Advancing Grid Efficiency and Stability." Energies 18, no. 11 (2025): 2917. https://doi.org/10.3390/en18112917.

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The widespread deployment of electric vehicles (EVs) has introduced substantial challenges to electricity pricing, grid stability, and renewable energy integration. This paper presents the first real-time quantum-enhanced electricity pricing framework for large-scale EV charging networks, marking a significant departure from existing approaches based on mixed-integer programming (MILP) and deep reinforcement learning (DRL). The proposed framework incorporates renewable intermittency, demand elasticity, and infrastructure constraints within a high-dimensional optimization model. The objective i

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Li, Fei, Bo Gao, Lun Shi, et al. "A Time-Varying Incentive Optimization for Interactive Demand Response Based on Two-Step Clustering." Information 13, no. 9 (2022): 421. http://dx.doi.org/10.3390/info13090421.

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With the increasing marketization of electricity, residential users are gradually participating in various businesses of power utility companies, and there are more and more interactive adjustments between load, source, and grid. However, the participation of large-scale users has also brought challenges to the grid companies in carrying out demand-side dispatching work. The user load response is uneven, and users’ behavioral characteristics are highly differentiated. It is necessary to consider the differences in users’ electricity consumption demand in the design of the peak–valley load time

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Karamanski, Stefan, and Gareth Erfort. "Wind Energy Supply Profiling and Offshore Potential in South Africa." Energies 16, no. 9 (2023): 3668. http://dx.doi.org/10.3390/en16093668.

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South Africa’s energy network is under severe pressure due to low supply and overwhelming demand. With an increase in renewable energy providers, specifically wind energy, knowing how the supply can satisfy the electricity demand may relieve apprehensions. This research aims to provide insight into the wind energy supply of South Africa and question how well this supply meets the demand of South Africa. The methodology used in this work highlights the importance of access to public datasets to dispel misconceptions in the energy industry. Additionally, the work supports network planning and th

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Virupaksha, Vinay, Mary Harty, and Kevin McDonnell. "Microgeneration of Electricity Using a Solar Photovoltaic System in Ireland." Energies 12, no. 23 (2019): 4600. http://dx.doi.org/10.3390/en12234600.

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Microgeneration of electricity using solar photovoltaic (PV) systems is a sustainable form of renewable energy, however uptake in Ireland remains very low. The aim of this study is to assess the potential of the community-based roof top solar PV microgeneration system to supply electricity to the grid, and to explore a crowd funding mechanism for community ownership of microgeneration projects. A modelled microgeneration project was developed: the electricity load profiles of 68 residential units were estimated; a community-based roof top solar PV system was designed; an electricity network mo

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Mazibuko, Thokozile, Katleho Moloi, and Kayode Akindeji. "Techno-Economic Design and Optimization of Hybrid Energy Systems." Energies 17, no. 16 (2024): 4176. http://dx.doi.org/10.3390/en17164176.

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The power generation capacity must be increased to accommodate population growth and address the lack of electricity access in rural areas. Traditional power plants in South Africa are unable to keep up with the growing demand for electricity. By strategically planning and building clusters of renewable energy sources like solar and wind, microgrid operators can provide a sustainable solution that boosts electricity supply while being cost-effective and environmentally friendly. Utilizing renewable energy can help alleviate strain on power plants by reducing peak demand in constrained distribu

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El-Bayeh, Claude Ziad, Ursula Eicker, Khaled Alzaareer, Brahim Brahmi, and Mohamed Zellagui. "A Novel Data-Energy Management Algorithm for Smart Transformers to Optimize the Total Load Demand in Smart Homes." Energies 13, no. 18 (2020): 4984. http://dx.doi.org/10.3390/en13184984.

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The increased integration of Electric Vehicles (EVs) into the distribution network can create severe issues—especially when demand response programs and time-varying electricity prices are applied, EVs tend to charge during the off-peak time to minimize the electricity cost. Hence, another peak demand might be created, and other solutions are required. Many researchers tried to solve the problem; however, limitations exist because of the decentralized topology of the network. The system operator is not allowed to control the end-users’ load due to security and privacy issues. To overcome this

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Mele, Enea, Anastasios Natsis, Aphrodite Ktena, Christos Manasis, and Nicholas Assimakis. "Electromobility and Flexibility Management on a Non-Interconnected Island." Energies 14, no. 5 (2021): 1337. http://dx.doi.org/10.3390/en14051337.

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The increasing penetration of electrical vehicles (EVs), on the way to decarbonizing the transportation sector, presents several challenges and opportunities for the end users, the distribution grid, and the electricity markets. Uncontrollable EV charging may increase peak demand and impact the grid stability and reliability, especially in the case of non-interconnected microgrids such as the distribution grids of small islands. On the other hand, if EVs are considered as flexible loads and distributed storage, they may offer Vehicle to Grid (V2G) services and contribute to demand-side managem

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Akpojedje, F.O., and F.O. Odiase. "Modeling of Demand Side Management Scheme for Matching Electricity Supply with Demand in the Nigerian Power System." Nigerian Research Journal of Engineering and Environmental Sciences 6, no. 2 (2021): 618–25. https://doi.org/10.5281/zenodo.5805205.

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<em>The unserved load in the Nigerian power system currently is as a result of the ever-growing gap between electric energy demand and supply which is one of the major causes of frequent power interruptions. Thus, stabilizing the network, equalization of the available electricity supply with the energy demand becomes necessary, of which demand side management (DSM) is a veritable tool being deployed to match the ever-growing energy demand with the available electricity supply. Consequently, this paper presents a concise overview of demand side management scheme and its modeling for matching el

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Davari, Mohammad Mehdi, Hossein Ameli, Mohammad Taghi Ameli, and Goran Strbac. "Impact of Local Emergency Demand Response Programs on the Operation of Electricity and Gas Systems." Energies 15, no. 6 (2022): 2144. http://dx.doi.org/10.3390/en15062144.

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With increasing attention to climate change, the penetration level of renewable energy sources (RES) in the electricity network is increasing. Due to the intermittency of RES, gas-fired power plants could play a significant role in backing up the RES in order to maintain the supply–demand balance. As a result, the interaction between gas and power networks are significantly increasing. On the other hand, due to the increase in peak demand (e.g., electrification of heat), network operators are willing to execute demand response programs (DRPs) to improve congestion management and reduce costs.

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Singh, Manish Kumar, K. S. Verma, Bindeshwar Singh, Prem Narayan Verma, Nitish Kumar Rai, and Jahnavi Jahnavi. "Impact of Widespread Electric Vehicle Penetration on Distribution Network Infrastructure: A Comprehensive Analysis." International Energy Journal 25, no. 1B (2025): 237. https://doi.org/10.64289/iej.25.01b05.4544476.

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The acceptance of electric vehicles, or EVs, is soaring, which offers opportunities and problems for the architecture of current distribution networks. With more people driving electric cars, there will likely be a large increase in the power demand, which might put unprecedented strain on the distribution network. The effects of widespread EV integration on distribution network architecture are thoroughly examined in this paper. Electricity distribution networks face opportunities and obstacles as the number of electric vehicles (EVs) increases. The increased use of EVs is predicted to increa

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Saboori, Hedayat, Shahram Jadid, and Mehdi Savaghebi. "Optimal Management of Mobile Battery Energy Storage as a Self-Driving, Self-Powered and Movable Charging Station to Promote Electric Vehicle Adoption." Energies 14, no. 3 (2021): 736. http://dx.doi.org/10.3390/en14030736.

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The high share of electric vehicles (EVs) in the transportation sector is one of the main pillars of sustainable development. Availability of a suitable charging infrastructure and an affordable electricity cost for battery charging are the main factors affecting the increased adoption of EVs. The installation location of fixed charging stations (FCSs) may not be completely compatible with the changing pattern of EV accumulation. Besides, their power withdrawal location in the network is fixed, and also, the time of receiving the power follows the EVs’ charging demand. The EV charging demand p

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Koch, Katharina, Bastian Alt, and Matthias Gaderer. "Dynamic Modeling of a Decarbonized District Heating System with CHP Plants in Electricity-Based Mode of Operation." Energies 13, no. 16 (2020): 4134. http://dx.doi.org/10.3390/en13164134.

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The targets of global CO2 reduction outline the importance of decarbonizing the heating and cooling sector, which consume half of the final energy in the European Union (EU). Consequently, heating network operators must adapt to growing requirements for carbon neutrality. Energy system modeling allows the simulation of individual network compositions and regulations, while considering electricity market signals for a more efficient plant operation. The district heating model, programmed for this work, covers a measured heat demand with peak load boiler, biomass-fired combined heat and power (C

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Tiwari, Amit, Adarsh Dhar Dubey, and Devesh Patel. "Comparative Study of Short Term Load Forecasting Using Multilayer Feed Forward Neural Network With Back Propagation Learning and Radial Basis Functional Neural Network." SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology 7, no. 01 (2015): 09–18. http://dx.doi.org/10.18090/samriddhi.v7i1.3307.

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The term load forecast refers to the projected load requirement using systematic process of defining load in sufficient quantitative detail so that important power system expansion decisions can be made. Load forecasting is necessary for economic generation of power, economic allocation between plants (unit commitment scheduling), maintenance scheduling and for system security such as peak load shaving by power interchange with interconnected utilities. With structural changes to electricity in recent years, there is an emphasis on Short Term Load Forecasting (STLF).STLF is the essential part

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Town, Graham, Seyedfoad Taghizadeh, and Sara Deilami. "Review of Fast Charging for Electrified Transport: Demand, Technology, Systems, and Planning." Energies 15, no. 4 (2022): 1276. http://dx.doi.org/10.3390/en15041276.

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As the number and range of electric vehicles in use increases, and the size of batteries in those vehicles increases, the demand for fast and ultra-fast charging infrastructure is also expected to increase. The growth in the fast charging infrastructure raises a number of challenges to be addressed; primarily, high peak loads and their impacts on the electricity network. This paper reviews fast and ultra-fast charging technology and systems from a number of perspectives, including the following: current and expected trends in fast charging demand; the particular temporal and spatial characteri

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Valinejad, Jaber, Taghi Barforoshi, Mousa Marzband, Edris Pouresmaeil, Radu Godina, and João P. S. Catalão. "Investment Incentives in Competitive Electricity Markets." Applied Sciences 8, no. 10 (2018): 1978. http://dx.doi.org/10.3390/app8101978.

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This paper presents the analysis of a novel framework of study and the impact of different market design criterion for the generation expansion planning (GEP) in competitive electricity market incentives, under variable uncertainties in a single year horizon. As investment incentives conventionally consist of firm contracts and capacity payments, in this study, the electricity generation investment problem is considered from a strategic generation company (GENCO) ′ s perspective, modelled as a bi-level optimization method. The first-level includes decision steps related to investment incentive

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Wan, Zhengdong, Yan Huang, Liangzheng Wu, and Chengwei Liu. "ADPA Optimization for Real-Time Energy Management Using Deep Learning." Energies 17, no. 19 (2024): 4821. http://dx.doi.org/10.3390/en17194821.

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The current generation of renewable energy remains insufficient to meet the demands of users within the network, leading to the necessity of curtailing flexible loads and underscoring the urgent need for optimized microgrid energy management. In this study, the deep learning-based Adaptive Dynamic Programming Algorithm (ADPA) was introduced to integrate real-time pricing into the optimization of demand-side energy management for microgrids. This approach not only achieved a dynamic balance between supply and demand, along with peak shaving and valley filling, but it also enhanced the rationali

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Chen, Wen, Chun Lin Guo, Zong Feng Li, et al. "Research of Time-of-Use Tariff Considering Electric Vehicles Charging Demands." Advanced Materials Research 953-954 (June 2014): 1354–58. http://dx.doi.org/10.4028/www.scientific.net/amr.953-954.1354.

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With the large-scale EV(electric vehicle) integrating into the power system, new challenges has been brought to the planning as well as the security of the network. There will be a great impact on the system if the system operator ignores the vast quantity of EV charging at the same. Thus, taking measures, e.g. the multiple tariff, is of vital importance to give the guidance to the EV owners to charging wisely to save the daily cost on charging, as well as reduce the gap between peak load and valley load. A model for TOU has been presented in this paper. In the model , an objective function is

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