Mingyuan Chen, Le Qi, Peizheng Xuan, Yanjie Liang, Youhui Yang, Qi Zou, Lanfen Cheng, Chaoyi Peng, Huayuan Li
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This paper summarizes the key issues that need to be addressed for energy storage to participate in the spot market from two aspects: the power bidding model does not meet the requirements of the physical and cost-operational characteristics of energy storage, and the real-time market under this model cannot achieve optimal allocation of energy storage. Considering the energy constraints and cost characteristics of energy storage, a charge and discharge bidding model is proposed, which is based on the stored energy value of energy storage and is in line with the physical and cost-operational characteristics and real-time optimization needs of energy storage. Subsequently, a market clearing model for energy storage participation in the spot market under the state of energy bidding method is constructed, and based on the IEEE 39-bus test case, a comparative analysis of the nodal electricity prices, energy storage revenue, and total system costs under the proposed market participation model and the traditional power bidding model is conducted. Simulation results show that the proposed energy storage participation model in the spot market can better utilize the value of energy storage in peak shaving and valley filling compared to the conventional power bidding model, reducing the extreme electricity prices by up to 10%, increasing single cycle revenue of energy storage by 46%, and reducing the total operating costs of the system in scenarios with significant deviations in system load in the day-ahead and real-time markets.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on the participation model of energy storage in electricity spot markets considering energy constraints and cost characteristics\",\"authors\":\"Mingyuan Chen, Le Qi, Peizheng Xuan, Yanjie Liang, Youhui Yang, Qi Zou, Lanfen Cheng, Chaoyi Peng, Huayuan Li\",\"doi\":\"10.1063/5.0194872\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the context of power systems with a high proportion of renewable energy, energy storage plays a significant role in facilitating the consumption of renewable energy and ensuring the operational safety of power systems. 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Considering the energy constraints and cost characteristics of energy storage, a charge and discharge bidding model is proposed, which is based on the stored energy value of energy storage and is in line with the physical and cost-operational characteristics and real-time optimization needs of energy storage. Subsequently, a market clearing model for energy storage participation in the spot market under the state of energy bidding method is constructed, and based on the IEEE 39-bus test case, a comparative analysis of the nodal electricity prices, energy storage revenue, and total system costs under the proposed market participation model and the traditional power bidding model is conducted. 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Research on the participation model of energy storage in electricity spot markets considering energy constraints and cost characteristics
In the context of power systems with a high proportion of renewable energy, energy storage plays a significant role in facilitating the consumption of renewable energy and ensuring the operational safety of power systems. However, the current power spot market's predominant power bidding model does not fully consider the physical and cost-operational characteristics of energy storage, which is not conducive to further incentivizing investment and construction of energy storage, and may indirectly affect the flexibility of energy storage in peak shaving and valley filling. This paper summarizes the key issues that need to be addressed for energy storage to participate in the spot market from two aspects: the power bidding model does not meet the requirements of the physical and cost-operational characteristics of energy storage, and the real-time market under this model cannot achieve optimal allocation of energy storage. Considering the energy constraints and cost characteristics of energy storage, a charge and discharge bidding model is proposed, which is based on the stored energy value of energy storage and is in line with the physical and cost-operational characteristics and real-time optimization needs of energy storage. Subsequently, a market clearing model for energy storage participation in the spot market under the state of energy bidding method is constructed, and based on the IEEE 39-bus test case, a comparative analysis of the nodal electricity prices, energy storage revenue, and total system costs under the proposed market participation model and the traditional power bidding model is conducted. Simulation results show that the proposed energy storage participation model in the spot market can better utilize the value of energy storage in peak shaving and valley filling compared to the conventional power bidding model, reducing the extreme electricity prices by up to 10%, increasing single cycle revenue of energy storage by 46%, and reducing the total operating costs of the system in scenarios with significant deviations in system load in the day-ahead and real-time markets.
期刊介绍：
The Journal of Renewable and Sustainable Energy (JRSE) is an interdisciplinary, peer-reviewed journal covering all areas of renewable and sustainable energy relevant to the physical science and engineering communities. The interdisciplinary approach of the publication ensures that the editors draw from researchers worldwide in a diverse range of fields.
Topics covered include:
Renewable energy economics and policy
Renewable energy resource assessment
Solar energy: photovoltaics, solar thermal energy, solar energy for fuels
Wind energy: wind farms, rotors and blades, on- and offshore wind conditions, aerodynamics, fluid dynamics
Bioenergy: biofuels, biomass conversion, artificial photosynthesis
Distributed energy generation: rooftop PV, distributed fuel cells, distributed wind, micro-hydrogen power generation
Power distribution & systems modeling: power electronics and controls, smart grid
Energy efficient buildings: smart windows, PV, wind, power management
Energy conversion: flexoelectric, piezoelectric, thermoelectric, other technologies
Energy storage: batteries, supercapacitors, hydrogen storage, other fuels
Fuel cells: proton exchange membrane cells, solid oxide cells, hybrid fuel cells, other
Marine and hydroelectric energy: dams, tides, waves, other
Transportation: alternative vehicle technologies, plug-in technologies, other
Geothermal energy
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