Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks

The unbalance between the renewable energy sources and user loads reduces the performance improvement of regional integrated energy systems (RIES), in which the multi-energy storage system with battery and heat tank is necessarily integrated. This paper aims to optimize the sites and capacities of m...

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Vydáno v:Energy (Oxford) Ročník 261; s. 125240
Hlavní autoři: Wang, Jiangjiang, Deng, Hongda, Qi, Xiaoling
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 15.12.2022
Témata:
algorithms
batteries
Capacity optimization
electricity
heat
heat pumps
Multi-energy storage system
Power and heat networks
Regional integrated energy systems (RIES)
Siting optimization
system optimization
thermal energy
wind
wind power
Capacity optimization
Multi-energy storage system
Siting optimization
Power and heat networks
Regional integrated energy systems (RIES)
ISSN:0360-5442
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Shrnutí:The unbalance between the renewable energy sources and user loads reduces the performance improvement of regional integrated energy systems (RIES), in which the multi-energy storage system with battery and heat tank is necessarily integrated. This paper aims to optimize the sites and capacities of multi-energy storage systems in the RIES. A RIES model including renewable wind power, power distribution network, district heating network, multi-energy storage system, and heat pump to convert electricity to heat is constructed. An optimization method combining a mixed-integer nonlinear programming optimization model is proposed to minimize the comprehensive cost of RIES. The second-order cone relaxation method performs convex relaxation of the power flow constraints, and the district heat network is operated under a constant-flow-variable-temperature strategy. The original optimization model is transformed into a mixed-integer second-order cone programming problem to solve. Three solution methods, including enumeration method, improved enumeration method and genetic algorithm, are employed to determine the optimum installation locations, and they are compared in computation time and efficiency. The results demonstrate that the distributed hybrid integration of electricity and thermal energy storages improves the RIES economy by collaborating the power and heat balances and reducing the purchased electricity from the grid. By integrating the hybrid storage system, the curtailed wind is reduced by 53.9%, and the economy is improved by 13.4%. •A two-stage optimization model of multi-energy storage configuration is developed.•The sites and capacities of hybrid energy storages in power and thermal networks are optimized.•Three methods to determine the installation locations are compared.•The economics performances at different configuration strategies are compared.•The hybridization reduces curtailed wind power by 53.9% and improves economic performance by 13.4%.
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ISSN:0360-5442
DOI:10.1016/j.energy.2022.125240