Multi-stage optimal allocation of energy storage considering long-term load probability prediction

doi:10.3969/j.issn.2097-0706.2024.02.003

Abstract

Abstract:

With the gradual penetration of high-proportion new energy into the power grid,the randomness and uncertainty of its output puts forward higher requirements for the safe and stable operation of the power system. An energy storage device can be taken as a power user and a flexibility source, improving the regulation capacity of the power grid. When it is applied on grid side,its power and capacity configuration will affect the stable operation and economic planning of the power system. A multi-stage optimal allocation method of energy storage considering long-term load probability prediction is proposed, to reasonably allocate the capacity of independent large-scale energy storage devices on grid side. Firstly, the cost-effectiveness analysis is conducted on the independent energy storage device on grid side, then the long-term load probability prediction model based on nonparametric combinatorial regression is used to achieve the multi-stage economic optimization. And the optimization model is established and solved by improved particle swarm algorithm. Finally,taking a power system in Jiuquan area as the study case, the sensitivity analysis of energy storage economy is made from the two aspects, peak-valley electricity price difference and new energy utilization rate, and the results verify the feasibility and superiority of the proposed optimal allocation method.

Key words: optimal configuration of energy storage, long-term load forecasting, multi-phase planning, sensitivity analysis, high-proportion new energy

CLC Number:

TK01

LI Yimin, DONG Haiying, DING Kun, WANG Jinyan. Multi-stage optimal allocation of energy storage considering long-term load probability prediction[J]. Integrated Intelligent Energy, 2024, 46(2): 19-27.

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参数	数值
单位功率成本c_p/（元·kW^-1）	1 270
单位容量成本s_p/[元·(kW·h)^-1]	1 650
折算系数β_j	0.13
通货膨胀率k/%	1.5
贴现率d/%	9
充电效率ηcha	0.9
放电效率ηdis	0.9
最大荷电状态S_{OC max}	0.8
最小荷电状态S_{OC min}	0.2
峰值电价/[元·(kW·h)^-1]	1.0
谷时电价/[元·(kW·h)^-1]	0.3

年份	不同分位点的预测值			规划
年份	20%	50%	80%	规划
2023	8 012	8 377	8 595	8 325
2024	9 158	9 574	9 824	9 491
2025	10 440	10 915	11 120	10 820

阶段	储能功率/MW	储能容量/(MW·h)
2023	1 100.1	6 166.7
2024	691.9	3 459.5
2025	918.5	3 674.0