Research on Operational Benefit Improvement Strategy of Optical Storage Power Station Based on Genetic Ant Colony Algorithm

doi:10.11930/j.issn.1004-9649.202101001

Electric Power ›› 2022, Vol. 55 ›› Issue (2): 9-18.DOI: 10.11930/j.issn.1004-9649.202101001

• Special Columns on Smart Grid Key Projects of the 13th Five-Year Plan:（11）Key Technologies of New Energy Storage and Energy Conversion • Previous Articles Next Articles

Research on Operational Benefit Improvement Strategy of Optical Storage Power Station Based on Genetic Ant Colony Algorithm

CAO Yaqi¹, ZHAO Bo¹, WANG Lijie¹, LI Xiangjun², GAO Binheng³

1. Beijing Information Science and Technology University, Beijing 100192, China;
2. State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems, China Electric Power Research Institute, Beijing 100192, China;
3. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China

Received:2021-01-05 Revised:2021-04-05 Online:2022-02-28 Published:2022-02-23
Supported by:
This work is supported by the National Natural Science Foundation of China (Research on Short-Term Generation Power Prediction of Grid-connected Wind Farms Based on Numerical Weather Prediction Information Fusion, No.51607009), Open Fund of Operation and Control of Renewable Energy & Storage Systems(Research on Equivalent Model and Characteristic Parameter Identification Technology of Large Capacity Energy Storage Power Station, No. DGB51201901183) and Young Talent Cultivation Plan of High-Level Teachers Construction of Beijing Municipal Institutions (No.CIT&TCD201804053).

Abstract

Abstract: This article takes the grid-connected optical storage regional power grid as the research object, and starts the research with the full use of the flexible regulation role of the energy storage system and the improvement of the system operation economy. On the basis of considering the cost of electricity, a control strategy for real-time adjustment of the BESS operating state is proposed, and an optimization model is established with the goal of maximizing net income, minimizing total cost, and extracting electricity from the large grid. The genetic-ant colony algorithm of the penalty function solves the optimization model, and analyzes the investment income of the grid-connected optical storage system from the perspective of investors. Finally, through the simulation analysis of actual data in a certain area of Jiangsu, the optimization control strategy of "photovoltaic and energy storage" in this area and the results of economic benefit analysis are given to verify the feasibility of this model and algorithm.

Key words: photovoltaic and energy storage, energy storage real-time optimization control strategy, operational economic benefits, net present value, investment recovery period

CAO Yaqi, ZHAO Bo, WANG Lijie, LI Xiangjun, GAO Binheng. Research on Operational Benefit Improvement Strategy of Optical Storage Power Station Based on Genetic Ant Colony Algorithm[J]. Electric Power, 2022, 55(2): 9-18.

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Research on Operational Benefit Improvement Strategy of Optical Storage Power Station Based on Genetic Ant Colony Algorithm

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