Optimized Energy Storage Capacity Allocation Based on Prediction Error Compensation Degree and Economic Benefits of Wind Power

doi:10.11930/j.issn.1004-9649.2016.05.141.08

Abstract

Abstract: The energy storage system can, through real time charging and discharging, compensate the error between predicted day-ahead output and actual output of wind power to indirectly improve the wind power prediction accuracy and utilization efficiency. Due to the constrains of energy storage cost, it is imperative to study the method for selecting the optimal energy storage capacity. Based on the contrast analysis of abandoned wind reduction, thermal power reserve capacity reduction, environment-friendly benefits, energy storage investment and operation & maintenance cost, different error compensation degrees are determined according to the probability distribution of wind power prediction errors, and subsequently the corresponding energy storage capacity, the economic benefits and the years for recovering the energy storage costs are in turn obtained. The energy storage capacity allocation and the year for recovering costs under the optimal compensation level are determined according to the relationship among compensation degree, energy storage capacity and the year for recovering costs. A case study is conducted by simulation for a wind farm of 148.5 MW in Xinjiang, and it is concluded that by limiting the day-ahead prediction error of wind power to ±25%, the optimal compensation degree is 91.5%, the optimal energy storage capacity is 12.28 MW, and it needs about 7.58 years to recover the costs.

Key words: energy storage, reduction of abandoned wind, wind power prediction error, compensation degree, benefit assessment

CLC Number:

TM715
TK82

HU Yawei, LI Jiang, HU Liqiang, CHAO Qin, HU Xukun, YANG Yang, LIU Qinggui. Optimized Energy Storage Capacity Allocation Based on Prediction Error Compensation Degree and Economic Benefits of Wind Power[J]. Electric Power, 2016, 49(5): 141-148.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.2016.05.141.08

https://www.electricpower.com.cn/EN/Y2016/V49/I5/141

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