尺寸
资本成本
风力发电
储能
网格
可靠性工程
发电
可再生能源
数学优化
总成本
计算机科学
运筹学
工程类
功率(物理)
经济
数学
电气工程
物理
量子力学
艺术
几何学
视觉艺术
微观经济学
作者
Shiwei Xia,Ka Wing Chan,Xiao Luo,Siqi Bu,Zhaohao Ding,Bin Zhou
标识
DOI:10.1016/j.renene.2018.02.010
摘要
Energy storage system (ESS) is a key technology to accommodate the uncertainties of renewables. However, ESS at an improper size would result in no-reasonable installation, operation and maintenance costs. With concerns on these costs outweighing ESS operating profit, this paper establishes a stochastic model to size ESS for power grid planning with intermittent wind generation. In the model, the hourly-based marginal distributions with covariance is first derived from historical data of wind generation, and a stochastic cost-benefit analysis model with consideration of the generation fuel cost expectation and ESS amortized daily capital cost is formed. Then a hybrid solution approach combining the Point Estimated method and the parallel Branch and Bound algorithm (PE-BB) is designed to solve the model. Finally, the stochastic model and PE-BB approach are thoroughly tested on the 10-unit and 26-unit systems with uncertain wind generation. Simulation results confirmed the proposed model and PE-BB approach are effective to optimize ESS size for power grid planning with intermittent wind generation. The cost-benefit investigations on four typical ESSs also indicated that the ESS capital cost, charging/discharging efficiency and lifetime are important properties for optimizing ESS size, and it is not always economically justifiable to install ESS in power system.
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