通过释放商业储能灵活性来提高可再生能源的渗透率
Increasing the Peneteration of Renewables by Releasing Merchant Energy Storage Flexibility
摘要：
预计大型储能设施（ESF）将成为未来能源市场的重要组成部分，以增加可再生能源的渗透率。本文提出了一种新的优化算法来参与大规模的商业ESF，以应对可再生能源的波动。ESF是一个投资者拥有和独立经营的，寻求最大限度地提高其总利润，同时对冲系统对净负荷变化。为此，一个精确的计算高效的双层混合整数线性规划（MILP）的设想。ESF运营商试图在上层实现自身利润最大化，而ISO则寻求在下层清除市场。原则上，ESF将能够构建其出价/出价曲线，以从/向不同市场购买/出售。为了保持问题的易处理性，每一个较低的水平是由其KKT最优性条件取代，和非线性转化为线性等价物，使用强对偶理论渲染单级MILP，从而重铸为MPEC。此外，建议的框架是根据信息差距决策论（IGDT）工具来捕捉不确定性对ESF利润的不利影响。
英文摘要：
It is anticipated that large-scale energy storage facility (ESF) will become an essential part of the future energy markets to increase the penetration of renewables. In this paper, a new optimization algorithm is developed to participate in large-scale merchant ESF to deal with renewables fluctuations. The ESF is an investor-owned and independently-operated, seeking to maximize its total profit while hedging the system against net-load variation. To do so, an exact computationally efficient bi-level mixed-integer linear programming (MILP) is envisaged. The ESF operator tries to maximize its own profit at the upper level while ISO seeks to clear the markets at the lower level. In principle, the ESF will be able to construct its bidding/offering curves to buy/sell from/to different markets. To maintain the tractability of the problem, each lower level is replaced by its KKT optimality conditions, and nonlinearities are converted into linear equivalents using strong duality theory rendering the single-level MILP and consequently recast as an MPEC. Additionally, the proposed framework is constructed according to the information gap decision theory (IGDT) instrument to capture the adverse impact of uncertainty on the profit of ESF.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
