Dynamic Setting Method of Assessment Indicators for Power Curves of Renewable Energy Sources Considering Scarcity of Reserve Resources

With the increasing proportion of renewable energy sources (RESs) in power grid, the reserve resource (RR) scarcity for correcting power deviation of RESs has become a potential issue. Consequently, the power curve of RES needs to be more rigorously assessed. The RR scarcity varies during different time periods, so the values of assessment indicators should be dynamically adjusted. The assessment indicators in this paper include two aspects, i. e., deviation exemption ratio and penalty price. Firstly, this paper proposes a method for dynamically calculating the supply capacity and RR cost, primarily taking into account the operating status of thermal units, forecast information of RES, and load curve. Secondly, after clarifying the logical relationship between the degree of RR scarcity and the values of assessment indicators, this paper establishes a mapping function between them. Based on this mapping function, a dynamic setting method for assessment indicators is proposed. In the future, RES will generally be equipped with battery energy storage systems (BESSs). Reasonably utilizing BESSs to reduce the power deviation of RESs can increase the expected income of RESs. Therefore, this paper proposes a power curve optimization strategy for RESs considering self-owned BESSs. The case study demonstrates that the dynamic setting method of assessment indicators can increase the revenue of RESs while ensuring that the penalty fees paid by RESs to the grid are sufficient to cover the RR costs. Additionally, the power curve optimization strategy can help RESs further increase income and fully utilize BESSs to reduce power deviation.