Information gap decision theory‐based electricity purchasing optimization strategy for load aggregator considering demand response,Energy Science & Engineering

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Information gap decision theory‐based electricity purchasing optimization strategy for load aggregator considering demand response
Energy Science & Engineering ( IF 3.5 ) Pub Date : 2020-11-07 , DOI: 10.1002/ese3.840
Bo Sun ₁ , Xudong Wu ₁ , Jingdong Xie ₁ , Xin Sun ₁

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The gradual improvement of the electricity market and the rapid development of demand response (DR) technology not only make the load aggregator (LA) integrate the demand side resources (DSR) to participate in the market becoming true, but also bring new problems and challenges to LA for formulating electricity purchasing optimization strategy. With the goal of minimizing the operating cost of LA participating in electricity market to purchase electricity and providing auxiliary services in response to the peak‐shaving demand planning, a deterministic day‐ahead electricity purchasing decision‐making model is established. Considering the uncertainty of wind power output and real‐time price and the different attitude of LA toward risk caused by uncertainty, we adopt stochastic scenario planning method to deal with the uncertainty of wind power output. And the information gap decision theory (IGDT) is introduced to transform the deterministic model into a day‐ahead electricity purchasing decision‐making model of LA under two different risk attitudes: risk‐averse and risk‐seeking. In order to verify the effectiveness of the proposed approach, a case study has been investigated and the day‐ahead electricity purchased optimization strategy for LA under different risk attitudes has been obtained. Moreover, the results confirm that participating in DR and improving the reliability of LA response can effectively reduce the operating cost of LA and improve the system stability.

中文翻译：

考虑需求响应的基于信息缺口决策理论的负荷聚合器购电优化策略

电力市场的逐步改善和需求响应（DR）技术的飞速发展，不仅使负载聚合器（LA）整合了需求侧资源（DSR）参与市场成为现实，而且还带来了新的问题和挑战向洛杉矶制定购电优化策略。为了最大限度地减少参与电力市场的洛杉矶市的电力购买电力的运营成本并响应调峰需求计划提供辅助服务，建立了确定性的日前购电决策模型。考虑到风电输出和实时价格的不确定性以及洛杉矶对不确定性引起的风险的不同态度，我们采用随机情景规划方法来应对风电输出的不确定性。然后引入信息缺口决策理论（IGDT），将确定性模型转变为在两种不同的风险态度下的洛杉矶的日用电购电决策模型：规避风险和寻求风险。为了验证该方法的有效性，已经进行了案例研究，并获得了在不同风险态度下洛杉矶的日购电优化策略。此外，结果证实，参与DR并提高LA响应的可靠性可以有效降低LA的运营成本并提高系统稳定性。然后引入信息缺口决策理论（IGDT），将确定性模型转变为在两种不同的风险态度下的洛杉矶的日用电购电决策模型：规避风险和寻求风险。为了验证该方法的有效性，已经进行了案例研究，并获得了在不同风险态度下洛杉矶的日购电优化策略。此外，结果证实，参与DR并提高LA响应的可靠性可以有效降低LA的运营成本并提高系统稳定性。然后引入信息缺口决策理论（IGDT），将确定性模型转变为在两种不同的风险态度下的洛杉矶的日用电购电决策模型：规避风险和寻求风险。为了验证该方法的有效性，已经进行了案例研究，并获得了在不同风险态度下洛杉矶的日购电优化策略。此外，结果证实，参与DR并提高LA响应的可靠性可以有效降低LA的运营成本并提高系统稳定性。研究了一个案例研究，并获得了在不同风险态度下洛杉矶的日购电优化策略。此外，结果证实，参与DR并提高LA响应的可靠性可以有效降低LA的运营成本并提高系统稳定性。研究了一个案例研究，并获得了在不同风险态度下洛杉矶的日购电优化策略。此外，结果证实，参与DR并提高LA响应的可靠性可以有效降低LA的运营成本并提高系统稳定性。

更新日期：2020-11-07

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