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Risk-Constrained Profit Maximization for Microgrid Aggregators With Demand Response

机译：具有需求响应的微电网聚合商的风险受限利润最大化

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摘要

In this paper, we consider the operation optimization for a microgrid (MG) aggregator, which can procure energy from various sources including the pool market and local distributed energy resources to serve MG customers. We assume that the MG aggregator sells electricity to customers at a predefined retail rate and it also offers customers various contracts for adjusting their loads. Our design objective is to determine the optimal hourly bids that the MG aggregator submits to the day-ahead market to maximize its profit. To deal with various uncertainties, a risk-constrained scenario-based stochastic programming framework is proposed where the MG aggregator’s risk aversion is modeled using conditional value at risk method. The proposed formulation enables customers’ demand response (DR) aggregation to be integrated into the operation of the MG aggregator via contractual agreements. This design is not only beneficial for both MG aggregator and customers, but also facilitates the operation of the system operator (SO), since a single entity (i.e., the MG aggregator) is visible to the SO instead of two separate entities (i.e., a MG aggregator and a DR aggregator). Extensive numerical results are shown to demonstrate the effectiveness of the proposed framework.
机译：在本文中，我们考虑了微电网（MG）聚合器的运行优化，该聚合器可以从包括池市场和本地分布式能源在内的各种来源获取能源，以为MG客户服务。我们假设MG聚合器以预定义的零售价向客户出售电力，并且还向客户提供各种合同来调整他们的负荷。我们的设计目标是确定MG聚合器提交给日间市场的最佳每小时出价，以使其利润最大化。为了应对各种不确定性，提出了一种基于风险约束的基于场景的随机编程框架，其中使用条件价值风险法对MG聚合器的风险规避进行了建模。提议的方案使客户的需求响应（DR）聚合可以通过合同协议集成到MG聚合器的运营中。这种设计不仅对MG聚合器和客户都有好处，而且由于单个实体（即MG聚合器）对SO可见而不是两个单独的实体（即， MG聚合器和DR聚合器）。大量的数值结果表明了所提出框架的有效性。

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