Abstract
Increasing penetration of distributed generation (DG) has brought more uncertainty to the operation of active distribution networks (ADNs). With the reformation of the power system, increasingly more flexible loads access to distribution network through load aggregators (LAs), which becomes an effective way to solve these issues. Since LAs and ADNs are separate entities with different interests, the traditional centralized and deterministic optimization methods fail to meet the actual operational requirements of ADNs. Based on the linear power flow model, a robust optimal dispatching model of ADNs considering the influence of renewable DG’s uncertain output on voltage security constraints is established. Then, an independent optimal scheduling model for LAs is modeled based on the analysis of the composition and characteristics of flexible load in LAs. LAs and ADNs, as two different stakeholders, use a distributed modeling method to establish different economic optimization goals. The optimization problem is solved by decoupling the coupling exchanging power between LAs and ADNs into virtual controllable loads and virtual DGs. Finally, with the case study of a modified IEEE 33-bus system, the correctness and effectiveness of the proposed method are verified. The effects of the robust level and demand response incentive on the results are also analyzed.
Highlights
With continuously increasing penetration of renewable energy, the uncertainty and intermittency of clean energy challenge the operation of distribution network (Ehsan and Yang, 2019)
Since the low electricity consumption level and Demand Response (DR) efficiency of an individual user (Adrian et al, 2018), the flexible load can participate in the DR program through the load aggregators (LAs) (Herre et al, 2020), which promotes the massive participation of flexible loads in the demand side and in guiding the users to consume electricity properly and economically (Wang et al, 2020)
The contributions of this article are summarized as follows: (1) This study proposes a distributed optimal scheduling model with DR incentive
Summary
With continuously increasing penetration of renewable energy, the uncertainty and intermittency of clean energy challenge the operation of distribution network (Ehsan and Yang, 2019). The article by Yu and Hong (2017) proposes a novel incentive-based demand response model from the view of a grid operator to enable system-level dispatch of demand response resources by adjusting the electricity price. Those literatures take the dynamic game process between two stakeholders into consideration. This article tries to answer these questions and presents an effective, robust, and distributed optimal scheduling for ADNs connected with multiple LAs by coordinating the controllable devices in power supply and demand sides, while addressing the uncertain DG output. The detailed dynamic economic dispatching models of the ADN and the LA are given below
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