A Risk-based Competitive Bi-level Framework for Operation of Active Distribution Networks with Networked Microgrids

Abstract

This paper presents a risk-based competitive bi-level framework for optimal decision-making in energy sales by a distribution company (DISCO) in an active distribution network (ADN). At the upper level of this framework, the DISCO and a rival retailer compete for selling energy. The DISCO intends to maximize its profit in the competitive market. Therefore, it is very important for the DISCO to make a decision and offer an optimal price for attracting customers and winning the competition. Networked microgrids (MGs) at the lower level, as the costumers, intend to purchase energy from less expensive sources in order to minimize costs. There is a bi-level framework with two different targets. The genetic algorithm is used to solve this problem. The DISCO needs to be cautious, so it uses the conditional value at risk (CVaR) to reduce the risk and increase the probability of making the desired profit. The effect of this index on the trade between the two levels is studied. The simulation results show that the proposed method can reduce the cost of MGs as the costumers, and can enable the DISCO as the seller to win the competition with its rivals.

Two-Stage Dynamic Alliance Bidding for Incremental Distribution and Retail Companies Based on Complex Network Theory

“…To handle the nonlinear or nonconvex of these bi-level optimization models, some heuristic methods, such as the particle swarm and genetic algorithms, are developed by Fang et al (2020) and Hamedi et al (2021). However, when the number of variables is large, these kinds of methods often suffer from local optimal and solution time is lone.…”

“…The operation problem of the IDRC as a strategic player has been studied in several works. In an active distribution network (ADN), a risk-based competitive bi-level framework is proposed by Hamedi et al (2021). As the leader of the game, IDRCs offer an optimal price for winning the competition.…”