Day-ahead energy market model for the smart distribution network in the presence of multi-microgrids based on two-layer flexible power management

Abstract

This study examines the implications of day-ahead energy markets (DA) for flexible power management (FPM) in a smart distribution network (SDN) with multiple microgrids (MMGs). MG sources are coordinated with MG operators (MGOs) in the first layer, and MGOs and SDN sources are coordinated with SDN operators in the second layer. An optimization framework with bilevels is used in the scheme. SDN participation in the wholesale and retail DA energy markets is represented by the upper-level model, equivalent to the second-layer FPM. Based on the network's linear operation and flexibility constraints and active load and source operation models, it minimizes the expected SDN energy cost in the markets mentioned. It has the same formulation as the upper-level problem but concerns MG's participation in the retail DA energy market. This corresponds to the first layer of FPM. After that, a single-level formulation is developed using the Karush-Kuhn-Tucker method, and stochastic programming models uncertainty about load, energy price, renewable generation power, and mobile active load energy demand. In this scheme, two-layer power management between microgrids and the distribution network; simultaneous modelling of economic, operation, and flexibility indices; and simultaneous participation of microgrids and the distribution network in the wholesale and retailer energy markets are the novelties. Ultimately, based on quantitative results, the proposed approach is evaluated in terms of its ability to improve the economic, operational, and flexibility state. The proposed scheme reduces the energy loss in the microgrids and the distribution network by around 43%-67% compared to power flow studies. Voltage drop in the proposed scheme is enhanced by about 40%-47% in the suggested scheme compared to power flow analysis. The economic status of the network is improved by roughly 22% in comparison with power flow studies. Also, the presented scheme can provide almost 100% flexibility conditions; however, it is corresponding to increased energy cost.