Dynamic Economic Dispatch Model of Microgrid Containing Energy Storage Components Based on a Variant of NSGA-II Algorithm

Abstract

With the development of microgrid, in order to improve the economy of the microgrid and intelligent service of electric power marketing, the proper management of the output of micro-source in microgrid and power exchange between grids is an urgent problem to be solved. Considering the interests of multiple stakeholders, such as users, power grids, renewable energy and battery, a dynamic economic dispatch model of microgrid is proposed in this paper based on time-of-use power price mechanism. Using a variant of Non-Dominated Sorting Genetic Algorithm (NSGA)-II algorithm, at the same time, an external penalty function is introduced to deal with the constraint conditions, which is convenient for solving multi-objective optimization models. Based on the data of load forecasting and renewable energy output in microgrid, the function of battery and time-of-use power price mechanism is considered to optimize the output of controllable micro-source in the system, in order to achieve the optimization of microgrid dispatch. The model established in this paper considers the overall economic optimization of multi-objective and multi-interest groups within the microgrid, and hence, can get a more comprehensive and reasonable scheduling scheme. It provides effective help for the operation of micro grid system, and realizes the electric power marketing for demand side, so as to provide help for improving the power marketing’s economy and intelligent service.

Multi-Objective Environmental Economic Dispatch of an Electricity System Considering Integrated Natural Gas Units and Variable Renewable Energy Sources

“…The algorithm guarantees that the crowding strategy will be able to select a diverse set of solutions. Finally, the continuation of this algorithm will promise a better spread among the non-dominated solutions when the whole population converges to the Pareto-optimal front [43].…”

Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids

“…No extra diversity control is needed, elitism preserve pareto-optimal solutions More members in the first non-dominated set lead place to other pareto-optimal solutions [109][110][111] Multi-objective evolutionary algorithm (MOEA)…”

Multi-Objective Based Optimal Energy Management of Grid-Connected Microgrid Considering Advanced Demand Response

“…Clearly, most of the power sources considered in the MG are micro-power sources, in other words, the aggregation of small actual entities that cover various forms of power generation such as renewable energy generation (PV system and WT) and non-renewable generation (DE). To link the renewable and non-renewable energy, several power conversion systems could be requested by the MG [23]. Although converters can be synchronized with the grid to control the grid current and maximum power tracking point, the efficiency of the converter was not considered in our work because the DC/AC or DC/DC conversion efficiency is negligible in the MG system [24].…”