Energy Reports (Nov 2021)
Multi-objective economic optimization scheduling of CCHP micro-grid based on improved bee colony algorithm considering the selection of hybrid energy storage system
Abstract
By factoring into the model selection of a hybrid energy storage system, this paper established an economically optimized multi-objective dispatching model for a micro-grid of Combined Cooling Heating and Power (CCHP) based on an improved Algorithm of Artificial Bee Colony (ABC). To upgrade the single-objective model in previous studies, the optimization goal of the model is to minimize the daily power generation dispatching cost and daily environmental pollutant treatment cost of the micro-grid, and the improved Algorithm of ABC based on Beetle Antennae Search Algorithm (BAS-ABC) was used to obtain a solution. To achieve a better application of theoretical results, the paper studied the summer typical daily real power load data of a grid-connected CCHP micro-grid in a district of Shanghai, and simulated a multi-objective economical dispatching model under the condition of using the Time of Use (TOU) billing system. The result shows that the minimum cost derived from the solution of the optimized ABC is lower than that from the traditional ABC. Furthermore, when the objective function of the CCHP microgrid is the lowest power generation cost or the lowest environmental cost, the optimized results are contradictory: it is impossible to simultaneously achieve an optimal power generation cost and an optimal environmental cost. This indicates the multi-objective optimized dispatching approach has comprehensively balanced the economic efficiency and the environmental-friendliness of the system.
