Micro Grid Economic Optimization Study Based On Improved Differential Evolution Algorithm

Smart grid technology has already been a trend spanning from nation to nation. At thesame time, micro grid has demonstrated to be an embracive organism for the accession of newenergy sources. Apparently, it can be inferred that the realization of its optimal operation willdirectly influence its economy, reliability and the exploitation rate of renewable energy. As forthe energy management system, it is responsible for the scheduling of new energy generation,while the economic optimization is the purpose of minimizing the overall power cost.This paper firstly approaches the power output characteristics of distributed generatorsconcerning with the cost function, cooling, heating and power relation as well as theenvironmental attributes of the micro grid. Then, a model corresponding to combined cooling,heating and power micro grid system is developed using simulink tool. In order to achieve atotal power cost minimization preconditioned by satisfying the cooling, heating and powerdemand of the users, the modified differential evolution algorithm, with the priority of lesserrunning time and higher accuracy, is employed to contribute an optimal adjustment of poweroutput of each component and parameter settings in the framework of the energy managementsystem.Afterwards, this algorithm has also been applied to solve the unit commitment andbattery charging strategy problems when attempting to reach a full day running economy ofthe micro grid, which could avoid the shortsighted effect that only concentrates on the currentstate resulting from the real-time optimization. As a result, additional economic benefits canbe rewarded.Finally, the environmental characteristics and operational objectives of three typicalscenarios including the island, building and park modes are analyzed in line with therespective energy management system, which can be hopefully functioned as a reference forthe future design with the proposed algorithm.Based on the above diverse examples, it can be verified that the differential evolutionalgorithm and the optimal strategy are proved to be practical and effective when applying tothe issues of real time optimization of economy, unit commitment and storage dispatching. Toa large extent,the proposed method is of great use for the guidance of the economicaloptimization of the micro grid.