Many-Objective Evolutionary Optimization Based Economic Dispatch of Integrated Energy System with Multi-microgrid and CHP

Integrated energy system (IES) containing a variety of heterogeneous energy supplies has been widely focused on energy conversion and power dispatching for effective utilization on energy. However, existing studies are most directed to single micro-grid based IES without considering energy exchange among several micro-grids and the corresponding high-dimensional dispatching models. Motivated by these, we here consider an IES with many micro-grids supplies for combinations of cooling, heating and power (CCHP). The structure of such a system is first presented, and then the corresponding model of many-objective based power dispatching is given in detail. In our model, the operational economy and the environment pollution of each micro-grid are taken as optimized objectives. Then, NSGA-III, a powerful evolutionary algorithm for many-objective optimization is used to solve the dispatching model. The effectiveness of the proposed algorithm is experimentally demonstrated by applying it to a practical problem.

[1]  Kalyanmoy Deb,et al.  An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints , 2014, IEEE Transactions on Evolutionary Computation.

[2]  Hua Xu,et al.  An improved NSGA-III procedure for evolutionary many-objective optimization , 2014, GECCO.

[3]  Ming Jin,et al.  Microgrid to enable optimal distributed energy retail and end-user demand response , 2018 .

[4]  R. K. Singh,et al.  Optimum Siting and Sizing of Distributed Generations in Radial and Networked Systems , 2009 .

[5]  Jun Zeng,et al.  A Multi-Energy Microgrid Modelling and Optimization Method Based on Exergy Theory , 2018, 2018 Chinese Automation Congress (CAC).

[6]  Gevork B. Gharehpetian,et al.  Optimization of distributed generation capacities in buildings under uncertainty in load demand , 2013 .

[7]  Ye Tian,et al.  A Classification-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization , 2019, IEEE Transactions on Evolutionary Computation.

[8]  Qingfu Zhang,et al.  On Tchebycheff Decomposition Approaches for Multiobjective Evolutionary Optimization , 2018, IEEE Transactions on Evolutionary Computation.

[9]  Kay Chen Tan,et al.  A Subregion Division-Based Evolutionary Algorithm With Effective Mating Selection for Many-Objective Optimization , 2020, IEEE Transactions on Cybernetics.

[10]  Tao Long,et al.  Optimization Strategy of CCHP Integrated Energy System Based on Source-Load Coordination , 2018, 2018 International Conference on Power System Technology (POWERCON).

[11]  Chongqing Kang,et al.  Optimal joint-dispatch of energy and reserve for CCHP-based microgrids , 2017 .

[12]  G. Andersson,et al.  Optimal Power Flow of Multiple Energy Carriers , 2007, IEEE Transactions on Power Systems.

[13]  Jianzhong Wu,et al.  Steady state flow analysis for integrated urban heat and power distribution networks , 2009, 2009 44th International Universities Power Engineering Conference (UPEC).