Abstract
This paper considers the economy and reliability of the microgrid cluster system, and proposes a bi-level optimized operation strategy for the microgrid cluster, which aims to improve the economic benefits of the microgrid cluster and reduce the operating risk of microgrid. The upper layer takes the microgrid cluster as the research object, with the goal of minimizing the total operating cost of the system, and establishes the optimal model of the microgrid cluster. The lower layer takes the sub-microgrid as the research object, and establishes the microgrid optimization model with the goal of optimal operating cost and operating risk index. The method of combining mixed integer linear programming and IABC algorithm is used to solve the multi-objective bi-level optimization model, and to provide decision makers with two microgrid dispatching schemes with different focuses. Finally, an example is used to verify the effectiveness of the bi-level optimization strategy and improved algorithm proposed in this paper, as well as the practicability of the two dispatching schemes.
Highlights
Energy Internet technology with new energy and the Internet as the main body is emerging
Based on the existing research and combined with the theory of bi-level optimization, this paper proposes a bi-level optimized operation strategy for microgrid cluster based on improved artificial bee colony algorithm (IABC) algorithm
The lower-layer model takes the sub-microgrid as the research object, and the optimization goal is to reduce operating costs and reduce operating risk index
Summary
Energy Internet technology with new energy and the Internet as the main body is emerging. The upper-layer model takes the microgrid cluster as the research object, and the optimization goal is the lowest system operating cost. The lower-layer model takes the sub-microgrid as the research object, and the optimization goal is to reduce operating costs and reduce operating risk index. The upper layer of this paper takes the microgrid cluster as the research object, and establishes the optimization model with the minimum total operating cost of the microgrid cluster as the optimization goal. The lower layer adopts an improved artificial bee colony algorithm to obtain the Pareto optimal solution set with the objective of the optimal operating cost and risk index of the sub-microgrid, which is convenient for decision makers to select the final result. The upper-layer optimization results, the exchange capacity and output between microgrids are sent to the lower-layer optimization model as dispatch instructions.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
