A Multitasking Electric Power Dispatch Approach With Multi-Objective Multifactorial Optimization Algorithm

Junwei Liu,Jianchun Peng,Gang Xu,Yongxing Zha,Peiling Li,Guibin Wang

doi:10.1109/access.2020.3018484

Junwei Liu, Jianchun Peng + Show 4 more

Open Access

https://doi.org/10.1109/access.2020.3018484

Copy DOI

Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 31	License type: CC BY 4.0

Affiliation: Shenzhen University, Shenzhen Technology University

Abstract

Electric power dispatch issue mainly consists of two optimization tasks: active and reactive power dispatches, each of which is a non-linear multi-objective optimization problem with a series of constraints. Traditional evolutionary algorithms are focused on single-task optimization for active or reactive power dispatch and they are not able to deal with several (single- or multi-objective) optimization tasks simultaneously. In this paper, to solve this problem, a multitasking electric power dispatch approach is proposed by introducing the multi-objective multifactorial optimization (MO-MFO) algorithm and integrating it with the characteristics of power system. The approach exhibits the great potential to be developed as a cloud-computing solver or platform for future large-scale smart grid applications involving different market entities because of its implicit parallel computation mechanism. The multitasking approach is thoroughly tested and benchmarked with IEEE-30-bus and IEEE-118-bus standard systems and exhibits generally better performances as compared to previously proposed Pareto heuristic approaches for electric power dispatch.

Highlights

Active and reactive power dispatches are two significant tasks for optimal and safety operations of modern power systems
2) TASK 2–REACTIVE POWER DISPATCH FOR THE IEEE-30-BUS SYSTEM In the computations of task 2, the transmission loss and the voltage deviation are selected as the optimization objectives, and the performance metrics of different algorithms after 30 runs of iterations are shown in Table 3, from which it can be observed that the average values of spacing, span, convergence, and lmax /lmin metrics of the multi-objective multifactorial optimization (MO-MFO) algorithm are the best
The aforementioned computation results, the overall performance metrics and solution qualities of the MO-MFO algorithm applied in the multitasking electric power dispatch problem are the best among the four algorithms