Solving the Multi-Objective Optimal Power Flow Problem Using the Multi-Objective Firefly Algorithm with a Constraints-Prior Pareto-Domination Approach
| Autor: | Hangtian Lei, Zhizhong Zhang, Xingting Yi, Gonggui Chen |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Mathematical optimization
Control and Optimization Optimization problem Computer science 020209 energy media_common.quotation_subject Energy Engineering and Power Technology 02 engineering and technology Multi-objective optimization lcsh:Technology multi-objective firefly algorithm multi-objective optimal power flow problem constraints-prior Pareto-domination approach quality indicator 0202 electrical engineering electronic engineering information engineering Firefly algorithm Penalty method Electrical and Electronic Engineering Engineering (miscellaneous) media_common Variables Renewable Energy Sustainability and the Environment lcsh:T Pareto principle Sorting Constraint (information theory) Energy (miscellaneous) |
| Zdroj: | Energies; Volume 11; Issue 12; Pages: 3438 Energies, Vol 11, Iss 12, p 3438 (2018) |
| ISSN: | 1996-1073 |
| DOI: | 10.3390/en11123438 |
| Popis: | Known as a multi-objective, large-scale, and complicated optimization problem, the multi-objective optimal power flow (MOOPF) problem tends to be introduced with many constraints. In this paper, compared with the frequently-used penalty function-based method (PFA), a novel constraint processing approach named the constraints-prior Pareto-domination approach (CPA) is proposed for ensuring non-violation of various inequality constraints on dependent variables by introducing the Pareto-domination principle based on the sum of constraint violations. Moreover, for solving the constrained MOOPF problem, the multi-objective firefly algorithm with CPA (MOFA-CPA) is proposed and some optimization strategies, such as the crowding distance calculation and non-dominated sorting based on the presented CPA, are utilized to sustain well-distributed Pareto front (PF). Finally, in order to demonstrate the feasible and effective improvement of MOFA-CPA, a comparison study between MOFA-CPA and MOFA-PFA is performed on two test systems, including three bi-objective optimization cases and three tri-objective optimization cases. The simulation results demonstrate the capability of the MOFA-CPA for obtaining PF with good distribution and superiority of the proposed CPA for dealing with inequality constraints on dependent variables. In addition, some quality indicators are used to evaluate the convergence, distribution, and uniformity of the PFs found by the MOFA-CPA and MOFA-PFA. |
| Databáze: | OpenAIRE |
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