An enhanced moth-swarm algorithm for efficient energy management based multi dimensions OPF problem
- PDF / 4,626,544 Bytes
- 21 Pages / 595.276 x 790.866 pts Page_size
- 70 Downloads / 189 Views
ORIGINAL RESEARCH
An enhanced moth‑swarm algorithm for efficient energy management based multi dimensions OPF problem Bachir Bentouati1 · Aboubakr Khelifi1 · Abdullah M. Shaheen2 · Ragab A. El‑Sehiemy3 Received: 25 May 2020 / Accepted: 8 November 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The optimal power flow (OPF) problem is very important issue in operation, planning and energy management of power systems. OPF analysis aims to find the optimal solution of system nonlinear algebraic equations with satisfying operational constraints. Economic, environmental and technical objectives are considered for multi-dimensions efficient energy management. These objectives involve the reduction of the production costs, reduction of the environmental emissions, improving the voltage profile, reducing the power losses and enhancing the system stability. This paper presents a new high-efficiency technology that proposes a multi-objective version of the recently proposed moth swarm algorithm (MSA) i.e. enhanced MSA (EMSA). The modification is implemented based on quasi-opposition-based learning. In order to verify the efficacy of proposed EMSA, the simulations are done in the IEEE 30-bus and IEEE 57-bus test systems. The scalability of the proposed method is proved on the IEEE 118-bus test network. The outcomes are compared with that obtained by MSA and the reported methods in the literature. From the outcomes obtained, it is strongly confirmed that proposed EMSA performs considerably better than MSA to address different test objectives with significant improvements of the considered complex power system. Keywords Enhanced moth swarm algorithm · Fuel cost · Voltage stability improvement · Real power loss · Multi-objective optimal power flow Abbreviations ai , bi , ci Cost coefficients of ith generator 𝛼i , 𝛽i , 𝛾i , 𝜉i and 𝜆i Emission coefficients of ith unit PGi Real power bus generator PD , QD Active and reactive load demands Gij Transfer conductance Bij Susceptance between bus i and bus j VG Voltage levels at generation buses TG Transformers tap setting QC Shunt VAR compensation xjmin , xjmax Upper and lower limit of candidate solutions
* Ragab A. El‑Sehiemy [email protected] 1
Electrical Engineering Department, LMSF Laboratory, Amar Telidji University of Laghouat, 03000 Laghouat, Algeria
2
Electrical Engineering Department, Suez University, Suez, Egypt
3
Electrical Engineering Department, Kafrelsheikh University, Kafr El‑Sheikh, Egypt
nh Small group of moths walks into random spiral path inside the neighborhood of light source nol Small moth group drifts towards the moonlight 𝜎jt Normalized form of dispersal degree at iteration 𝜇t Relative dispersion cp Crossover points t Bestglobal Best global solution ngw Gaussian walk xit+1 Onlooker moths Xqo Quasi-opposite point
1 Introduction The optimal power flow (OPF) problem is one of the basic problems with given or fixed load power and generator power. Over the past few decades, OPF has been one of the
Data Loading...
