1. Microgrid system operation optimization model
references:
[1] Li Xingxin, Zhang Jing, He Yu, et al. Multi-objective optimal dispatch of microgrid based on improved particle swarm algorithm [J]. Electric Power Science and Engineering, 2021, 37(3):7
2. Multi-objective artificial hummingbird algorithm MOAHA
The multi-objective artificial hummingbird algorithm (MOAHA) is an efficient multi-objective optimization algorithm proposed in 2022. It uses the dynamic elimination-based crowding distance (DECD) to maintain the external Archive.
The MOAHA algorithm is described as follows:
references:
[1]Weiguo Zhao, Zhenxing Zhang, Seyedali Mirjalili, Liying Wang, Nima Khodadadi, Seyed Mohammad Mirjalili.An effective multi-objective artificial hummingbird algorithm with dynamic elimination-based crowding distance for solving engineering design problems,Computer Methods in Applied Mechanics and Engineering, 398,2022,
3. Solution results
(1) Part of the code
close all;
clear ;
clc;
global P_load; %electric load
global WT;% wind power
global PV;% photovoltaic
%%
TestProblem=1;
MultiObj = GetFunInfo(TestProblem);
MultiObjFnc=MultiObj.name;%problem name
% Parameters
params.Np =100; % population size (can be modified)
params.Nr =200; % (size of external archive)
params.maxgen =100; % maximum number of iterations (can be modified)
[Xbest,Fbest] = MOAHA(params,MultiObj);
% Xbest is the POX obtained by MOAHA
% Fbest is the POF obtained by MOAHA
%% Draw the result figure
figure(1)
plot(Fbest(:,1),Fbest(:,2),'ro');
legend( 'MOAHA');
xlabel('operating cost')
ylabel('environmental protection cost')
(2) Partial results
At the lowest operating cost:
