# A-Modified-Binary-PSO-to-solve-the-Thermal-Unit-Commitment-Problem
This repository contains the results of my Master thesis as published in here:
https://ethesys.lis.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0713118-191039
The thesis file can be found here:
https://drive.google.com/open?id=1g-V09C45TIsVyHdf6WtMIl_hjd0GJdHg
This project was written in the following language: MATLAB
This project contains the folllowing files:
__## Scripts__ :
- __Swarm_Generator.m__: Generates a swarm of binary particles of dimensions N x T where N is the number of units in the power system and T is the study horizon (e.g. 24 hours). This script is useful for any swarm-based metaheuristic that aims to tackle the classic Thermal Unit Scheduling problem.
- __Swarm Optimizer.m__: Implements a Binary Particle Swarm Optimization (BPSO) algorithm to solve the Thermal Unit Commitment Problem. Eight modified activations functions based on the popular sigmoid and tanh functions are considered. This optimizer performs better than Dynamic Programming, both in running time and total cost, when considering the IEEE 10-unit benchmark system.
The Dynamic Programming solution used for comparison can be found here:
https://www.mathworks.com/matlabcentral/fileexchange/32073-unit-commitment-by-dynamic-programming-method
__## Helper Functions__:
- __AFLC.m__: Returns a sorted array in a descending fashion according to AFLC criteria.
- __ED_fmincon.m__: Finds the minimum of the constrained non-linear optimization objective (fmincon)
- __F_LIM_ED.m__: Enhanced Lambda Iteration (ELI) Method to solve the Economic Dispatch problem (EDP)
- __F_LIM_ED_RR.m__ : Same as F_LIM_ED.m but considers the ramping rate constraints in the TUCP problem.
- __LIM_ED.m__ : Lambda Iteration Method to solve the Economic Dispatch problem (EDP)
- __LIM_ED_RR.m__ Same as F_LIM_ED.m but considers the ramping rate constraints in the TUCP problem.
- __Recomm_swp.m__: Recommit units to satisfy System Power Demand at time t
- __SU_COST.m__: Computes the start up and shut down costs (to expand) of the UC schedule
- __check_MUT_MDT.m__: Checks if the current schedule satisfies the MUT/MDT constraints are satisfied in the UC problem
- __check_SR_PD.m__: Checks if the current schedule satisfies the SR constraint is satisfied in the UC problem
- __constraint_repair.m__ : Schedule repair function based on the proposed pivot heuristic algorithm
- __count_intervals.m__ :Returns a vector of ON/OFF intervals & their respective duration.
- __mod_repair_MDT_MUT.m__: Modified straightforward repair for pivot heuristic
- __sf_repair_MDT_MUT.m__: Straightforward repair of MDT/MUT constraint in the Thermal UC problem
- __until_zero__ : Returns the first or last occurring zero closest to the pivot.This function is part of the modified repair strategy by pivot heuristic
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《A Modified Binary PSO to solve the Thermal Unit Commitment Problem》完全复现。代码主要做的是一个考虑需求响应的机组组合问题,首先构建了机组组合问题的基本模型,在此基础上,进一步考虑负荷侧管理,也就是需求响应,在调控过程中通过补偿引导负荷侧积极进行需求响应,在模型的求解上,采用了一种基于改进二进制粒子群算法的求解方法,相较于传统的粒子群算法,更加创新。而且求解的效果更好,代码出图效果非常好;
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A-Modified-Binary-PSO-to-solve-the-Thermal-Unit-Commitment-Problem-master.zip (44个子文件)
A-Modified-Binary-PSO-to-solve-the-Thermal-Unit-Commitment-Problem-master
matlab.gitignore 414B
sf_repair_MDT_MUT.m 2KB
Graphs
V2.mat 230B
P_SOL_OPT_26_OPTTTTT.mat 762B
P_SOL_stacked.mat 405B
PDR_OPT.mat 373B
V3_EM.mat 212B
P_SOL_OPT_RR.mat 559B
LOAD_DEMAND.mat 219B
S1.mat 216B
V3_26U.mat 224B
V1.mat 260B
P_D_26.mat 251B
P_D_DR.mat 219B
P_26OPT.mat 883B
S4.mat 222B
EM.mat 241B
S2.mat 216B
V4.mat 260B
V3_RR.mat 248B
V3.mat 208B
C_26_OPTTTT.mat 247B
S3.mat 215B
Graphs.m 6KB
V3_DR.mat 257B
P_SOL_OPT_EM.mat 416B
check_MUT_MDT.m 8KB
LIM_ED_RR.m 3KB
until_zero.m 2KB
F_LIM_ED_RR.m 5KB
ED_fmincon.m 3KB
check_SR_PD.m 849B
F_LIM_ED.m 3KB
constraint_repair.m 19KB
count_intervals.m 4KB
Recomm_swp.m 1KB
Swarm_optimizer.m 4KB
AFLC.m 360B
LIM_ED.m 2KB
mod_repair_MDT_MUT.m 7KB
README.md 3KB
Swarm_generator.m 33KB
swap.m 49B
SU_COST.m 3KB
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