An Interactive Fuzzy Satisfying-Based Simulated Annealing Technique for Economic Emission Load Dispatch with Nonsmooth Fuel Cost and Emission Level Functions

2004 ◽  
Vol 32 (2) ◽  
pp. 163-173 ◽  
Author(s):  
M. BASU
Keyword(s):  
Simulated Annealing ◽  
Fuel Cost ◽  
Emission Level

Immune-Based Algorithm for Power Economic Emission Dispatch

2013 ◽  
Vol 470 ◽  
pp. 785-789 ◽  
Author(s):  
Chao Lung Chiang
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Inequality Constraints ◽  
Small Population ◽  
Previous Method ◽  
Fuel Cost ◽  
Artificial Immune ◽  
Emission Level ◽  
Equality And Inequality Constraints ◽  
Emission Dispatch

This paper proposes an artificial immune system for the economic environmental dispatch (EED) of the hydrothermal power system (HPS), considering non-smooth fuel cost and emission level functions. The artificial immune system (AIS) equipped with an accelerated operation and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to handle the equality and inequality constraints of the HPS, and the ε-constraint technique is employed to manage the constraints of HPS. To show the advantages of the proposed algorithm, one example addressing the best compromise is applied to test the EED problem of the HPS. The proposed algorithm integrates the AIS, the MU and the ε-constraint technique, revealing that the proposed approach has the following merits – 1)ease of implementation; 2)applicability to non-smooth fuel cost and emission level functions; 3)better effectiveness than the previous method, and 4)the requirement for only a small population in applying the optimal EED problem of the HPS.

Multi-Objective Economic Environmental Dispatch of Variable Hydro-Wind-Thermal Power System

2021 ◽  
Vol 12 (2) ◽  
pp. 16-35
Author(s):  
Suman Kumar Dey ◽  
Deba Prasad Dash ◽  
Mousumi Basu
Keyword(s):  
Power System ◽  
Thermal Power ◽  
Nox Emission ◽  
Fuel Cost ◽  
Nsga Ii ◽  
So2 Emission ◽  
Emission Level ◽  
Multi Objective ◽  
Thermal Power System ◽  
Operational Constraints

This article presents a multi-objective economic environmental/emission dispatch (EED) of variable head hydro-wind-thermal power system. The combination of NOx emission, SO2 emission, and fuel cost are minimized for non-smooth hydrothermal plants while satisfying various operational constraints like non-smooth fuel cost, penalty coefficient, and wind power uncertainty. The objectives—cost, NOx emission, and SO2 emission—are optimized at the same time. In this research, the non-dominated sorting genetic algorithm-II (NSGA-II) has been employed for solving the given problem where the total cost, NOx emission level, and SO2 emission level are optimized at the same time while satisfying all the operational constraints. The simulation results that are obtained by applying the two test systems on the proposed scheme have been evaluated against strength pareto evolutionary algorithm 2 (SPEA 2).

Hybrid Differential Evolution Based Multi-Objective Approach for Hydrothermal Power Systems

2012 ◽  
Vol 212-213 ◽  
pp. 1009-1014 ◽  
Author(s):  
Chao Lung Chiang
Keyword(s):  
Power Systems ◽  
Differential Evolution ◽  
Inequality Constraints ◽  
Small Population ◽  
Previous Method ◽  
Fuel Cost ◽  
Emission Level ◽  
Multi Objective ◽  
Equality And Inequality Constraints ◽  
Emission Dispatch

This paper develops a hybrid differential evolution based multi-objective approach for the optimal economic emission dispatch (EED) of the hydrothermal power system (HPS), considering non-smooth fuel cost and emission level functions. The hybrid differential evolution (HDE) equipped with an accelerated operation and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to handle the equality and inequality constraints of the HPS, and the ε-constraint technique is employed to manage the multi-objective problem. To show the advantages of the proposed algorithm, one example addressing the best compromise is applied to test the EED problem of the HPS. The proposed approach integrates the HDE, the MU and the ε-constraint technique, revealing that the proposed approach has the following merits - ease of implementation; applicability to non-smooth fuel cost and emission level functions; better effectiveness than the previous method; better efficiency than differential evolution (DE) with the MU (DE-MU), and the requirement for only a small population in applying the optimal EED problem of the HPS.

Penjadwalan Produksi Menggunakan Metode Simulated Annealing pada Unit Produksi Daun Pintu di PT. ML

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Rosnani Ginting ◽  
Chairul Rahmadsyah Manik
Keyword(s):  
Simulated Annealing ◽  
Problem Solving ◽  
Production Scheduling ◽  
Production Control ◽  
Delivery Time ◽  
Production Schedule ◽  
A Company ◽  
Predetermined Time ◽  
Factory Floor

Penjadwalan merupakan aspek yang sangat penting karena didalamnya terdapat elemen perencanaan dan pengendalian produksi bagi suatu perusahaan yang dapat mengirim barang sesuai dengan waktu yang telah ditentukan, untuk memperoleh waktu total penyelesaian yang minimum. Masalah utama yang dihadapi oleh PT. ML adalah keterlambatan penyelesaian order yang mempengaruhi delivery time ke tangan costumer karena pelaksanaan penjadwalan produksi dilantai pabrik belum menghasilkan makespan yang sesuai dengan order yang ada. Oleh kaena itu dituntut untuk mencari solusi pemecahan masalah optimal dalam penentuan jadwal produksi untuk meminimisasi total waktu penyelessaian (makespan) semua order. Dalam penelitian ini, penjadwalan menggunakan metode Simulated Annealing (SA) diharapkan dapat menghasilkan waktu total penyelesaian lebih cepat dari penjadwalan yang ada pada perusahaan.   Scheduling is a very important aspect because in it there are elements of planning and production control for a company that can send goods in accordance with a predetermined time, to obtain a minimum total time of completion. The main problem faced by PT. ML is the delay in completing orders that affect delivery time to customer because the implementation of production scheduling on the factory floor has not produced the makespan that matches the existing order. Therefore, it is required to find optimal problem solving solutions in determining the production schedule to minimize the total time of elimination (makespan) of all orders. In this study, scheduling using the Simulated Annealing (SA) method is expected to produce a total time of completion faster than the existing scheduling in the company.

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