A comparative analysis between price-penalty factor method and fractional programming method for combined economic emission dispatch problem using novel probabilistic CSA-JAYA algorithm

2021 ◽  
Author(s):  
B. Dey ◽  
S. Basak ◽  
B. Bhattacharyya
Keyword(s):  
Comparative Analysis ◽  
Fractional Programming ◽  
Programming Method ◽  
Jaya Algorithm ◽  
Factor Method ◽  
Penalty Factor ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

scholarly journals Grasshopper Optimization Algorithm on Combined Economic Emission Dispatch Problem Involving Cubic Functions

2019 ◽  
Vol 9 (1) ◽  
pp. 808-817
Keyword(s):  
Optimization Algorithm ◽  
Electric Power System ◽  
Test Cases ◽  
Fuel Cost ◽  
Unit System ◽  
Penalty Factor ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

In this paper, grasshopper optimization algorithm is presented to resolve the combined economic emission dispatch (CEED) problem involving cubic functions considering power flow constraints. Electric power system wants to satisfy its customers load demand with minimum fuel cost and emission. Fuel cost and emission has instantly association with energy cost. In CEED problem, the price penalty factor occupies a cardinal role to fetch the optimal results. The various types of price penalty factor available in the literature are analyzed to determine the optimal one for the test cases considered. The test systems used in this CEED problem are 3 unit system considering transmission loss and 13 unit system considering valve point effects. The leading requirement in both the test cases is to optimize the total cost, fuel cost and emission. The numerical and statistical results affirm the high degree of the solution founded by GOA and its superiority is compared with already existing algorithms employed in solving CEED problems

scholarly journals Dynamic Combined Economic Emission Dispatch Including Wind Generators by Real Coded Genetic Algorithm

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Genetic Algorithm ◽  
Comparative Analysis ◽  
Optimization Technique ◽  
Electric Power System ◽  
Fuel Cost ◽  
Renewable Source ◽  
Wind Generators ◽  
Real Coded Genetic Algorithm ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

With the growing environmental depletion, the shift in the focus towards minimizing the emissions of gases released in the conventional generators and further incorporation of a cleaner alternate renewable source of energy such as wind or solar to the existing system is of utmost importance. The research paper aims to build an environmentally resilient electric power system. Real coded genetic algorithm- powerful optimization technique is employed to solve the dynamic combined economic emission dispatch i.e. DCEED strategy for two proposed algorithm. The first proposed DCEED algorithm includes fuel cost of only conventional generators while in the second algorithm along with conventional generators, wind powered generators with varying power output characteristic is added. A comparative analysis of both the algorithms in terms of total combined cost, emission level and fuel cost is taken into account and it is observed that in spite of wind uncertainty the proposed method is more economical.

scholarly journals Implementation and Comparison of Particle Swarm Optimization and Genetic Algorithm Techniques in Combined Economic Emission Dispatch of an Independent Power Plant

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2037 ◽  
Author(s):  
Shahbaz Hussain ◽  
Mohammed Al-Hitmi ◽  
Salman Khaliq ◽  
Asif Hussain ◽  
Muhammad Asghar Saqib
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Power Plant ◽  
Particle Swarm ◽  
Computational Time ◽  
Fuel Cost ◽  
Swarm Optimization ◽  
Penalty Factor ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

This paper presents the optimization of fuel cost, emission of NOX, COX, and SOX gases caused by the generators in a thermal power plant using penalty factor approach. Practical constraints such as generator limits and power balance were considered. Two contemporary metaheuristic techniques, particle swarm optimization (PSO) and genetic algorithm (GA), have were simultaneously implemented for combined economic emission dispatch (CEED) of an independent power plant (IPP) situated in Pakistan for different load demands. The results are of great significance as the real data of an IPP is used and imply that the performance of PSO is better than that of GA in case of CEED for finding the optimal solution concerning fuel cost, emission, convergence characteristics, and computational time. The novelty of this work is the parallel implementation of PSO and GA techniques in MATLAB environment employed for the same systems. They were then compared in terms of convergence characteristics using 3D plots corresponding to fuel cost and gas emissions. These results are further validated by comparing the performance of both algorithms for CEED on IEEE 30 bus test bed.

scholarly journals Combined Economic Emission Dispatch with Environment-Based Demand Response Using WU-ABC Algorithm

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6450
Author(s):  
Ho-Sung Ryu ◽  
Mun-Kyeom Kim
Keyword(s):  
Demand Response ◽  
Test System ◽  
Optimal Operation ◽  
Pollutant Emissions ◽  
Superior Performance ◽  
Pollutant Emission ◽  
Abc Algorithm ◽  
Penalty Factor ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

Owing to the growing interest in environmental problems worldwide, it is essential to schedule power generation considering the effects of pollutants. To address this, we propose an optimal approach that solves the combined economic emission dispatch (CEED) with maximum emission constraints by considering demand response (DR) program. The CEED consists of the sum of operation costs for each generator and the pollutant emissions. An environment-based demand response (EBDR) program is used to implement pollutant emission reduction and facilitate economic improvement. Through the weighting update artificial bee colony (WU-ABC) algorithm, the penalty factor that determines the weighting of the two objective functions is adjusted, and an optimal operation solution for a microgrid (MG) is then determined to resolve the CEED problem. The effectiveness and applicability of the proposed approach are demonstrated via comparative analyses at a modified grid-connected MG test system. The results confirm that the proposed approach not only satisfies emission constraints but also ensures an economically superior performance compared to other approaches. These results present a useful solution for microgrid operators considered environment issues.

scholarly journals Optimasi Kombinasi Biaya Bahan Bakar dan Emisi Pembangkit Energi Listrik menggunakan Teknik Reduksi Tempat Kedudukan

2021 ◽  
Vol 9 (2) ◽  
pp. 318
Author(s):  
JANGKUNG RAHARJO
Keyword(s):  
Cost Savings ◽  
Reduction Technique ◽  
Jaya Algorithm ◽  
Energy Problem ◽  
Swarm Optimization ◽  
Area Reduction ◽  
Whale Optimization ◽  
Emission Dispatch ◽  
Reduction Cost ◽  
Economic Emission Dispatch

ABSTRAKDalam pengoperasian pembangkit energi listrik bukan saja untuk mendapatkan biaya yang minimal, namun juga meminimalkan emisi yang dihasilkan atau dikenal dengan Combined Economic Emission Dispatch (CEED), karena emisi merupakan bagian dari permasalahan energi. Makalah ini mengusulkan teknik reduksi tempat kedudukan untuk memecahkan masalah CEED. Prinsip dasar dari teknik ini adalah menebarkan sejumlah kandidat pada tempat kedudukan, S0 yang dibentuk dari limit daya generator, dan ditentukan sebuah kandidat terbaik. S0 diperkecil dan proses diulangi hingga didapatkan tempat kedudukan yang sangat kecil dimana kandidat terbaiknya dapat dianggap sebagai titik optimal. Teknik ini lebih akurat dibandingkan dengan metoda lain seperti Gradient Method (GM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), JAYA Algorithm dan Whale Optimization Algorithm (WOA). Hasilnya memberikan penghematan biaya tanpa melibatkan emisi masing-masing terhadap GM, ACO, PSO, WOA dan JAYA sebesar 9,24%, 3,91%, 0,56%, 0,47% dan 0,21%, serta bila melibatkan emisi sebesar 21,28%, 16,09%, 5,52%, 5,31% dan 5,04%.Kata kunci: CEED, reduksi tempat kedudukan, penghematan biaya, optimal, akurat. ABSTRACTIn an operating, generator units not only to get minimal costs but also to consider the emissions produced, known as the Combined Economic Emission Dispatch (CEED), because emission is part of the energy problem. This paper proposes a feasible area reduction technique for solving CEED problems. The basic principle of this technique is to spread number of candidates on a feasible area, S0 which is formed by generator limits from n generator units and the best candidate is determined. S0 is reduced and the process is repeated until a very small area is found, where the best candidate can be considered the solution. This technique is more accurate than other methods such as GM, ACO, PSO, JAYA Algorithm and WOA. The result provides cost savings without involving emission of GM, ACO, PSO, WOA and JAYA of 9.24%, 3.91%, 0.56%, 0.47% and 0.21% respectively, as well as when it involves emissions amounted to 21.28%, 16.09%, 5.52%, 5.31% and 5.04% respectively.Keywords: CEED, feasible area reduction, cost saving, optimal, accurate

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