Multi-Objective Squirrel Search Algorithm for Multi-Area Economic Environmental Dispatch With Multiple Fuels and Valve Point Effects

Sakthivel, V.; Goh, Hui Hwang; Subramanian, S.; Sathya, P. D.; Rahim, Sharul Kamal Abdul

doi:10.1109/access.2020.3046257

Cited by 12 publications

(10 citation statements)

References 32 publications

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“…In order to further evaluate the robustness of the proposed ChMODE for solving the nonconvex EEDP, seven well-known multiobjective optimization methods, including MOCDOA [31], MODE [69], MOPSO [31], NSGA-II [31], MOSSA [75], PESA-II [31], and NSPSO [76], are adopted and compared with ChMODE. In this subsection, the performance of the ChMODE algorithm, when looking for the extreme points of the PF, is compared with MODE [50] for Cases 1, 2, and 3.…”

Section: Robustness Analysismentioning

confidence: 99%

A Hybrid Chaotic-Based Multiobjective Differential Evolution Technique for Economic Emission Dispatch Problem

2023

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The economic emission dispatch problem (EEDP) is a nonconvex and nonsmooth multiobjective optimization problem in the power system field. Generally, fuel cost and total emissions of harmful gases are the problem objective functions. The EEDP decision variables are output powers of thermal generating units (TGUs). To make the EEDP problem more practical, valve point loading effects (VPLEs), prohibited operation zones (POZs), and power balance constraints should be included in the problem constraints. In order to solve this complex and constrained EEDP, a new multiobjective optimization technique combining the differential evolution (DE) algorithm and chaos theory is proposed in this study. In this new multiobjective optimization technique, a nondomination sorting principle and a crowding distance calculation are employed to extract an accurate Pareto front. To avoid being trapped in local optima and enhance the conventional DE algorithm, two different chaotic maps are used in its initialization, crossover, and mutation phases instead of random numbers. To overcome difficulties caused by the equality constraint describing the power balance constraint, a slack TGU is defined to compensate for the gap between the total generation and the sum of the system load and total power losses. Then, the optimal power outputs of all thermal units except the slack unit are determined by the suggested optimization technique. To assess the effectiveness and applicability of the proposed method for solving the EEDP, the six-unit and ten-unit systems are used. Moreover, obtained results are compared with other new optimization techniques already developed and tested for the same purpose. The superior performance of the ChMODE is also evaluated by using various metrics such as inverted generational distance (IGD), hyper-volume (HV), spacing metric (SM), and the average satisfactory degree (ASD).

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Section: Robustness Analysismentioning

confidence: 99%

A Hybrid Chaotic-Based Multiobjective Differential Evolution Technique for Economic Emission Dispatch Problem

2023

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“…Multi-objective grey prediction evolution algorithm has adopted two learning processes to update the uniformity and diversity of the optimal solutions of economic and environmental dispatch [34]. The proposed algorithm is a combination of squirrel search algorithm and Pareto dominance theory, which has been applied to minimize total fuel cost and emission of pollutants [5]. An algorithm inspired by kernel tricks has been proposed and implemented to solve the multi-objective optimization problem along with weighed sum and Newton method [35].…”

Section: Kho-kho Optimization Technique Has Been Proposedmentioning

confidence: 99%

“…The conflicting and non-commeasurable nature of fuel cost and pollutant's emission are considered as the objectives of EEPD. The objectives are to optimize the power generated by thermal power generating units through minimizing the fuel cost and pollutant emission, simultaneously [5]. Therefore, to fulfil the future power demand of different consumers, more specific research is needed for best technical, economic and environmental conditions.…”

mentioning

confidence: 99%

Hybrid krill herd optimizer for thermal power scheduling problem

Kaur¹,

Singh²,

Dhillon³

2021

IJATEE

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The active world is changing each and every day with the advancement of technology and its growing use in daily life, which in turns increases the use of electricity. To fulfil this increase in electricity demand, the electric power system is becoming more complex. The effective functioning of electric power system includes the satisfaction of its consumers with continuous and qualitative service of power supply.

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“…NSGA-III was tested on IEEE 30 to demonstrate its potential. Sakthivel et al [26] established multi-area economic environmental dispatch (MAEED) to reduce fuel cost and pollutant emissions with tie-line, valve point loading, multi-fuel, and power balancing restrictions. MAEED should use multi-objective squirrel search.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective economic load dispatch using hybrid NSGA-II and PVDE techniques

Chandrashekhar,

Dhal

2024

IJPEDS

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Over decades, numerous methods have been used to optimize objective functions. Where cost and emissions clash. The improved non-dominated sorting genetic algorithm (NSGA-II) employs elitism to discover the optimum value and speed convergence in multi-objective optimization problems. Population variant differential evolution algorithm alters differential evolution (DE). The main distinction between DE and population variant differential evolution algorithm (PVDE) is population replenishment. NSGA-II and PVDE are combined in the suggested hybrid approach. The hybrid technique solves multi-objective optimization problems efficiently by combining two or more methods. The hybrid technique solves multi-objective optimization problems well. This optimization problem pits cost vs pollution. The hybrid approach exposes half the population to the NSGA-II algorithm and half to the PVDE algorithm. In optimization problems with opposing aims, such as minimizing costs and emissions, a hybrid technique is utilized to find the optimal solution. Elitist diversity-preserving strategies avoid optimization issues becoming converging too soon. A 10-generator IEEE 39 bus test system was validated using this method. The hybrid NSGA-II and PVDE methodology achieves global optimal solutions with more durability, simplicity, and optimization performance than existing methods.

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Multi-Objective Squirrel Search Algorithm for Multi-Area Economic Environmental Dispatch With Multiple Fuels and Valve Point Effects

Cited by 12 publications

References 32 publications

A Hybrid Chaotic-Based Multiobjective Differential Evolution Technique for Economic Emission Dispatch Problem

A Hybrid Chaotic-Based Multiobjective Differential Evolution Technique for Economic Emission Dispatch Problem

Hybrid krill herd optimizer for thermal power scheduling problem

Multi-objective economic load dispatch using hybrid NSGA-II and PVDE techniques

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