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Abstract

Department of Electrical Engineering, Anna University Regional Centre, Coimbatore, India This paper presents a new approach to solve economic load dispatch (ELD) problem in thermal units with non-convex cost functions using differential evolution technique (DE). In practical ELD problem, the fuel cost function is highly non linear due to inclusion of real time constraints such as valve point loading, prohibited operating zones and network transmission losses. This makes the traditional methods fail in finding the optimum solution. The DE algorithm is an evolutionary algorithm with less stochastic approach to problem solving than classical evolutionary algorithms.DE have the potential of simple in structure, fast convergence property and quality of solution. This paper presents a combination of DE and variable neighborhood search (VNS) to improve the quality of solution and convergence speed. Differential evolution (DE) is first introduced to find the locality of the solution, and then VNS is applied to tune the solution. To validate the DE-VNS method, it is applied to four test systems with non-smooth cost functions. The effectiveness of the DE-VNS over other techniques is shown in general.

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Authors and Affiliations

J. Jasper
T. Aruldoss Albert Victoire
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Abstract

This paper proposes a fair calculation approach for the cost and emission of generators. Generators also have reactive power requirements along with the active power demand to meet up the total power demand. In this paper, firstly the reactive power is calculated considering the random active power operating points on the capability curve of a generator then the cost for reactive power generation as well as emission are calculated. In order to develop the mathematical function for the reactive power cost and reactive power emission, a curve-fitting technique is applied, which gives the generalised reactive power cost and reactive power emission functions. At the end, the problem is formulated as a multiobjective problem, considering conflicting objectives such as combined active- reactive economic dispatch and combined active-reactive emission dispatch. The problem is converted from the multiobjective load dispatch problem (MOLDP) into a scalar problem, using the weighting method and the best compromised solution has been calculated using the particle swarmoptimization (PSO) technique.Afuzzy cardinal method has been applied to choose the best solution. In order to demonstrate the efficiency of developed functions the proposed method is applied on a 3 generator unit system and a 10 generator unit system, the results obtained show its validity and effectiveness.

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Authors and Affiliations

Harinder Pal Singh
Yadwinder Singh Brar
D.P. Kothari
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Abstract

Economic Load Dispatch (ELD) is utilized in finding the optimal combination of the real power generation that minimizes total generation cost, yet satisfying all equality and inequality constraints. It plays a significant role in planning and operating power systems with several generating stations. For simplicity, the cost function of each generating unit has been approximated by a single quadratic function. ELD is a subproblem of unit commitment and a nonlinear optimization problem. Many soft computing optimization methods have been developed in the recent past to solve ELD problems. In this paper, the most recently developed population-based optimization called the Salp Swarm Algorithm (SSA) has been utilized to solve the ELD problem. The results for the ELD problem have been verified by applying it to a standard 6-generator system with and without due consideration of transmission losses. The finally obtained results using the SSA are compared to that with the Particle Swarm Optimization (PSO) algorithm. It has been observed that the obtained results using the SSA are quite encouraging.
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Authors and Affiliations

Ramesh Devarapalli
1
ORCID: ORCID
Nikhil Kumar Sinha
1
ORCID: ORCID
Bathina Venkateswara Rao
2
ORCID: ORCID
Łukasz Knypinski
3
ORCID: ORCID
Naraharisetti Jaya Naga Lakshmi
4
ORCID: ORCID
Fausto Pedro García Márquez
5
ORCID: ORCID

  1. Department of EE, B. I. T. Sindri, Dhanbad, Jharkhand – 828123, India
  2. Department of EEE, V R Siddhartha Engineering College (Autonomous), Vijayawada-520007, A.P., India
  3. Poznan University of Technology, Poland
  4. SR Engineering College: Warangal, Telangana, India
  5. Ingenium Research Group, University of Castilla-La Mancha, Spain

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