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1

Optimizing the harmony search algorithm for combined heat and power economic dispatch in american english

Benayed F.Z., Abdelhakem-Koridak L., Bouadi A., Rahli M.

Journal of Power Technologies

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2023

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Vol. 103, nr 1

14--20

EN

Achieving optimal utilization of multiple combined heat and power (CHP) systems is a complex problem that requires powerful methods for resolution. This paper presents a harmony search (HS) algorithm to address the economic dispatch issue in CHP (CHPED ). The recently developed metaheuristic HS algorithm has been successfully employed in a wide range of optimization problems. The method is demonstrated through a test case from existing literature and a new one proposed by the authors. Numerical results indicate that the proposed algorithm can identify superior solutions compared to traditional methods, and that the Harmony Search algorithm can be effectively applied to CHPED-related problems.

2

Clustering and Classification based real time analysis of health monitoring and risk assessment in Wireless Body Sensor Networks

Alameen Abdalla, Gupta Ashu

Bio-Algorithms and Med-Systems

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2019

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Vol. 15, no. 4

art. no. 20190016

EN

Wireless body sensor networks (WBSNs) play a vital role in monitoring the health conditions of patients and are a low-cost solution for dealing with several healthcare applications. However, processing a large amount of data and making feasible decisions in emergency cases are the major challenges attributed to WBSNs. Thus, this paper addresses these challenges by designing a deep learning approach for health risk assessment by proposing fractional cat based salp swarm algorithm (FCSSA). At first, the WBSN nodes are utilized for sensing data from patient health records to acquire certain parameters for making the assessment. Based on the obtained parameters, WBSN nodes transmit the data to the target node. Here, the hybrid harmony search algorithm and particle swarm optimization (hybrid HSA-PSO) is used for determining the optimal cluster head. Then, the results produced by the hybrid HSA-PSO are given to the target node, in which the deep belief network (DBN) is used for classifying the health records for the health risk assessment. Here, the DBN is trained using the proposed FCSSA, which is developed by integrating fractional cat swarm optimization (FCSO) and salp swarm algorithm (SSA) for initiating the classification. The proposed FCSSA-based DBN shows better performance using metrics, namely accuracy, energy, and throughput with values 94.604, 0.145, and 0.058, respectively.

3

Optimal placement and sizing of Static Var Compensators in power systems using Improved Harmony Search Algorithm

Sirjani R., Mohamed A., Shareef H.

Przegląd Elektrotechniczny

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2011

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R. 87, nr 7

214-218

EN

This paper presents the application of the improved harmony search (IHS) algorithm for determining the optimal location and sizing of static Var compensator (SVC) to improve the voltage profile and reduce system power losses. A multi-criterion objective function comprising of both operational objectives and investment costs is considered. The results on the 57-bust test system showed that the IHS algorithm give lower power loss and better voltage improvement compared to the particle swarm optimization method in solving the SVC placement and sizing problem.

PL

Artykuł przedstawia zastosowanie algorytmu IHS (Improved harmony search) do określania optymalnej lokalizacji kompensatora mocy biernej. Rezultaty testów wykazały że algorytm zapenia mniejsze straty mocy oraz zniekształcenia w porównaniu do innych metod optymalizacji.

4

Harmony Search Algorithm to solve Dynamic Economic Environmental Dispatch (DEED)

Belmadani A., Benasla L., Rahli M.

Przegląd Elektrotechniczny

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2011

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R. 87, nr 9a

338-342

EN

This paper presents an application of Harmony Search algorithm (HSA) to solve the Dynamic Economic-Environmental Dispatch (DEED) problem under some equality and inequality constraints. The equality constraints reflect a real power balance, and the inequality constraint reflects the limits of real generation. The voltage levels and security are assumed to be constant. Dynamic Economic-Environmental Dispatch problem is obtained by considering both the economy and emission objectives. This bi-objective problem is converted into a single objective function using a price penalty factor. Harmony Search algorithm is tested on six generators system and its results are compared with the solutions obtained in paper of Keerati. The results are quite encouraging and useful in the economic emission environment.

PL

Zbadano zastosowanie algorytmu HSA do rozwiązania problemów dynamicznego rozsyłu energii. Uwzględniono realny balans mocy jak i realne ograniczenia. Algorytm przetestowano na sześciu systemach.

5

Reconstruction of the thermal conductivity coefficient by using the harmony search algorithm

Grzymkowski R., Hetmaniok E., Słota D., Zielonka A.

Journal of Achievements in Materials and Manufacturing Engineering

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2011

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Vol. 49, nr 2

299--304

EN

Purpose: of this paper: Aim of this paper is a presentation of the respectively new tool for solving the optimization problems, which is the Harmony Search algorithm in version slightly modified by the authors, used for identifying the thermal conductivity coefficient. Proposed approach is illustrated with an example confirming its usefulness for solving such kinds of problems. Design/methodology/approach: For solving the considered parametric inverse heat conduction problem the approach is applied in which the essential part consists in minimization of the functional representing the differences between the measurement values of temperature and approximate values calculated with the aid of finite difference method. For minimizing the functional the Harmony Search algorithm is used. Findings: The elaboration shows that approaches involving the algorithms of artificial intelligence for solving the inverse heat conduction problems of that kind are efficient and they ensure to receive satisfying results in shorter time in comparison with the classical procedures. Research limitations/implications: Specific properties of the heuristic algorithms require to execute the procedure several times and to average the obtained results because each running of the algorithm can give slightly different results. Each execution of the procedure means the solution of the direct problem associated with the considered inverse problem by using the finite difference method. Practical implications: In spite of the problem described above the approaches involving the heuristic algorithms of artificial intelligence are successful because they are respectively simple and easy to use and they give satisfying results after short time of working. Another advantage of using optimization algorithms of that kind is the fact that they do not need to satisfy any assumptions about the solved problem, oppositely to the classical optimization algorithms. Originality/value: Proposal of the original approach involving the heuristic optimization algorithm for solving the parametric inverse heat conduction problem is discussed in the paper.