Siti Rafidah Abdul Rahim
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Preferred name
Siti Rafidah Abdul Rahim
Official Name
Siti Rafidah, Abdul Rahim
Alternative Name
Abdul Rahim, Siti Rafidah
Rahim, S. R.
Rahim, S.R.A
Abdul Rahim, S.R.
Rahim, S.R. Abd
Main Affiliation
Scopus Author ID
11639107900
Researcher ID
E-5412-2011

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Integrated clustering development using embedded meta evolutionary-firefly algorithm technique for DG planning

2020-12-01 , Siti Rafidah Abdul Rahim , Musirin I. , Othman M.M. , Muhamad Hatta Hussain , Syahrul Ashikin Azmi

Recent trend changes have created opportunities to achieve numerous technological innovations including the use of distributed generation (DG) to achieve different advantages. A precise evaluation of energy losses is expanding rapidly when DG is connected to the electricity sector due to developments such as increased competition and real time pricing. Nevertheless, non-optimal DG installation either in the form of DG locations and sizing will lead to possible under-compensation or over-compensation phenomena. The integrated clustering resulted from the pre-developed Embedded Meta Evolutionary Programming-Firefly Algorithm (EMEFA) has been used to ensure the optimum allocation and placement of DG. The study also considers the different types of DG. The aim of the technique is to consider the computational time of the optimization process for DG planning in achieving the minimal total loss. Two test systems have been used as test specimens to achieve the efficacy of the proposed technique. In this study, the techniques proposed were used to establish the DG size and the appropriate place for DG planning. The results for total losses and minimum voltage for the system were recorded from the simulation. The result in this study will be compared with the ranking identification technique to ensure the capability of this technique. The power system planner can adopt the suitable sizes and locations from the obtained result for the planning of utility in term of economic and geographical consideration.

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Cost of energy losses analysis using a hybrid evolutionary programming-firefly algorithm for distributed generation installation

2022 , Noor Najwa Husnaini Mohammad Husni , Siti Rafidah Abdul Rahim , Mohd Rafi Adzman , Muhammad Hatta Hussain , Ismail Musirin

This paper presents the Hybrid Evolutionary Programming-Firefly Algorithm (EPFA) technique for the cost of energy losses analysis of distributed generation (DG). In this study, EPFA is developed to determine the optimal size of DG while considering the system’s energy losses. EPFA is developed based on embedded Firefly Algorithm (FA) properties into the classical EP technique. The objective of this study was to reduce the cost of energy losses while increasing the voltage profile and minimizing distribution system losses between the different operational strategies and types of DG. In this study, the analysis was done by considering DG type 1 and DG type 2. The proposed technique was tested using the IEEE 69-bus test system. In terms of economic concerns, power system planners can use the information acquired for utility planning to determine the right location and capacity of DG. Finally, the proposed method can determine the appropriate DG sizing while reducing the cost of energy losses and total losses in the system, based on the simulation results.

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