Optimal Allocation and Sizing of Multi DG Units Including Different Load Model Using Evolutionary Programming

In this paper, an efficient method is proposed for optimal allocation and sizing of Thyristor Controlled Series Compensator (TCSC) to improve the technical and economic indices of a power network with deterministic and stochastic load models. First, the compensator allocation is done in the transmission system with the deterministic load model. After calculating the technical and economic indices of the network in the presence of a deterministic load model, the proposed method is applied to the system with a stochastic load model. The two-point estimation method is used for simulating the stochastic conditions. The indices of voltage deviation and economics of the system are optimized for selecting the optimal location and size of TCSCs. The economic index comprises loss cost, cost of the produced active power of generators and also the costs of installation, operation and maintenance of TCSCs. The multi-objective particle swarm optimization (MOPSO) is utilized to optimize the objective functions. After the multi-objective optimization, the fuzzy decision method is employed to extract one of the Pareto-optimal solutions as the best compromise one. For evaluating the proposed method, comprehensive simulations have been performed on the IEEE 39-bus network by using MATLAB/Matpower software. The simulation results clearly prove the remarkable performance of the proposed method in improving the technical and economic indices of the system.

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Effect of Load Model Using Ranking Identification Technique for Multi Type DG Incorporating Embedded Meta EP-Firefly Algorithm

MATEC Web of Conferences ◽

10.1051/matecconf/201815001014 ◽

2018 ◽

Vol 150 ◽

pp. 01014

Author(s):

Siti Rafidah Abdul Rahim ◽

Ismail Musirin ◽

Muhammad Murtadha Othman ◽

Muhamad Hatta Hussain

Keyword(s):

Power System ◽

Distributed Generation ◽

Distribution System ◽

Firefly Algorithm ◽

Optimal Allocation ◽

Load Factor ◽

Load Model ◽

Load Models ◽

Voltage Dependent ◽

Identification Technique

This paper presents the effect of load model prior to the distributed generation (DG) planning in distribution system. In achieving optimal allocation and placement of DG, a ranking identification technique was proposed in order to study the DG planning using pre-developed Embedded Meta Evolutionary Programming–Firefly Algorithm. The aim of this study is to analyze the effect of different type of DG in order to reduce the total losses considering load factor. To realize the effectiveness of the proposed technique, the IEEE 33 bus test systems was utilized as the test specimen. In this study, the proposed techniques were used to determine the DG sizing and the suitable location for DG planning. The results produced are utilized for the optimization process of DG for the benefit of power system operators and planners in the utility. The power system planner can choose the suitable size and location from the result obtained in this study with the appropriate company’s budget. The modeling of voltage dependent loads has been presented and the results show the voltage dependent load models have a significant effect on total losses of a distribution system for different DG type.

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