Optimum Allocation Of Capacitor And DG In MV Distribution Network Using PSO And OpenDSS

The optimum capacitor and distributed generation (DG) allocation in medium voltage (MV) distribution network utilizing particle swarm optimization (PSO) for selecting the optimum size and placement of (DG) units can significantly affect the distribution network. Capacitor installation is a standard method for reactive power compensation within a distribution network. The placement and sizing of the capacitor have been optimized in the distribution network for a number of capacitors with the objective of the voltage profile improvement and power loss minimization. Maximum and minimum bus voltage and possible maximum capacitor size were the constraints of the optimum capacitor and sizing problems, which take into account as a penalty factor (PF) within the objective function (OF) and the allocation of DG units. To solve the obtained OF, PSO and Open DSS engines were used in this research to analyse power flow results that obtained from the standard IEEE14 Bus system. The performance evaluation of PSO model was carried out by showing the results that the PSO algorithm. PSO can obtain the optimal solution of the size and location also find the optimum DG size for the loss minimization and voltage profile improvement compared to the standard case without DG and capacitor compensation. All simulations had been performed using MATLAB software

High PV Penetration Impact on European-based LV Residential Network

The impact of high PV penetration into the grid particularly at the distribution side has been extensively studied. However, most of the available research focuses on North American style systems. This project aims to investigate the effect of high PV penetration at a residential area in a European-based distribution network, which is electricity supply system Malaysia is based on. The modeling is done using OpenDSS while the network model used is the IEEE European Low Voltage Test Feeder which consists of 55 loads representing a generic housing area. Each load point is then equipped with a 4 kW PV system-representing a typical size for a house installation. PV output variability is then introduced into the modeling using two sample days of actual irradiance variability obtained from UTeM Malaysia; one for clear day and another for a high variability day. Voltage unbalance, voltage rise and reverse power flow were analyzed. One significant finding of this project is that voltage rise exceeds the standard of 1.05 pu during noon. Besides that, the high variability days significantly affect the mitigation measures required to manage reverse power flow

Using Particle Swarm Optimization Algorithm in the Distribution System Planning

Technology advancement, the drive to reduce environmental pollution and energy security concern, have led to an increase in the use of Distributed Generations (DGs). One of the important aspects of the power system is the optimal operation of distribution networks. Therefore, the objective of this paper is to determine the possible solution for optimal operation of distribution networks which takes into account the impact of DG. Since the optimal operation of distribution networks is an optimization problem with discrete and continuous variables, it can be introduced as an integer problem that can be formulated using the metaheuristic approach. This paper utilizes the Particle Swarm Optimization (PSO) algorithm to solve the distribution planning problem with DG. In addition, a case study on IEEE 34 bus system has been carried out to demonstrate the effectiveness of the PSO algorithm with regards to Genetic Algorithm (GA). Results indicate that PSO have better performance over the GA in terms of cost of losses minimization and convergence time. Future work should consider to minimize the overall network cost simultaneously that takes into account the DG investment cost, cost of losses and maintenance cost

IoT-based electricity energy monitoring system at Universiti Teknikal Malaysia Melaka

Electricity bill is one of the major operating expenses in most of the commercial buildings and industrial plants. Thus, the buildings’ energy management system is an essential element that should be utilized to optimize the energy usage and hence, contributes to carbon footprint reduction. To achieve this, one needs to first understand how the energy is being used in the buildings before any saving measures can be identified and proposed. Therefore, this paper presents the development of an Internet of Things (IoT) enabled device that can communicate with different digital energy meters through modbus protocol. The prototype has been successfully installed in three locations in the main campus of Universiti Teknikal Malaysia Melaka (UTeM). The proposed solution enables the campus-wide energy usage to be monitored and stored efficiently and economically as opposed to the capital-intensive SCADA system

Optimal Capacitor Allocation in Distribution System using Particle Swarm Optimization

In distribution networks, capacitor installation is one of the commonly used methods for reactive power compensation. Capacitor placement and sizing in power system can be applied in multiple objectives and reasons. In this paper, the optimum capacitor placement and sizing has been applied in the distribution network in terms of power losses minimization and voltage profile improvement. The maximum and minimum bus voltage and maximum possible capacitor size are the constraints of optimum capacitor placement and sizing problem which considered as a penalty factor in the objective function. In order to solve the obtained objective function, the Particle Swarm Optimization (PSO) is utilizes to find the best possible capacitor placement and size. The OpenDSS software has been utilized to solve the power flow through Matlab coding interface. To validate the functionality of the proposed method, the IEEE 13-bus test system is implemented and the obtained results have been compared with IEEE standard case and without capacitor case. The result shows that the proposed algorithm is more cost effective and has lower power losses compare to the IEEE standard case. In addition, the voltage profile has been improved, accordingly

Optimum Feeder Routing and Distribution Substation Placement and Sizing using PSO and MST

A long term distribution network planning consists of several complexity aspects due to the multiple decision variables in objective functions. Optimum placement of distribution substations and determination of their sizing and feeder routing is one of major issues of distribution network planning. This paper proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified MST. The proposed algorithm has been evaluated on the distribution network case with 500 consumers which are consisting of residential and commercial loads. The test network is generated by fractal based distribution network generation model software tool. The results indicate the proposed algorithm has been succeeded to find the reasonable placement and sizing of distributed generation with adequate feeder path

Reactive Power Imbalance Method for Islanding Detection in Micro-Grid Operation

Micro-grids usage among consumers has become a new attraction due their several of advantage. Its major function is to ensure the stable operation during the fault and a variety of utility grid disruption. Since the utilization of micro-grid become common, the correct application and operation of micro-grid is importance and significant. One of the main challenges in micro-grids operation is islanding detection methods. There are several methods that are handles the islanding detection that each one have advantage and some disadvantage. This paper presents and investigates the Reactive Power Imbalance Method for islanding detection. The passive algorithm implements in this paper due to the low cost operation, however it got the higher non-detection zone (NDZ) and slower response time compare some active methods. The micro-grid simulation is modeled in Matlab/Simulink program and the results of the monitoring are discussed as well. As the result, the performance of the Reactive Power Imbalance method for the islanding detection state is compared with the simulation model without control algorithm. Finally, the micro-grid model capability with control algorithm is shown in order to meet the load demand

AN INVESTIGATION ON PARTICLE SWARM OPTIMIZATION ALGORITHM FOR DISTRIBUTION SYSTEM PLANNING WITH DISTRIBUTED GENERATION

Nowadays, technology advancement, the drive to reduce environmental pollution and power system restructuring have caused the increase in the utilization of Distributed Generations (DGs). One of the important aspects of the power system is the optimal operation of distribution networks. Therefore, the main objective of this paper is to investigate and to find the best solution for optimal operation of distribution networks which takes into account the impact of DG. Since optimal operation of distribution networks is an optimization problem with discrete and continuous variables, so it can be introduced as an integer problem that can be formulated by metaheuristic. In this regards, this paper presents the Particle Swarm Optimization (PSO) algorithm to solve the distribution planning problem with DG. In addition, case study on IEEE 34 buses system have been carried out to demonstrate the effectiveness of the PSO algorithm. And finally the performance of PSO algorithm is compared with Genetic Algorithm (GA)

AN INVESTIGATION ON PARTICLE SWARM OPTIMIZATION ALGORITHM FOR DISTRIBUTION SYSTEM PLANNING WITH DISTRIBUTED GENERATION

Nowadays, technology advancement, the drive to reduce environmental pollution and power system restructuring have caused the increase in the utilization of Distributed Generations (DGs). One of the important aspects of the power system is the optimal operation of distribution networks. Therefore, the main objective of this paper is to investigate and to find the best solution for optimal operation of distribution networks which takes into account the impact of DG. Since optimal operation of distribution networks is an optimization problem with discrete and continuous variables, so it can be introduced as an integer problem that can be formulated by metaheuristic. In this regards, this paper presents the Particle Swarm Optimization (PSO) algorithm to solve the distribution planning problem with DG. In addition, case study on IEEE 34 buses system have been carried out to demonstrate the effectiveness of the PSO algorithm. And finally the performance of PSO algorithm is compared with Genetic Algorithm (GA)

Design Of Battery Storage System For Malaysia Low Voltage Distribution Network With The Presence Of Residential Solar Photovoltaic System

The recent proliferation of residential solar photovoltaic systems has prompted several technical challenges to the operation of low voltage (LV) distribution networks. More specifically, the mismatch of the solar generation and demand profiles, particularly during the midday when the demand is low and solar generation is high, can lead to network overvoltages and increased network losses. In addition, the solar photovoltaic system is not able to reduce the system’s maximum demand, given the residential LV network would normally have an evening peak when the sun goes down. In this regard, this paper examines two different control strategies in designing the battery energy storage system. One aims to eliminate reverse flow caused by the surplus solar energy and the other aims for peak demand reductio