No abstract

<p>Voltage profile and power losses on the distribution system is a function of real and imaginary power loading condition. This can be effectively managed through the controlled real and reactive power flow by optimal placement of capacitor banks (CB) and distributed generators (DG). This paper presents adaptive Particle Swarm Optimization (MPSO) to efficiently tackle the problem of simultaneous allocation of DG and CB in radial distribution system to revamp voltage magnitude and reduce power losses. The modification to the conventional PSO was achieved by replacing the inertial weight equation (W) in the velocity update equation base on the particle best experience in the previous iteration. The inertial weight equation is designed to vary with respect to the iteration value in the algorithm. The proposed method was investigated on IEEE 30-bus, 33-bus and 69-bus test distribution systems. The results shows a significant improvement in the rate of convergence of APSO, improved voltage profile and loss reduction.</p>

This study investigates and compares the cost of generating electricity from petrol and liquified petroleum gas (LPG) gas using a 2.5 kVA, 50Hz Elepaq generator. It also develops mathematical models that can be used to predict important parameters of the generator The generator is connected with a multi-fuel carburetor in the experimental setup, allowing both fuel sources to be fed alternatively. The electric bulbs of different ratings were connected and varied as load. The generator was first run using petrol. The time used to exhaust half litres of petrol was recorded. It was then run with LPG for a period equal to the time of run on petrol, taking note of the mass of LPG consumed. A cost comparison was carried out and mathematical models were developed for both fuels usage using MATLAB “polyfit” command. The results show that with less or equal 1350W connection of purely resistive load. It is more economical to run the generator using LPG. However, at any load beyond 1350 W, it is economical to run the generator using petrol. The two models developed best fit the experimental results obtained with a correlation of 0.9869 and 0.9962.

Summary Conventionally, voltage profile are regulated by controllers that are not operational flexible to the system dynamism and challenges offered by the integration of renewable energy sources. Consequently, there is a need for the adaptive coordinating mechanism as an interface between the passive network and the new active network. This will provide a platform for the smooth integration of distributed energy resources in most developing countries where traditional network is still operational. This paper proposes an algorithm for real‐time multiperiod adaptive compensation of network reactive power support based on hierarchical structure and decentralized layered multiagent system voltage coordinating scheme. A multiperiod voltage control algorithm replicates the daily load flow evaluation aiming at ameliorating voltage fluctuation over a 24‐hour simulation period. The algorithm applies the decentralized voltage control mechanism to monitor the network parameters and dynamically evaluate the capacity of the capacitor banks (CBs) to be injected for voltage compensation. This mitigates the challenges associated with under and over reactive power compensation experienced in the day‐ahead programming and manual switching operation. The algorithm works in conjunction with an on‐load tap changing transformer (OLTC) and energy storage system (ESS). The ESS complements the OLTC during switching delay, dip in its output root mean square and voltage fluctuation as network loading condition varies. The effectiveness of the proposed method is verified on standard IEEE 33 and 118‐bus distribution systems. The results show an improved voltage performance and reduction in stress/complexity associated with load and renewable generation forecast in manual switching operations.