Adisa A. Jimoh

Reconfiguration and Load Balancing in the LV and MV Distribution Networks for Optimal Performance

To get the distribution network to operate at its optimum performance in an automated distribution system reconfiguration was been proposed and researched. Considering, however, that optimum performance implies minimum loss, no overloading of transformers and cables, correct voltage profile, and absence of phase voltage and current imbalances, network reconfiguration alone is insufficient. It has to be complemented with techniques for phase rearrangement between the distribution transformer banks and the specific primary feeder with a radial structure and dynamic phase and load balancing along a feeder with a radial structure. This paper contributes such a technique at the low-voltage and medium-voltage levels of a distribution network simultaneously with reconfiguration at both levels. While the neural network is adopted for the network reconfiguration problem, this paper introduces a heuristic method for the phase balancing/loss minimization problem. A comparison of the heuristic algorithm with that of the neural network shows the former to be more robust. The approach proposed here, therefore for the combined problem, uses the neural network in conjunction with a heuristic method which enables different reconfiguration switches to be turned on/off and connected consumers to be switched between different phases to keep the phases balanced. An application example of the proposed method using real data is presented.

Feasibility study of a hybrid PV-micro hydro system for rural electrification

The present study investigates the possibility of using a stand-alone solar/micro hydro hybrid power system for low-cost electricity production which can satisfy the energy load requirements of a typical remote and isolated rural area. In this context, the optimal dimensions to improve the technical and economical performances of the hybrid system are determined according to the load energy requirements, the solar and water resources and the importance of supply continuity. The proposed systems installation and operating costs are simulated using the Hybrid Optimization Model for Electric Renewable (HOMER) with the stream flow, the solar radiation and the system components costs as inputs; and then compared with those of other supply options such as grid extension and diesel generation.

Economic and environmental analysis of micro hydropower system for rural power supply

This paper discusses the advantages of using renewable energy sources in the architecture of an off-grid hybrid power system in rural areas. The studied system is composed of a diesel generator to which a micro hydropower plant is added. Simulations using the Hybrid Optimization Model for Electric Renewable (HOMER) are performed for given annual values of hydro resources, power demands and hybrid system component costs. The results highlight the cost-effectiveness character and the reduction of gas pollutant emissions achieved by using such a system rather than a diesel generator to supply the same load.

Particle swarm optimization for power system state estimation

Abstract The electrical network measurements are usually sent to the control centers using specific communication protocols. However, these measurements contain uncertainties due to the meters and communication errors (noise), incomplete metering or unavailability of some of these measurements. The aim of state estimation is to estimate the state variables of the power system by minimizing all measurement errors available at the control center. In the past, many traditional algorithms, based on gradient approach, have been used for this purpose. This paper discusses the application of an artificial intelligence (AI) algorithm, the particle swarm optimization (PSO), to solve the state estimation problem within a power system. Two objective functions are formulated: the weighted least square (WLS) and weighted least absolute value (WLAV). The effectiveness of PSO over another AI optimization algorithm, genetic algorithm (GA), is shown by comparing both two solutions to the true state variable values obtained using Newton–Raphson (NR) algorithm.

Optimal location of network devices using a novel inherent network topology based technique

A new approach for the identification of the best node for the injection of bulk power is proposed. The proposed approach can also be used to determine the minimum numbers of static var compensator devices that can ensure the operation of power system network within the specified voltage limits. The proposed approach is based on the inherent topology of networks and application of singular value decomposition technique. The results of numerical examples show that buses with the smallest singular values can serve as indicators of the best locations for static var compensators and best node for injection of bulk power without the need for additional transmission lines.

Viability and economic analysis of wind energy resource for power generation in Johannesburg, South Africa

In this study, wind characteristics and wind power potential of Johannesburg are investigated using 5-min average time series wind speed collected between 2005 and 2009 at anemometer height of 10 m. The statistical distribution that best fits the empirical wind speed data at the site of study is first determined based on the coefficient of determination and root mean square error criteria. The statistical parameters and wind power density based on this model are estimated for different months of the year using standard deviation method. Economic analyses of some wind turbines are also carried out. Some of the key results show that the site is only suitable for small wind turbines in a standalone application. A 10 kW wind turbine with cut-in wind speed of 3.5 m/s, rated wind speed of 9 m/s, and cut-out wind speed of 25 m/s seems most appropriate in Johannesburg with the lowest cost that varies from 0.25 to 0.33

The ieee 34 node radial test feeder as a simulation testbench for Distributed Generation

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Voltage profile improvement based on network structural characteristics

The advent of distributed generation introduces new challenges and possibilities of controlling reactive power and regulating voltage in distribution systems. In addition, dynamic behavior of the distribution system is influenced by the presence of Distributed Generation (DG). As a result, the impact of DG on distribution system radial feeders and laterals needs to be evaluated in terms of steady state normal and transient conditions before implementation. Several computer programs exist to carry out such simulations and this paper focuses on DigSILENT PowerFactory. Power Factory provides steady state solutions for balanced and unbalanced load flow for both transmission and distribution networks, short circuit calculations and, it also provides dynamic solutions for transient studies. The main objective of this work is to establish a test bench in PowerFactory and report steady state results. The simulation test bench is to be used in ongoing research work for analysis of the impact of various forms of DG on distribution networks. The IEEE 34 Node test feeder is modeled and results are compared with those of the IEEE distribution system analysis subcommittee.

A Statistical Analysis of Wind Distribution and Wind Power Potential in the Coastal Region of South Africa

This paper demonstrates voltage profile improvement by partitioning the Y-admittance and the application of circuit theory on power system networks. The partitioned Y-admittance matrix and eigenvalue decomposition technique were used to identify the suitable locations for reactive power compensators. The proposed approach was applied to the 40-bus Southwest England network and the results were compared with the classical Q-V sensitivity approach. The proposed approach improves the overall voltage profile towards the nominal voltage limit.

Classification of networks based on inherent structural characteristics

This article investigates the wind characteristics and the wind power potential for electricity generation in the coastal regions of South Africa through the analysis of local wind regime of ten different sites. The data used consist of 10-min average time series wind speeds, temperatures, and standard deviation measured at anemometer height of 20 and 60 m for a period of 1 year. First, the statistical distribution model that best fits the empirical wind speed data in the areas of study is determined based on the coefficient of determination and root mean square error, which are used to test the goodness of fit. The parameters and the wind power density based on this model are estimated for each of the months and season of the year. For a realistic result in estimating the power density, the stochastic nature of the site air density based on the local temperature and the site altitude above the sea level is taken into consideration. The diurnal (day and night), electricity peak periods wind characteristic, and the turbulence intensity of the sites are calculated. The optimum wind speed, most probable wind speed and shear exponential which are important pieces of information in the selection of wind turbines are evaluated. Some of the key results show that at 60 m anemometer height, site WM05 has an exceptional wind power potential with annual power density of 694 W/m2, while site WM02 shows a poor wind power potential with annual power density of 216.29 W/m2.