In recent years, distributed generation, as clean natural energy generation and cogeneration system of high thermal efficiency, has increased due to the problems of global warming and exhaustion of fossil fuels. Many of the distributed generations are set up in the vicinity of the customer, with the advantage that this decreases transmission losses. However, output power generated from natural energy, such as wind power, photovoltaics, etc., which is distributed generation, is influenced by meteorological conditions. Therefore, when the distributed generation increases by conventional control techniques, it is expected that the voltage change of each node becomes a problem. Proposed in this paper is the optimal control of distribution voltage with coordination of distributed installations, such as the load ratio control transformer, step voltage regulator (SVR), shunt capacitor, shunt reactor, and static var compensator. In this research, SVR is assumed to be a model with tap changing where the signal is received from a central control unit. Moreover, the communication infrastructure in the supply of a distribution system is assumed to be widespread. The genetic algorithm is used to determine the operation of this control. In order to confirm the validity of the proposed method, simulations are carried out for a distribution network model with distributed generation (photovoltaic generation).

Optimal Distribution Voltage Control and Coordination With Distributed Generation

Distributed generators (DGs) such as fuel cells, solar cells, wind mills and micro gas turbines, etc. are going to be installed on the demand side of power systems. Such distributed generators can reduce distribution loss if they are placed appropriately in the distribution system. In this paper, a tabu search application for finding the optimal allocation of DGs from a viewpoint of loss minimization is illustrated. In other words, the authors discuss about an implementation method of tabu search to find how much distribution loss can be reduced if DGs are optimally allocated at the demand side of a power system. Namely, locations and discrete capacities of DGs to minimize the distribution loss are determined by nested use of the tabu search algorithm. Numerical examples are shown to demonstrate the method.

Application of tabu search to optimal placement of distributed generators

The problem of capacitor allocation for loss reduction in electric distribution systems has been extensively researched over the past several decades. This paper describes the evolution of the research and provides an evaluation of the practicality and accuracy of the capacitor placement algorithms in the literature. The intent of this paper is not to provide a complete survey of all the literature in capacitor allocation, but to provide researchers and utility engineers further insight into the choices of available capacitor allocation techniques and their respective merits and shortcomings. Furthermore, this paper serves as a useful and practical guideline to assist in the implementation of an appropriate capacitor allocation technique.

Classification of capacitor allocation techniques

This paper presents a fuzzy-GA method to resolve dispersed generator placement for distribution systems. The problem formulation considers an objective to reduce power loss costs of distribution systems and the constraints with the number or size of dispersed generators and the deviation of the bus voltage. The main idea of solving fuzzy nonlinear goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature and solve the problem using the proposed genetic algorithm without any transformation for this nonlinear problem to a linear model or other methods. Moreover, this algorithm proposes a satisfying method to solve the constrained multiple objective problem. Analyzing the results and updating the expected value of each objective function allows the dispatcher to obtain the compromised or satisfied solution efficiently.

Dispersed generator placement using fuzzy-GA in distribution systems

Cuckoo search algorithm for economic dispatch

A neural network for controlling shunt capacitor banks and feeder voltage regulators in electric distribution systems is presented. The objective of the neural controller is to minimize total I/sup 2/R losses and maintain all bus voltages within standard limits. The performance of the neural network for different input selections and training data is discussed and compared. Two different input selections are tried, one using the previous control states of the capacitors and regulator along with measured line flows and voltage which is equivalent to having feedback and the other with measured line flows and voltage without previous control settings. The results indicate that the neural net controller with feedback can outperform the one without. Also, proper selection of a training data set that adequately covers the operating space of the distribution system is important for achieving satisfactory performance with the neural controller. The neural controller is tested on a radially configured distribution system with 30 buses, 5 switchable capacitor banks and a nine tap line regulators to demonstrate the performance characteristics associated with these principles. Monte Carlo simulations show that a carefully designed and relatively compact neural network with a small but carefully developed training set can perform quite well under slight and extreme variation of loading conditions.

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Neural Networks for Combined Control of Capacitor Banks and Voltage Regulators in Distribution Systems

Three studies have examined the operational and planning problems associated with connecting small power sources to an electric distribution system. In one study [ 6], the harmonic distortion produced by a subdivision of PV arrays connected through line-commutated inverters was simulated. A second study [1,2,3] exami ned the protection and safety problems associated with the operation of small ac generators and dc-to-ac inverters. A third study [11] assessed the the effects of dispersed sources on distribution planning and design. The purpose of the studies was to determine the adequacy of the electric utility industryl traditional practices, hardware, and design for the operation of dispersed power sources on electric distribution systems. The purpose of this paper is to summarize the important results of these studies and related studies, give recommendations for accommodating this new technology, and identify areas needing further research.

Operational and Design Considerations for Electric Distribution Systems with Dispersed Storage and Generation (DSG)

Integrating Dispersed Storage and Generation with an Automated Distribution System

This paper formulates a methodology to aid in deciding on the appropriate quality and quantity of protection equipment required for a small electric power producing device, known in the industry as dispersed storage and generation (DSG). In this methodology, a discrete state-space model of the response of both the utility's and DSG's protection equipment to shunt and series faults on an electric distribution feeder is developed. The parameters of the model are linked to the component reliabilities of the protection schemes and the specific characteristics of the distribution system. The mathematics of semi-Markov theory are used in the methodology to calculate the expected annual damage costs for various protection schemes. The total costs are calculated for alternative protection schemes by considering equipment damaqe, repair time, lost revenue, outage costs, and time spent in different operating states during the hazardous conditions. This methodology is useful to electric utilities, small power producers, and regulatory bodies who must make decisions regarding the adequacy as well as the cost-effectiveness of protection requirements for DSG installations.

D. T. Rizy

Papers

Neural Networks for Combined Control of Capacitor Banks and Voltage Regulators in Distribution Systems

Operational and Design Considerations for Electric Distribution Systems with Dispersed Storage and Generation (DSG)

Integrating Dispersed Storage and Generation with an Automated Distribution System

A Decision Analysis Model to Determine the Appropriate Level of Protection for the Small Power Producer/Utility Interconnection