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Problems in the supply of electrical energy affect economic and social life and cause significant economic losses. In this study, the interruption costs of customers and distribution companies in 21 distribution regions in Turkey have been calculated and forecasts for the future have been realized. The aim here is to reveal the magnitude of the interruption costs with detailed analyses and methods that can be easily applied by decision makers and to support the decision-making processes. In this direction, the costs of interruption have been calculated by indirect analytical methods. Also, it is necessary to know how the interruption costs will change in the future to consider the interruption costs in investment plans. In this study, future forecasts have been performed using time series analyses and machine learning models. Additionally, solutions have been developed to facilitate the inclusion of interruption costs in the investment plans of the decision makers. With these solutions, the number and scope of investments can be increased. Thus, supply continuity performance will be increased in countries with high cost of interruptions and the losses incurred by the stakeholders in the energy sector will be reduced. [ABSTRACT FROM AUTHOR]

Control areas around the world use a variety of methods to ensure that resources added to meet future electricity loads create an adequate supply. This work describes a particular method for determining adequacy based on economic costs and benefits that applies equally well to dispatchable and nondispatchable resources. Analysis of the Northwest power supply indicates that energy efficiency and demand response may be the most cost-effective capacity resources for achieving an economic adequacy standard. [ABSTRACT FROM AUTHOR]

This paper presents a mixed integer linear programming (MILP) based approach for determining the optimal number, type and location of automation devices to be installed in the network by considering different types of devices simultaneously (remotely controlled circuit breakers/reclosers, sectionalizing switches, remotely supervised fault passage indicators). Simultaneously, it determines the new (optimal) locations of the automation devices that already exist in the network. In determining the most effective network automation scenario, the proposed approach takes into account the outage cost of consumers/producers due to momentary, short-term, and long-term interruptions, the commonly used network reliability indices (SAIFI, SAIDI, MAIFI, and ASIDI) as well as the cost of automation devices and the cost of crews. It provides the best network automation scenario in distribution systems if the network reliability indices are used for measuring the distribution system reliability, if cost of interruptions is defined to all consumers/producers, and if both aforementioned approaches (criteria) are used. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a new methodology to solve transmission expansion planning (TEP) problems in power system, based on the metaheuristic ant colony optimisation (ACO). The TEP problem includes the search for the least cost solution, bearing in mind investment cost and reliability worth. Reliability worth is considered through the assessment of the interruption costs represented by the index LOLC – loss of load cost. The focus of this work is the development of a tool for the multi-stage planning of transmission systems and how reliability aspects can influence on the decision-making process. The applications of the proposed methodology are illustrated through case studies carried out using a test system and a real sub-transmission network. [Copyright &y& Elsevier]

This paper shows a new hybrid method for risk assessment regarding interruptions in sensitive processes due to faults in electric power distribution systems. This method determines indices related to long duration interruptions and short duration voltage variations (SDVV), such as voltage sags and swells in each customer supplied by the distribution network. Frequency of such occurrences and their impact on customer processes are determined for each bus and classified according to their corresponding magnitude and duration. The method is based on information regarding network configuration, system parameters and protective devices. It randomly generates a number of fault scenarios in order to assess risk areas regarding long duration interruptions and voltage sags and swells in an especially inventive way, including frequency of events according to their magnitude and duration. Based on sensitivity curves, the method determines frequency indices regarding disruption in customer processes that represent equipment malfunction and possible process interruptions due to voltage sags and swells. Such approach allows for the assessment of the annual costs associated with each one of the evaluated power quality indices. [ABSTRACT FROM AUTHOR]

This paper describes a new methodology for measuring the impact of generation and transmission (G&T) maintenance strategies on the system reliability and on the associated costs. The proposed algorithm captures accurately the beginning and the end of all maintenance scheduling requests through a chronological or pseudo-chronological Monte Carlo simulation. Specific situations involving maintenance and repair outages are considered. In order to measure the performance of a given maintenance request, a strategy based on incremental costs has been proposed. These costs account for variations in production, revenues and reliability caused by maintenance schedules. Although, they are all random variables, the emphasis will be placed in the interruption costs and loss of potential revenue. Numerical examples are presented and the corresponding results are analyzed in detail. [Copyright &y& Elsevier]

The main idea presented and discussed in this paper is a model reproducing a time-dependent component failure rate pattern similar to the observed pattern recorded in failure statistics. This pattern includes all types of failures, caused by the weather or by technical and human aspects. Failure causes and mechanisms are not modelled explicitly and the observed pattern is assumed to be representative for the analysis period ahead. Being able to predict and time-tag component failures, the time-dependent variables of load, repair time and customer-specific interruption costs can be adequately combined to calculate annual reliability indices and interruption costs. This fact also permits us to apply an analytical model which will produce expectation values comparable with average values in a Monte Carlo simulation. © 1998 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]