This paper presents a new methodology to evaluate loss of load indices, with particular emphasis on LOLC (loss of load cost) assessment, for composite generation and transmission systems considering time varying loads for different areas or buses. The proposed approach, named pseudo-chronological simulation, retains the computational efficiency of nonsequential Monte Carlo simulation and the ability to model chronological load curves in sequential simulation. It considers the actual blocks of unsupplied energy per consumer class, per bus, and the respective duration, to accurately characterize the interruption process. Case studies on the IEEE-MRTS (Modified Reliability Test System) and the BSS (Brazilian South-Southeastern System) are presented and discussed.

Pseudo-chronological simulation for composite reliability analysis with time varying loads

Information on the value of reliable electricity service can be used to assess the economic efficiency of investments in generation, transmission and distribution systems, to strategically target investments to customer segments that receive the most benefit from system improvements, and to numerically quantify the risk associated with different operating, planning and investment strategies. This paper summarizes research designed to provide estimates of the value of service reliability for electricity customers in the US. These estimates were obtained by analyzing the results from 28 customer value of service reliability studies conducted by 10 major US electric utilities over the 16 year period from 1989 to 2005. Because these studies used nearly identical interruption cost estimation or willingness-to-pay/accept methods it was possible to integrate their results into a single meta-database describing the value of electric service reliability observed in all of them. Once the datasets from the various studies were combined, a two-part regression model was used to estimate customer damage functions that can be generally applied to calculate customer interruption costs per event by season, time of day, day of week, and geographical regions within the US for industrial, commercial, and residential customers. Estimated interruption costs for different types of customers and of different duration are provided. Finally, additional research and development designed to expand the usefulness of this powerful database and analysis are suggested.

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Estimated Value of Service Reliability for Electric Utility Customers in the United States

This paper summarizes the results of a survey of 210 large commercial and industrial customers to obtain detailed descriptions of the components of interruption costs they would experience under varying outage conditions. In addition, the survey observed plant operating schedules, products and services, processes used machinery used in production, backup generation and equipment designed to ensure power quality. The paper describes a statistical approach for obtaining inexpensive outage cost estimates for individual customers by combining information from on-site interviews with less costly information obtained from utility representatives. Results from regression models estimated from the information obtained in the on-site survey are described in detail.

Power interruption costs to industrial and commercial consumers of electricity

Transmission expansion planning (TEP) has faced a significant change since the introduction of deregulation. It becomes even more complicated. Algorithms have to be changed to meet new challenges. This paper organizes and classifies existing TEP algorithms in both regulated and deregulated environment so as to facilitate other research works in this area. Besides, two suggestions have been made for the TEP approach in the future. Firstly, some standard elements are inevitably needed in TEP algorithms. Those standard elements can be left to other researchers for specialization. Research effort can, therefore, be saved, if only TEP algorithm has to be considered. Secondly, specific market regulations and conditions should be included in the future TEP algorithm so as to turn the algorithm from an academically feasible one into a commercially feasible one

Transmission Expansion Planning From Past to Future

Author(s): Lawton, Leora; Sullivan, Michael; Van Liere, Kent; Katz, Aaron; Eto, Joseph | Abstract: A clear understanding of the monetary value that customers place on reliability and the factors that give rise to higher and lower values is an essential tool in determining investment in the grid. The recent National Transmission Grid Study recognizes the need for this information as one of growing importance for both public and private decision makers. In response, the U.S. Department of Energy has undertaken this study, as a first step toward addressing the current absence of consistent data needed to support better estimates of the economic value of electricity reliability. Twenty-four studies, conducted by eight electric utilities between 1989 and 2002 representing residential and commercial/industrial (small, medium and large) customer groups, were chosen for analysis. The studies cover virtually all of the Southeast, most of the western United States, including California, rural Washington and Oregon, and the Midwest south and east of Chicago. All variables were standardized to a consistent metric and dollar amounts were adjusted to the 2002 CPI. The data were then incorporated into a meta-database in which each outage scenario (e.g., the lost of electric service for one hour on a weekday summer afternoon) is treated as an independent case or record both to permit comparisons between outage characteristics and to increase the statistical power of analysis results. Unadjusted average outage costs and Tobit models that estimate customer damage functions are presented. The customer damage functions express customer outage costs for a given outage scenario and customer class as a function of location, time of day, consumption, and business type. One can use the damage functions to calculate outage costs for specific customer types. For example, using the customer damage functions, the cost experienced by an "average" customer resulting from a 1 hour summer afternoon outage is estimated to be approximately $3 for a residential customer, $1,200 for small-medium commercial and industrial customer, and $82,000 for large commercial and industrial customer. Future work to improve the quality and coverage of information on the value of electricity reliability to customers is described.

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A framework and review of customer outage costs: Integration and analysis of electric utility outage cost surveys

This paper documents the material presented at the IEEE 1994 Summer Power Meeting Panel on the application of reliability in least cost power system planning, sponsored by the Application of Probability Methods (APM) Subcommittee of the Power System Engineering Committee of IEEE. The paper contains short notes by five panelists, representing five electric utilities in North America, on the application of reliability and value of service analysis in power system planning.

W. Gambel

Papers

Experience with application of reliability and value of service analysis in system planning