Equivalent Forced Outage Rate Research Articles

The Implementation of K-Means Clustering in Coal-fired Power Plant Performance

Performance monitoring for power plant industry is important to know current condition and determined the prior way for improvement strategy. This study aims to classified performance index which are Equivalent Availability Factor (EAF) and Equivalent Forced Outage Rate (EFOR) in various coal-fired power plant in Java Bali, Indonesia. The results of this plants grouping possible to be applied as one of the supports systems in real-time operational decisions to determine plant maintenance priorities. The proposed clustering model is possible to be applied for power plant’s control centre unit in Indonesia in grouping power plants based on performance indexes. The result show that there were 4 clusters of the power plant performance. The clustering drives to identify which plant that must be prioritized for improvement. The clustering method has a model accuracy rate of 87% which indicates that model was valid and applicable. For further research, a decision support system design was required for operational validation. Keywords—Decision-making, Decision support system, Kmeans clustering, Performance, Power plant.

Implementation of Competitive Intelligence in Improving Company Performance of Power Plant in Indonesia

Numerous studies have been conducted on competitive intelligence and its impact on business performance. Most of companies agreed that competitive intelligence is a critical element of business and corporate strategy to increase income hence investment in competitive intelligence considered to be profitable. This research is aimed to expand the knowledge boundary by investigating the application of Competitive Intelligence in electrical power plant company. Twenty companies were selected as the target sample using purposive sampling design, in which the questionnaires were distributed to 120 individuals who were argued to have knowledge in the practice of Competitive Intelligence. In total, 105 questionnaires were returned for further analysis. Data were analyzed using descriptive statistic provided by SPSS. In the aspect of Competitive Intelligence Practices, results indicated that the mean score for each individual item range between 3.23 to 4.14, suggesting intensive practices of Competitive Intelligence. In the aspect of Utilization of Tools in practicing Competitive Intelligence, results indicated that three most widely used tools were from Employees, Customers and Internet. In the aspect of measurement variables in measuring competitive intelligence practices, results indicated that three most widely used measures were (1) yearly improvement of Equivalent Availability Factor-EAF (mean 3.96), (2) increase in percentage of planned maintenance (mean 3.82), and (3) yearly improvement of Equivalent Forced Outage Rate – EFOR (mean 3.75). Public utilities (infrastructure) company usually being pictured as companies that does not really care about competition as they usually being run by the Government. However, the findings of this research show otherwise

Evaluating the benefits of using short-term direct normal irradiance forecasts to operate a concentrated solar thermal plant

Past studies about using direct normal irradiance (DNI) forecasts to operate a concentrated solar thermal (CST) plant have not considered intra-day forecasts. This is a critical research gap because short-term forecasts are recommended for managing variable output from renewable energy generators, including CST plants. This study evaluates the benefits of using 1-h forecasts to decide updated bids for a CST plant after making initial bids from 48-h forecasts. The benefits are represented by the financial value calculated from revenue and reserve generation (RG) payments, and the reliability calculated from the equivalent forced outage rate (EFOR).Simulating a CST plant operating in the Australian National Electricity Market for one year showed that using 1-h forecasts increases financial value by $1.04–1.13million and reduces EFOR by 20–21% points for a 50 Megawatt (MW) CST plant with 7.5h of storage, and increases financial value by $0.7–$0.9million and reduces EFOR by 20–23% points for a 50MW CST plant without storage. Reduced RG costs contributed towards 76–98% of the financial value increase for both CST plants. A CST plant without storage that uses 1-h forecasts achieves an EFOR of 10–11%, whereas a CST plant with storage that does not use 1-h forecasts achieves an EFOR of 21–22%, so using 1-h forecasts may improve reliability more than adding storage to a CST plant without storage. Using 1-h forecasts does not achieve the same total net value as a perfect 48-h forecast, but it achieves close to maximum value per unit electricity generated. Overall, CST plants should use short-term forecasts if permitted under local electricity market regulations because they can achieve higher financial value and reliability. Future studies should use short-term forecasts when allowed by the local electricity market to more accurately demonstrate the value of CST plants.

Incorporating multi‐state unit models in composite system adequacy assessment

AbstractComponents are usually represented by a two state model in conventional generating capacity and composite generation and transmission system reliability studies. Multi‐state generating unit models create a significant increase in the number of generation contingency states and can result in a considerable increase in the overall solution time. In order to avoid this problem, the derated states are usually amalgamated with the totally forced out state to create the derating‐adjusted forced outage rate (DAFOR). This statistic is also known as the equivalent forced outage rate (EFOR). Studies have shown that modeling large generating units in generating capacity adequacy assessments using DAFOR can provide pessimistic appraisals. Many utilities therefore use multi‐state generating unit representations to assess generating capacity adequacy, in order to obtain more accurate appraisals. There is relatively little published material dealing with the effects of using multi‐state generating unit representations in composite system adequacy assessment. This paper illustrates these effects by application to the IEEE‐Reliability Test System (RTS). Load point and system indices for the test system are presented to illustrate the impact of incorporating multi‐state representations in composite system adequacy assessment. Attention is focused on the effects of model variations including how many derated states should be used in a multi‐state model to obtain a reasonably accurate appraisal. Copyright © 2007 John Wiley & Sons, Ltd.

A Method for Estimating Equivalent Forced Outage Rates of Multistate Peaking Units

This paper proposes and illustrates a method for calculating the equivalent forced outage rate of multi-state peaking generating units. The proposed method considers partial- outages which were not specifically included in the methods proposed previously. Two approaches proaches are described and illustrated: one requires developing and solving a multi-state model using component failure and repair rates; the other which is an empirical approach requires quires additional data on start times and stop times of the units to define the demand period.

Effect of Partial Outage Representation in Generation System Planning Studies

Large size thennal units are subject to a number of partial outages due to their multitude of components and auxiliaries. These derated states should be correctly included in the generation system capacity outage probability model. Virtually all static capacity planning studies utilize a binary representation of the generating units. Any type of approximation; representing partial outages as full outages, neglecting partial outages or an equivalent forced outage rate EFOR can result in significant error. This paper investigates the quantitative effects of accurate derated and approximate EFOR representation on the possible expansion of a generation system.