Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In the present research, generation reliability is considered, and a method for its assessment is pr...Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In the present research, generation reliability is considered, and a method for its assessment is proposed using game theory and NN （neural networks）. Also, due to the stochastic behavior of power markets and generators＇ forced outages, MCS （monte carlo simulation） is used for reliability evaluation. Generation reliability merely focuses on the interaction between generation complex and load. Therefore, in the research, based on the behavior of players in the market and using game theory, two outcomes are considered： cooperation and non-cooperation. The proposed method is assessed on IEEE-Reliability Test System with satisfactory results. LOLE （loss of load expectation） is used as the reliability index and it will be shown that generation reliability in cooperation market is better than non-cooperation outcome.展开更多
Climate change threatens the sustainable development and survival of the small Caribbean island nations. The continual rise in the demand and cost of the earth＇s finite hydrocarbon energy reservoir drives these count...Climate change threatens the sustainable development and survival of the small Caribbean island nations. The continual rise in the demand and cost of the earth＇s finite hydrocarbon energy reservoir drives these countries to examine the integration of renewable energy to reduce green house gas emissions whilst meeting their electrical energy demands. One possible renewable energy source is wind. Trinidad and Tobago, through its renewable energy policy, is seeking to reliably and economically integrate wind power with its conventional power generation sources. This paper assesses the adequacy of wind power generation at potential sites through the use of auto-regressive modeling and the use of Monte Carlo Simulation to evaluate the well-being indices for the combination of wind and conventional power generation. Two sites in the twin island Republic of Trinidad and Tobago were identified as case studies for the proposed methodology. Analysis of the results indicated that the methodology should be applied to sites with conditions encouraging economic feasibility of wind power generation.展开更多
This paper presents a novel method for accurately estimating the cumulative capacity credit(CCC)of renewable energy(RE)projects.Leveraging data from the main interconnected system(MIS)of Oman for 2028,where a substant...This paper presents a novel method for accurately estimating the cumulative capacity credit(CCC)of renewable energy(RE)projects.Leveraging data from the main interconnected system(MIS)of Oman for 2028,where a substantial increase in RE generation is anticipated,the method is introduced alongside the traditional effective load carrying capability(ELCC)method.To ensure its robustness,we compare CCC results with ELCC calculations using two distinct standards of reliability criteria:loss of load hours(LOLH)at 24 hour/year and 2.4 hour/year.The method consistently gives accurate results,emphasizing its exceptional accuracy,efficiency,and simplicity.A notable feature of the method is its independence from loss of load probability(LOLP)calculations and the iterative procedures associated with analytic-based reliability methods.Instead,it relies solely on readily available data such as annual hourly load profiles and hourly generation data from integrated RE plants.This innovation is of particular significance to prospective independent power producers(IPPs)in the RE sector,offering them a valuable tool for estimating capacity credits without the need for sensitive generating unit forced outage rate data,often restricted by privacy concerns.展开更多
文摘Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In the present research, generation reliability is considered, and a method for its assessment is proposed using game theory and NN （neural networks）. Also, due to the stochastic behavior of power markets and generators＇ forced outages, MCS （monte carlo simulation） is used for reliability evaluation. Generation reliability merely focuses on the interaction between generation complex and load. Therefore, in the research, based on the behavior of players in the market and using game theory, two outcomes are considered： cooperation and non-cooperation. The proposed method is assessed on IEEE-Reliability Test System with satisfactory results. LOLE （loss of load expectation） is used as the reliability index and it will be shown that generation reliability in cooperation market is better than non-cooperation outcome.
文摘Climate change threatens the sustainable development and survival of the small Caribbean island nations. The continual rise in the demand and cost of the earth＇s finite hydrocarbon energy reservoir drives these countries to examine the integration of renewable energy to reduce green house gas emissions whilst meeting their electrical energy demands. One possible renewable energy source is wind. Trinidad and Tobago, through its renewable energy policy, is seeking to reliably and economically integrate wind power with its conventional power generation sources. This paper assesses the adequacy of wind power generation at potential sites through the use of auto-regressive modeling and the use of Monte Carlo Simulation to evaluate the well-being indices for the combination of wind and conventional power generation. Two sites in the twin island Republic of Trinidad and Tobago were identified as case studies for the proposed methodology. Analysis of the results indicated that the methodology should be applied to sites with conditions encouraging economic feasibility of wind power generation.
文摘This paper presents a novel method for accurately estimating the cumulative capacity credit(CCC)of renewable energy(RE)projects.Leveraging data from the main interconnected system(MIS)of Oman for 2028,where a substantial increase in RE generation is anticipated,the method is introduced alongside the traditional effective load carrying capability(ELCC)method.To ensure its robustness,we compare CCC results with ELCC calculations using two distinct standards of reliability criteria:loss of load hours(LOLH)at 24 hour/year and 2.4 hour/year.The method consistently gives accurate results,emphasizing its exceptional accuracy,efficiency,and simplicity.A notable feature of the method is its independence from loss of load probability(LOLP)calculations and the iterative procedures associated with analytic-based reliability methods.Instead,it relies solely on readily available data such as annual hourly load profiles and hourly generation data from integrated RE plants.This innovation is of particular significance to prospective independent power producers(IPPs)in the RE sector,offering them a valuable tool for estimating capacity credits without the need for sensitive generating unit forced outage rate data,often restricted by privacy concerns.
