In power market environment,the growing importance of demand response(DR)and renewable energy source(RES)attracts more for-profit DR and RES aggregators to compete with each other to maximize their profit.Meanwhile,th...In power market environment,the growing importance of demand response(DR)and renewable energy source(RES)attracts more for-profit DR and RES aggregators to compete with each other to maximize their profit.Meanwhile,the intermittent natures of these alternative sources along with the competition add to the probable financial risk of the aggregators.The objective of the paper is to highlight this financial risk of aggregators in such uncertain environment while estimating DR magnitude and power generated by RES.This work develops DR modeling incorporating the effect of estimating power at different confidence levels and uncertain participation of customers.In this paper,two well-known risk assessment techniques,value at risk and conditional value at risk,are applied to predict the power from RES and DR programs at a particular level of risk in different scenarios generated by Monte Carlo method.To establish the linkage between financial risk taking ability of individuals,the aggregators are classified into risk neutral aggregator,risk averse aggregator and risk taking aggregator.The paper uses data from Indian Energy Exchange to produce realistic results and refers certain policies of Indian Energy Exchange to frame mathematical expressions for benefit function considering uncertainties for each type of three aggregators.Extensive results show the importance of assessing the risks involved with two unpredictable variables and possible impacts on technical and financial attributes of the microgrid energy market.展开更多
文摘In power market environment,the growing importance of demand response(DR)and renewable energy source(RES)attracts more for-profit DR and RES aggregators to compete with each other to maximize their profit.Meanwhile,the intermittent natures of these alternative sources along with the competition add to the probable financial risk of the aggregators.The objective of the paper is to highlight this financial risk of aggregators in such uncertain environment while estimating DR magnitude and power generated by RES.This work develops DR modeling incorporating the effect of estimating power at different confidence levels and uncertain participation of customers.In this paper,two well-known risk assessment techniques,value at risk and conditional value at risk,are applied to predict the power from RES and DR programs at a particular level of risk in different scenarios generated by Monte Carlo method.To establish the linkage between financial risk taking ability of individuals,the aggregators are classified into risk neutral aggregator,risk averse aggregator and risk taking aggregator.The paper uses data from Indian Energy Exchange to produce realistic results and refers certain policies of Indian Energy Exchange to frame mathematical expressions for benefit function considering uncertainties for each type of three aggregators.Extensive results show the importance of assessing the risks involved with two unpredictable variables and possible impacts on technical and financial attributes of the microgrid energy market.
