Abstract
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.
Highlights
The dependency on the microgrid is because of it provides the potential benefits of reliability, security, efficiency and being environment friendly [1, 2]
The work considers that the three types of aggregators (RNA, risk averse aggregator (RAA), risk taking aggregator (RTA)) are presented both in demand response (DR) market and renewable energy source (RES) market
The hours where the demand above the +10% of aggregated base load of customers are considered as peak period while the hours where the demand below −10% of aggregated base load of customers are considered as valley periods
Summary
The dependency on the microgrid is because of it provides the potential benefits of reliability, security, efficiency and being environment friendly [1, 2]. The paper did not consider the uncertainty involved with the power generated by the RES and response of the customers during a DR event. References [6,7,8,9] considered the uncertainty but did not consider the financial risk that RESA faces during bidding in a day-ahead scenario. We use the risk measures VaR and CVaR to find out the benefit of the RES and DRAs. The uncertainty studies carried out here is basically to assess uncertainties in predicting the power to be committed and further to analyze the properties of the uncertainties for the future forecast. The uncertainty in the power generated by the RES and customers response is those that are inherent and cannot be removed These uncertainties can often be modeled by probability distribution unlike the economic uncertainty that follows Brownian motion or discrete Markov chain. This ensures that probability of obtaining power less than VaRa is lower than 100% À a
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