Bi-Level Approach for Load Serving Entity’s Sale Price Determination under Spot Price Uncertainty and Renewable Availability

Abstract

Load serving entities (LSEs) maximise their profit by increasing the difference between revenue from electricity sale to consumers and the cost of procuring that electricity. Considering the offered sale prices, consumers minimise energy bills by scheduling their energy consumption. Varying spot market prices and consumer behaviour impact LSE's electricity procurement and sale price decisions. The two conflicting objectives of LSE profit maximization and consumer cost minimization can be modelled effectively by hierarchical bi-level programming. Additionally, LSE has to consider spot market price uncertainty and renewable availability during different hours of the day. This paper considers these issues for LSE's risk-based profit maximization decision making model under RE availability by proposing a bi-level framework to determine optimal dynamic sale prices and energy procurement decisions. The upper level considers risk-based profit maximization for LSE and the lower level addresses the consumer's objective of cost minimization. This work considers Conditional Value at Risk (CVaR) to model spot market price risk for pragmatic characterisation of LSE's risk-averse behaviour. A case study on the PJM market shows the effectiveness of the proposed approach.

Load Serving Entity’s Profit Maximization Framework for Correlated Demand and Pool Price Uncertainties

“…Minimum up and down time of generating units is given by constraints (10) and (11). Minimum and maximum generation limits are decided by constraint (12). Equation 13is a non-negativity constraint.…”

“…For example, LSE may meticulously utilize short-term contracts and flexible demand to manage its strategy in electricity markets [9]. To modulate demand side response for increasing its profit [10] When flexible demand is available to LSE, a price-maker LSE's bidding and sale price decisions require strategic modifications to secure profit [11,12]. LSE's participation in renewable energy markets necessitates development of its profit strategies considering renewable factors [13].…”

Impact Assessment of Solar Integrated Residential Consumers on Retailer Decision-making

“…Availing such information of consumers is desirable, but it is challenging for retailers. Moreover, the challenges with renewable sources such as energy availability for limited periods and uncertainty create formidable scenarios for retailers [9]. The collective variation in demand due to renewable-integrated consumers could be far away from realistic demand estimated based on conventional factors, which could affect the retailer's profit.…”

“…Therefore, extensive research in various directions is necessary to consider the factors and emphasize different aspects. For instance, the hierarchical interaction between the retailer and consumer modeling requires advanced mathematical programming [9,20]. Consumers rationally optimize their consumption profiles subject to price sensitivity and demand flexibility to minimize energy bills.…”