Optimization of Electricity Retailer's Contract Portfolio Subject to Risk Preferences

Abstract

When an electricity retailer faces volume risk in meeting load and spot price risk in purchasing from the wholesale market, conventional risk management optimization methods can be quite inefficient. For the management of an electricity contract portfolio in this context, we develop a multistage stochastic optimization approach which accounts for the uncertainties of both electricity prices and loads, and which permits the specification of conditional-value-at-risk requirements to optimize hedging across intermediate stages in the planning horizons. Our experimental results, based on real data from Nordpool, suggest that the modeling of price and load correlations is particularly important. The sensitivity analysis is extended to characterize the behavior of retailers with different risk attitudes. Thus, we observe that a risk neutral retailer is more susceptible to price-related than load-related uncertainties in terms of the expected cost of satisfying the load, and that a risk averse retailer is especially sensitive to the drivers of the forward risk premium.

Retail Energy Management in Electricity Markets: Structure, Challenges and Economic Aspects- a Review

“…Considering the wholesale market, Day-ahead Market (DAM) [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28], Real Time Market (RTM) [17][18][19][20][21][22][23][24][25][26][27][28][29], Reserve Market (RM) [15,21,22] and Intraday Market (IDM) [20] are the most common markets used by retailers to purchase their obligated energy. Moreover, regarding the wholesale contracts, future contracts [17,26,29], forward contracts [16,18,23,30], call option [23,30] and swing contracts [25,28] are typically used in different studies of retail market. In addition to the large-scale power production facilities which participate in the wholesale market, some retailers prefer to procure some parts of their electrical energy through bilateral contracts signed with small-scale power generators.…”

“…In the literature about the energy management in retail electricity markets, there are many different research studies which consider the retailers as a price-taker agent [21][22][23][24][25][26][27][28][29]. Price-taker retailers (PTR) and price-maker retailers (PMR) are exposed to different sources of uncertainty.…”

“…Electricity price and clients' consumption are the key uncertain variables in the retail problem [17,23,[28][29][30][31][32][33][34]. Volatile electricity price in the electricity market, e.g.…”

“…The most common way to model the problem with uncertain variables is the stochastic programming. Regarding the retail problem, many research studies use stochastic programming approach to model the problem mathematically [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. Instead of the stochastic programming, some papers, especially in recent years, have concentrated on Information Gap Decision Theory (IGDT) [16] and robust optimization approach [31] to model the retail problem.…”

“…However, considering more trading floors, e.g. forward contract, day-ahead market, intraday market and real time market, the stochastic programming is converted into a multi-stage approach [28]. It is worth mentioning that in the stochastic programming with recourse, retailers are able to take corrective measures in each stage of the stochastic programming (correspond to each trading floors of the retail market).…”