Abstract
An important revenue stream for electric battery operators is often arbitraging the hourly price spreads in the day-ahead auction. The optimal approach to this is challenging if risk is a consideration as this requires the estimation of density functions. Since the hourly prices are not normal and not independent, creating spread densities from the difference of separately estimated price densities is generally intractable. Thus, forecasts of all intraday hourly spreads were directly specified as an upper triangular matrix containing densities. The model was a flexible four-parameter distribution used to produce dynamic parameter estimates conditional upon exogenous factors, most importantly wind, solar and the day-ahead demand forecasts. These forecasts supported the optimal daily scheduling of a storage facility, operating on single and multiple cycles per day. The optimization is innovative in its use of spread trades rather than hourly prices, which this paper argues, is more attractive in reducing risk. In contrast to the conventional approach of trading the daily peak and trough, multiple trades are found to be profitable and opportunistic depending upon the weather forecasts.
Highlights
Operating a storage facility within an electricity system used to be relatively straightforward
In sunny locations with substantial solar energy, e.g., California, the lowest hourly prices may often be in the middle of the day, since widespread local solar production reduces demand on the wholesale market [1]
Secomandi [34] focuses upon gas storage as a dynamic inventory problem and in Nadarajah et al [35] extends this to deal with network transportation trading
Summary
Operating a storage facility within an electricity system used to be relatively straightforward. Even if the operator is considering other modes of operation, the authors of this paper have been informed by a battery operator that the estimation of potential arbitrage profits from the day-ahead auction can provide an opportunity cost baseline for bidding the asset into other flexibility auctions, as offered by grid operators, or for some of the storage services required by end-users and retailers Despite these profit maximization algorithms being based upon expected arbitrage spreads in the hourly prices, as set by day-ahead auctions, risk is an important consideration, as emphasized by Lucas [4]. This paper applies the spread densities formulation to the German market, which forms the largest and main daily reference for wholesale power in Europe This market is strongly influenced by wind and solar production, as well as providing a place where batteries and demand-side management are active innovations.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
