Energy systems are in transition towards more sustainable generation portfolios. In the envisioned smart grid generation will primarily depend on renewable power sources making uncertain quantities of electricity available, the delivery of which cannot be guaranteed. Current electricity tariffs promise certain delivery, and are thus not well-suited to trade uncertain quantities. However, if not traded the electricity might need to be curtailed, foregoing potential benefits for both supply and demand sides. We propose to adopt service level agreements (SLAs) that comprise quantity, reliability, and price, for electricity trading in settings where supply depends on volatile power sources. We define a characterization of the value degradation of tolerant and critical buyers with regards to the uncertainty of electricity delivery generalizing the widely used value of lost load (VoLL). This captures buyers’ varying abilities to cope with uncertainty. We consider allocating SLAs to buyers using either a sequential second-price auction or the combinatorial Vickrey-Clarke-Groves (VCG) mechanism that is known to elicit truthful bids, and discuss the settings in which we can obtain truthfulness in the sequential setting. In addition, we empirically compare their performance and demonstrate that VCG dominates alternative allocations and vastly improves the efficiency of the proposed system, when compared to baseline allocations that only use the VoLL. This article hence contributes an essential component to the future smart grid by facilitating distributed energy trading under uncertainty.
Additional Metadata
Keywords Electricity trading, Uncertainty, SLAs, VoLL, Mechanism design
Persistent URL dx.doi.org/10.1186/s42162-018-0062-y
Journal Energy Informatics
Project Stable and scalable decentralized power balancing systems using adaptive clustering
Grant This work was funded by the The Netherlands Organisation for Scientific Research (NWO); grant id nwo/408-13-012 - Stable and scalable decentralized power balancing systems using adaptive clustering
Citation
Methenitis, G, Kaisers, M, & La Poutré, J.A. (2018). Renewable electricity trading through SLAs. Energy Informatics, 1(57). doi:10.1186/s42162-018-0062-y