Affiliation:
1. Department of Electrical Engineering National Institute of Technology Calicut Kozhikode Kerala India
2. Faculté des sciences et technologies Université de Lorraine Nancy Grand Est France
3. Department of Electrical and Electronics Engineering National Institute of Technology Tiruchirappalli Tiruchirappalli Tamilnadu India
Abstract
AbstractThe energy risk associated with distributed energy resources (DERs) is inevitable in Peer‐to‐Peer (P2P) transactive energy markets owing to mismatches between energy commitments and metered measurements. However, adjusting these possible mismatches by progressive revision of the energy commitments in the rolling time horizon mitigates the energy risk, and thereby mitigates the financial risk for prosumers. In this study, the conditional value at risk (CVaR) is used to estimate the risk value for each prosumer. The energy offers that are riskier than CVaR‐based threshold values are reduced in an “adjustment bid”. A new pricing mechanism for these adjustment bids is introduced, which varies with historical deviations of a prosumer from energy commitments. This market framework and pricing mechanism are simulated through a blockchain network hosted on a Python Django server using the practical Byzantine fault tolerance consensus algorithm to guarantee network immutability and data privacy. Efforts to mitigate such mismatches between ex‐ante and ex‐post energy values incentivise risk‐aware participation in P2P markets. In addition, the welfare of both prosumers and consumers improves with their participation in the proposed market framework. Furthermore, implementing a network using blockchain technology guarantees the privacy of bidding data and provides a secure transaction platform.
Publisher
Institution of Engineering and Technology (IET)
Cited by
4 articles.
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