In this section
@inproceedings{Shilov:2023:10.1109/SmartGridComm57358.2023.10333930,
author = {Shilov, I and Le, Cadre H and Busic, A and Sanjab, A and Pinson, P},
doi = {10.1109/SmartGridComm57358.2023.10333930},
title = {Towards Forecast Markets For Enhanced Peer-to-Peer Electricity Trading},
url = {http://dx.doi.org/10.1109/SmartGridComm57358.2023.10333930},
year = {2023}
}
TY - CPAPER
AB - This paper examines the impact of the coupling between an introduced data market, in which agents can purchase a forecast of their renewable energy sources' generation levels to improve their estimation quality, and a peer-to-peer (P2P) electricity market, enabling prosumers to trade energy in a decentralized manner with their peers, amidst the growing trend of decentralization and uncertainty of renewable energy sources (RES) in electricity markets. The study formulates the P2P trading as a generalized Nash equilibrium problem and identifies conditions for achieving a maximized efficiency of the peer-to-peer electricity market, one of which is prosumers' participation in the forecast market. Along these lines, the analysis demonstrates that prosumers have incentives to participate in the forecast market and outlines the conditions, considering the case in which the forecasts are given in the form of a Gaussian distribution. Numerical examples using Pecan Street data demonstrate the theoretical findings and provide illustrations for the general case, as well as highlight the mutual benefits of market coupling for forecast sellers and electricity market agents.
AU - Shilov,I
AU - Le,Cadre H
AU - Busic,A
AU - Sanjab,A
AU - Pinson,P
DO - 10.1109/SmartGridComm57358.2023.10333930
PY - 2023///
TI - Towards Forecast Markets For Enhanced Peer-to-Peer Electricity Trading
UR - http://dx.doi.org/10.1109/SmartGridComm57358.2023.10333930
ER -
Dyson School of Design Engineering
Imperial College London
25 Exhibition Road
South Kensington
London
SW7 2DB
design.engineering@imperial.ac.uk
Tel: +44 (0) 20 7594 8888