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An electric power trading framework for smart residential community in smart cities
Author(s) -
Hanumantha Rao Bokkisam,
Arun Saravana Loganathan,
Selvan Manickavasagam Parvathy
Publication year - 2019
Publication title -
iet smart cities
Language(s) - English
Resource type - Journals
ISSN - 2631-7680
DOI - 10.1049/iet-smc.2019.0055
Subject(s) - locality , prosumer , electricity , schedule , demand response , electricity market , computer science , environmental economics , electric power system , business , power (physics) , economics , renewable energy , engineering , electrical engineering , physics , quantum mechanics , philosophy , linguistics , operating system
This study proposes a multi‐agent‐based framework for Peer‐to‐Peer (P2P) power trading in a locality electricity market (LEM) for self‐interested smart residential prosumers. In LEM, prosumers may sell (buy) their excess generation (demand) at a profitable market prices compared to utility prices to achieve a win–win outcome. In LEM, three agents namely locality electricity trading system (LETS), utility and prosumer act together to achieve P2P power trading in a day‐ahead market. LETS computes the internal market prices employing any one of the market‐clearing mechanisms and broadcasts it to the prosumers. Prosumers optimise the generation‐demand schedule for the next day using residential energy management and trading system to achieve minimum electricity bill. The performance of the proposed framework is validated through different case studies on a residential locality with ten prosumers. The simulation is carried out using MATLAB parallel computation tool box and the load data is collected from the residential locality of National Institute of Technology Tiruchirappalli, India. It is evident from the simulation results that all the participants are economically benefited by P2P power trading. It is also found that the SDR mechanism in P2P outperforms and reduces the locality electricity bill by 27–68% under different operating conditions.

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