2023
DOI: 10.1007/s42452-023-05424-6
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Energy consumption forecast in peer to peer energy trading

Abstract: This study predicts future values of energy consumption demand from a novel dataset that includes the energy consumption during COVID-19 lockdown, using up-to-date deep learning algorithms to reduce peer-to-peer energy system losses and congestion. Three learning algorithms, namely Random Forest (RF), Bi-LSTM, and GRU, were used to predict the future values of a building’s energy consumption. The results were compared using the RMSE and MAE evaluation metrics. The results show that predicting the future energy… Show more

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Cited by 3 publications
(2 citation statements)
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“…Over the past decade, Distributed Energy Resources (DER) have experienced a substantial global proliferation [1][2][3][4]. These resources have revolutionized the dynamics of energy generation and distribution within the energy sector by enabling consumers and prosumers (individuals who both generate and consume electricity) to engage in direct energy sharing without the necessity of intermediaries.…”
Section: Introductionmentioning
confidence: 99%
“…Over the past decade, Distributed Energy Resources (DER) have experienced a substantial global proliferation [1][2][3][4]. These resources have revolutionized the dynamics of energy generation and distribution within the energy sector by enabling consumers and prosumers (individuals who both generate and consume electricity) to engage in direct energy sharing without the necessity of intermediaries.…”
Section: Introductionmentioning
confidence: 99%
“…Over the past decade, Distributed Energy Resources (DER) have experienced a substantial global proliferation [1][2][3][4]. These resources have revolutionized the dynamics of energy generation and distribution within the energy sector by enabling consumers and prosumers (individuals who both generate and consume electricity) to engage in direct energy sharing without the necessity of intermediaries.…”
Section: Introductionmentioning
confidence: 99%