Assessing and comparing a DDPG model and GA optimization for a heat and power virtual power plant operating in a power purchase agreement scheme

Assessing and comparing a DDPG model and GA optimization for a heat and power virtual power plant operating in a power purchase agreement scheme

This paper proposes a deep deterministic policy gradient (DDPG) model for the operation management of a solar power-based virtual power plant (VPP) having a PPA with the grid and supplying power and thermal energy to consumers. The VPP serves to balance the solar power intermittency, cover the deman...

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Bibliographic Details
Main Authors: Ahmed Hany Elgamal, Mehdi Shahrestani, Maria Vahdati
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Heliyon
Subjects:
Machine learning
Reinforcement learning
Power purchase agreement
Solar PV
CCHP
Virtual power plant
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024003499

Internet

http://www.sciencedirect.com/science/article/pii/S2405844024003499

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