A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Stochastic Demand Response under Random Renewable Power Generation in Smart Grid
Rooftop photovoltaic (PV) generation combined with battery energy storage provides a promising solution for solar energy integration in smart grid. Specifically, the home battery energy storage systems can improve the efficiency and reliability of PV integration while reducing the greenhouse gas emissions. In this paper, we investigate the randomness of home PV generation and the residential random load demand, which may affect the efficiency and reliability of the power grid. A bilevel stochastic programming problem is formulated to provide a pricing strategy to customers for the optimal demand response in smart grid. In particular, the operators model represents the cost minimization of the power system operation, while the customers’ model represents the cost minimization of their household energy demand. In the operators model, power loss calculated based on power flow analysis is used as the system loss, while the stochastic model of the household load demand is used instead of the expected value to characterize the human random behaviour. The performance of the proposed stochastic demand response scheme is evaluated through extensive simulations. Simulation results indicate that this novel scheme can help both power system operators and electrical customers to better decide on their operating schedule and energy usage, respectively
Stochastic Demand Response under Random Renewable Power Generation in Smart Grid
Rooftop photovoltaic (PV) generation combined with battery energy storage provides a promising solution for solar energy integration in smart grid. Specifically, the home battery energy storage systems can improve the efficiency and reliability of PV integration while reducing the greenhouse gas emissions. In this paper, we investigate the randomness of home PV generation and the residential random load demand, which may affect the efficiency and reliability of the power grid. A bilevel stochastic programming problem is formulated to provide a pricing strategy to customers for the optimal demand response in smart grid. In particular, the operators model represents the cost minimization of the power system operation, while the customers’ model represents the cost minimization of their household energy demand. In the operators model, power loss calculated based on power flow analysis is used as the system loss, while the stochastic model of the household load demand is used instead of the expected value to characterize the human random behaviour. The performance of the proposed stochastic demand response scheme is evaluated through extensive simulations. Simulation results indicate that this novel scheme can help both power system operators and electrical customers to better decide on their operating schedule and energy usage, respectively
Stochastic Demand Response under Random Renewable Power Generation in Smart Grid
Wang, Yue (author) / Liang, Hao (author) / Dinavahi, Venkata (author)
2019-08-01
Conference paper
Electronic Resource
English
DDC:
690
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