Distributed energy resources integration and demand response: the role of stochastic demand modelling

2017 ◽  
pp. 245-278
Author(s):  
Emilio J. Palacios-Garcia Palacios-Garcia ◽  
Antonio Moreno-Munoz Moreno-Munoz ◽  
Isabel Santiago-Chiquero Santiago-Chiquero ◽  
Jose Maria Flores-Arias Flores-Arias ◽  
Francisco J. Bellido-Outeirino Bellido-Outeirino
Keyword(s):  
Demand Response ◽  
Stochastic Demand ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Demand Modelling ◽  
Resources Integration

A non-cooperative game based energy management considering distributed energy resources in price-based and incentive-based demand response program

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Monika Gaba ◽  
Saurabh Chanana
Keyword(s):  
Energy Management ◽  
Cooperative Game ◽  
Demand Response ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Energy Storage Devices ◽  
Electricity Cost ◽  
Distributed Approach ◽  
The Impact

Abstract Demand response (DR), an integral part of the smart grid, has great potential in handling the challenges of the existing power grid. The potential of different DR programs in the energy management of residential consumers (RCs) and the integration of distributed energy resources (DERs) is an important research topic. A novel distributed approach for energy management of RCs considering the competitive interactions among them is presented in this paper. The impact of participation of RC’s in price-based (PB) and incentive-based (IB) DR programs is investigated using game theory. For this, an energy management optimization problem (EMOP) is formulated to minimize electricity cost. The utility company employs electricity price as a linear function of aggregated load in the PB DR program and an incentive rate in the IBDR program. RCs are categorized into active and passive users. Active users are further distinguished based on the ownership of energy storage devices (SD) and dispatchable generation units (DGU). EMOP is modeled using a non-cooperative game, and the distributed proximal decomposition method is used to obtain the Nash equilibrium of the game. The results of the proposed approach are analyzed using different case studies. The performance of the proposed approach is evaluated in terms of aggregated cost and system load profile. It has been observed that participation in PB and IBDR program benefits both the utility and the consumers.

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