Abstract
This article investigates the autonomous demand response (ADR) in a building microgrid incorporating photovoltaic (PV) generation and plug-in electric vehicles. Two operation models are introduced in this article to enhance the self-utilization of PV power: 1) mixed integer programming (MIP)-based optimization model; and 2) the game theoretic model. To avoid the disadvantages of MIP-based centralized optimization in a decentralized approach, a non-cooperative ADR game framework is formulated based on the proposed virtual cost mechanism for each player to help in selecting the optimal consumption strategy coordinately. The existence of the unique Nash equilibrium which coincides with the optimal solution of the MIP-based operation model is proved. In addition, an iterative algorithm is developed to determine the equilibrium solution for the ADR game. Simulation results verify that the non-cooperative game-based ADR program is effective in improving the utilization of PV energy and benefits to microgrid systems.
Highlights
Demand response (DR) programs are implemented to control the energy consumption at the demand side of the meter [1], [2], which are widely applied all over the world due to several reasons including the growing energy demand and environment protection, resilience enhancement of the power systems, as well as the stochastic nature of renewable energy sources (RESs) [3], [4]
In this article, an autonomous demand response (ADR) framework for a commercial building MG in the presence of the publication was Bin Zhou .electric vehicles (PEVs) and battery energy storage system (BESS) was studied to promote the utilization of PV energy based on non-cooperative game approach
In the scheduling framework, based on the proposed virtual cost mechanism, we formulated an ADR game in a decentralized manner to overcome the disadvantages of the centralized optimization problem
Summary
Demand response (DR) programs are implemented to control the energy consumption at the demand side of the meter [1], [2], which are widely applied all over the world due to several reasons including the growing energy demand and environment protection, resilience enhancement of the power systems, as well as the stochastic nature of renewable energy sources (RESs) (mainly solar and wind energy) [3], [4]. Where LDOD is the total cycle times when the discharge depth is DOD (DOD∈[0,1]); Lann is the annualized cycle times of the BESS, which is calculated using the rain-flow-counting method [40] Summarizing, this is an MIP-based centralized scheduling problem in which the system requires the ESP to collect all the information needed, such as consumption requirements of the users, and PV output, to determine the optimal energy consumption schedulings for the PEVs and BESS, which can be solved with branch and bound method [41]. MODELING OF ADR GAME a virtual cost mechanism is developed so as to avoid the disadvantages of above MIP-based centralized optimization, which is the basis to guide the energy consumption schedulings of the PEVs and BESS. In order to transform centralized optimization into decentralized autonomous optimization, an ADR game model among the PEVs and BESS is introduced in the MG to maximize the utilization of PV power
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