Abstract
In this paper, a hybrid energy management system is developed to optimize the operation of a wind farm (WF) by combining centralized and decentralized approaches. A two-stage optimization strategy, including distributed information sharing (stage 1); and centralized optimization (stage 2) is proposed to find out the optimal set-points of wind turbine generators (WTGs) considering grid-code constraints. In stage 1, cluster energy management systems (CEMSs) and transmission system operator (TSO) interact with their neighboring agents to share information using diffusion strategy and then determine the mismatch power amount between the current output power of WF and the required power from TSO. This amount of mismatch power is optimally allocated to all clusters through the CEMSs. In stage 2, a mixed-integer linear programming (MILP)-based optimization model is developed for each CEMS to find out the optimal set-points of WTGs in the corresponding cluster. The CEMSs are responsible for ensuring the operation of WF in accordance with the requirements of TSO (i.e., grid-code constraints) and also minimizing the power deviation for the set-points of WTGs in each cluster. The minimization of power deviation helps to reduce the internal power fluctuations inside each cluster. Finally, to evaluate the effectiveness of the proposed method, several case studies are analyzed in the simulations section for operation of a WF with 20 WTGs in four different clusters.
Highlights
In recent years, the demand for renewable energy sources (RESs) is increasing dramatically due to the exhaustion of fossil fuels as well as the shortage of electricity supplies
In order to optimize the operation of wind farm (WF), we developed a two-stage optimization strategy to find out optimal set-points of wind turbine generators (WTGs) and fulfill the grid-code constraints from transmission system operator (TSO)
In order to ensure stability for the operation of WF, the power balance is always maintained in WF between the total output power from WTGs and the required power from the power system
Summary
The demand for renewable energy sources (RESs) is increasing dramatically due to the exhaustion of fossil fuels as well as the shortage of electricity supplies. After the information-sharing process, the amount of mismatch power can be calculated based on the current WF’s output power and the required power from TSO This amount of mismatch power is optimally allocated to all clusters through the CEMSs. In stage 2, an MILP-based optimization model is developed for each CEMS and the CEMS will perform optimization to find out optimal set-points of WTGs for balancing the mismatch power in the corresponding cluster A hybrid energy management system is developed to optimize the operation of a large WF system by combining both centralized and decentralized approaches This makes the design of communication network much simpler. A two-stage optimization is proposed to optimize the operation of the WF system to reduce the power deviation for set-points of WTGs. CEMSs and TSOs share information to optimally determine the amount of increase/decrease for each cluster using diffusion strategy.
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