Research On Energy Management Optimization Of Off-grid Hybrid Renewable Rnergy System

With the development of smart grid,energy management is the key part in power system operation for good efficiency and reliability.Among the important components of future smart grid,hybrid renewable energy systems have attracted widespread attention.Hybrid renewable energy systems are usually integrated with distributed energy sources,such as distributed generators,energy storage systems,and controllable loads.It can operate in grid-connected mode or off-grid mode.Meanwhile,it can carry out energy plans through the energy management system.With the development of emerging technology,renewable energy power generation such as wind energy and solar energy has increasingly penetrated into the hybrid renewable energy system,making the energy management problem of the hybrid renewable energy system more complex and uncertain.The research work in this paper was funded by the national key research and development program,which target is to build on the key technologies for planning and stability control of weakly interconnected hybrid renewable energy systems(2018YFE0127600).This paper mainly studies the distributed robust optimization considering the energy management of off-grid hybrid renewable energy systems.Together with photovoltaic power generation,cascade small hydropower,pumped storage hydropower stations and diesel generators are added to form a hydro-phobic storage system.The operation model of diesel combined power generation is helpful to realize the maximum revenue,which is the the objective function,and considers the power generation cost and emission cost of the distributed generators,and establishes an energy management under the constraints of the opportunity of the pumping pump power limit of the pumped storage hydropower station.The system model uses a distributed robust optimization method to deal with a chanceconstraint,and reformulates the energy management problem as a second-order cone programming problem,which is then solved by the Gurobi solver.At last,the comparison between the distributed robust optimization method and the stochastic optimization with normal distribution method is conducted.The main contents of the paper are as follows:(1)For off-grid hybrid renewable energy systems,cascade small hydropower,pumped storage power stations,photovoltaic power stations and diesel generators form a hybrid renewable energy joint operation system,with the goal of maximizing the total system revenue,consider the power generation cost and emission cost of distributed generators,and establish an energy management system model under the constraint of chance constraint of pumping pump power.(2)At the same time,the worst-case CVa R(Conditional Value at Risk)is used to approximate the chance constraint.The distributed robust optimization method is used to transform the chance constraint,and the energy management problem is transformed into a second-order cone programming problem.The Gurobi solver in the Python is used to solve the problem.The final result verifies the feasibility of the proposed model,thereby improving the reliability of the system.(3)Through the case analysis,the capacity allocation problem is discussed.At the same time,the distributed robust optimization method and the stochastic optimization method are compared under the same situation.The results show the advantages and robustness of the distributed robust optimization method.