Research On The Planning And Operation Optimization Of Renewable Energy System Considering Uncertainty

In order to cope with the increasingly severe climate change and energy crisis,the renewable energy,including photovoltaic and wind power,has been vigorously developed at home and abroad.Renewable energy has the advantages of being clean and renewable,but it also brings challenges to the safe and economic operation of the power system because of its inherent intermittence and volatility.Different uncertainty quantization methods of renewable energy have a great impact on the planning and operation optimization of the power system.With the support of the National Natural Science Foundation of China(NSFC)project "Research on the Source-load Synergy Optimization Considering the Integration of Multi-dimensional Renewable Energy and Dynamic Demand Response"(52107073),this dissertation focuses on the planning and operation optimization of the power system considering the uncertainty of the renewable energy.The main contributions of this dissertation can be summarized as follows.1.A two-level planning and operation optimization model for the power system considering the geographical constraints of renewable energy is proposed.The proposed model considers the geographical constraints of the construction location of substations,pumped storage power stations,photovoltaic and wind farms,as well as the impact of system operation on the planning.The proposed two-level optimization model includes the planning level and operation level.At the planning optimization level,the topology of the renewable energy system is optimized to minimize the total cost including the planning cost and operation cost.The topology optimization includes determining the construction location of substations,pumped storage power stations,photovoltaic and wind farms,as well as the connection layout of all buses.At the operation optimization level,based on the generated uncertain scenario of uncertain variables,the economic operation strategy of the renewable energy system is optimized through the optimal power flow calculation.2.From the perspective of independent energy storage investors,this dissertation proposes a planning and operation model to maximize the profits of energy storage investors and reduce the renewable energy curtailment of the power system.In the proposed model,the capacity and size of battery energy storage systems are optimized.The planning and operation problem of the battery energy storage system considering the uncertainty is formulated as a bi-level optimization model.In the upper optimization level,the particle swarm optimization is adopted to optimize the installation time,location,rated power and capacity of the battery energy storage system.In the lower optimization level,the charging/discharging power of the battery energy storage system is optimized by the interior point method to improve the economic benefits of the power system,and then the optimal power flow is calculated to obtain the optimal scheduling strategy of the wind energy.3.In order to deal with the uncertainty of renewable energy in the unit commitment of the power system,the uncertainty set with the adjustable boundary is introduced to describe the uncertainty of renewable energy.The balance between the conservativeness and economy of the operation of the power system is balanced by optimizing the boundary of the adjustable uncertainty set,and the proposed method can guarantee the safe operation of power system in this adjustable uncertainty set.A distributionally robust optimization approach is proposed to evaluate the operational risk of load shedding and renewable energy curtailment at the upper and lower bounds of the adjustable uncertainty set.Because of the consideration of the probability distribution information of renewable energy generation,the distributionally robust optimization approach can reduce the conservativeness of the traditional robust optimization method.In addition,a dynamic demand response strategy is proposed to reduce the operational risk of the renewable energy system by enlarging the size of the adjustable uncertainty set.4.An energy scheduling model which considers the uncertainty of multiple renewable energy is proposed.This model introduces a convex hull based uncertainty set whose boundaries can be adjusted to quantify the uncertainty of renewable energy generation.This adjustable convex hull based uncertainty set can capture the correlation between multiple renewable energy.In this dissertation,a data-driven approach is adopted to evaluate the operational risk of the adjustable convex hull based uncertainty set.This approach guarantees the operation safety of the power system in the adjustable convex hull based uncertainty set.Besides,it defines the operational risk of the power system as the minimum expected penalty cost of making the renewable energy generation return to the adjustable convex hull based uncertainty set,in which the operation safety is guaranteed.Based on the operational risk assessment,a day-ahead energy scheduling model of the renewable energy system considering the adjustable convex hull based uncertainty set is constructed.