The Scheduling Strategies Of Concentrating Solar Power Plants Considering Multi-uncertainties And Multi-resources’ Coordination

Due to fossil energy crises and environmental problems,renewable energy sources have drawn unprecedented attention.However,the output power of intermittent renewable energy sources such as wind power and photovoltaic(PV)power is intermittent and fluctuating.The large-scale integration of intermittent renewable energy sources brings new challenges to the power quality and securely operation of power systems.In recent years,the concentrating solar power(CSP)technology has developed rapidly.The basic principle of CSP is to use solar energy to generate heat,then heat the working fluid and drive the turbine to generate electricity.Compared with intermittent renewable energy sources such as wind power and PV power,whose output power is with uncertainties,the output power of the CSP plant is dispatchable and controllable,and it also has the ability to adjust the output power quickly.With the growing maturity of the CSP technology,its self-scheduling as an independent power generator or coordinated scheduling with other source or load resources that are with uncertainties in the electricity market environment have received more and more attention.In order to address the scheduling strategies for CSP plants under multi-uncertainties and with multi-resources,this dissertation has carried out some comprehensive and systematic researches on CSP plants,mainly including the following four aspects:(1)The scheduling strategy of CSP plants based on stochastic information gap modelsWith the risk attitude of the CSP plant,the non-stochastic thermal production as well as the stochastic day-ahead and real-time market prices considered,a stochastic information gap approach is proposed to optimize the CSP plant’s scheduling strategies in the day-ahead and real-time electricity markets.This approach integrates the information gap decision theory and the mixed conditional value at risk,thus it can effectively deal with the scheduling strategy optimization problem of both the risk-averse and risk-seeking CSP plants considering the coexistent non-stochastic and stochastic uncertainties.A two-stage architecture is proposed to determine the scheduling strategies of the CSP plant in the day-ahead and real-time markets.The first-stage aims to co-optimize the day-ahead and real-time scheduling strategies,but the real-time scheduling strategy is not actually implemented.The second-stage determines the actual scheduling strategy in the real-time market based on the rolling-horizon technique.Simulation results show that the stochastic information gap approach can effectively deal with non-stochastic uncertainties,stochastic uncertainties,as well as the risk attitude of the decision maker,and it can effectively determine the optimal scheduling strategies for CSP plants in the day-ahead and real-time markets.(2)Risk-constrained scheduling strategy for CSP plants with demand responseA scheduling strategy is proposed for the CSP plants considering demand response based on the framework of the virtual power plant.The considered demand response is provided by a residential load aggregator and the industrial loads.For the residential load aggregator,the participation factor is proposed to describe the uncertainty of the residential demand response it provides.For the industrial loads,the price-based demand response is considered based on the day-ahead real-time pricing mechanism.As uncertainties such as the market price,the thermal production of the CSP plant,and participation factors of residential demand response may lead to the profit risk for the virtual power plant,the information gap decision theory is proposed to deal with these uncertainties and analyze their impacts on the scheduling profit risks of the virtual power plant.The simulation results verify the effectiveness of the information gap decision theory in uncertainty management and risk analysis.(3)The coordinated scheduling strategy for integrating CSP plants with solar prosumers considering thermal interactions and demand flexibilitiesCSP plants have good dispatchability,and they are located in areas with abundant solar irradiance.To develop solar prosumers who are equipped with photovoltaic(PV)and photo-thermal(PT)facilities around a CSP plant can make the best of solar irradiance and promote local solar energy accommodation.Based on the above background,a coordinated scheduling strategy for aggregating CSP plants and solar prosumers in the form of virtual power plants is proposed.In order to improve the coordinated scheduling flexibility and profit of the virtual power plant,the CSP plant concerned is equipped with a heat exchanger,which can be used to supply the heat and cooling loads of the solar prosumer.With the heat exchanger of the CSP plant as well as the electric,heating and cooling loads of the solar prosumer considered,the energy exchange mechanism and the complicated interactions of each component are modeled innovatively.Based on the modeling of each component,a mixed integer linear programming model is proposed considering thermal interactions and demand flexibilities so as to optimize the coordinated scheduling strategy of the CSP plant and solar prosumer.Simulation results based on multiple cases show that compared with the individual operation,the coordinated operation of CSP plant and solar prosumer can significantly improve the expected and day-ahead profits as well as the operational flexibilities of both the CSP plant and the solar prosumer.(4)The offering strategy and coordinated scheduling strategy for hybrid CSP-PV plants based on a bi-level stochastic modelWith the increasing maturity of the CSP technology and PV technology,the hybridization of,and coordination between,the CSP system and the PV system have practical significance and broad application prospects.Based on this background,a bi-level stochastic programming model is proposed so as to address the offering strategy and coordinated scheduling strategy optimization problem of a price-maker hybrid CSP-PV plant in the day-ahead electricity market.The upper-level of the bi-level model represents a profit maximization problem for the hybrid plant in the day-ahead electricity market.Since the CSP system of the hybrid CSP-PV plant is dispatchable,it can be used to reduce the volatility of the PV system.In order to maximize the coordinated scheduling profit for the hybrid plant,the upper-level fully considers and models the coordinated operation mechanism between the CSP and PV systems.The lower-level of the proposed bi-level model represents the day-ahead market clearing problem,which is linear programming.Since the formulated bi-level stochastic programming model is difficult to solve,it is transformed into a single-level mixed integer linear programming model based on the Karush Kuhn Tucker conditions of the lower-level linear programming problem and the strong duality theory.Simulations based on a regional Guangdong power grid verify the effectiveness of the proposed offering strategy and coordinated scheduling strategy of the hybrid CSP-PV plant.