Multi-energy Optimal Scheduling For Power Systems With High Clean Energy Penetration In Southwest China

With the rapid development of hydropower in the past 20 years and wind-photovoltaic power in the past 10 years,several provincial power grids with high penetration of clean energy have been built in southwest China.However,limited by the huge system scale,complex operational constraints,and significant uncertainty of wind-photovoltaic power,two main challenges are presented for power systems with high clean energy penetration:the dimensionality curse,and the shortage of flexible regulation capacity.To cope with these issues,this paper focuses on multi-energy optimal scheduling to realize the optimal allocation of generation resources and improve power system operation efficiency.On the one hand,to address the curse of dimensionality,efficient mathematical optimization methods for dimension reduction are explored.On the other hand,from the aspects of wind-photovoltaic uncertainty modeling,deep peak regulation of thermal units,and spinning reserve scheduling,the shortage of flexible regulation capacity is studied.Main contents are introduced as follows:(1)To deal with the dimensionality curse in long-term optimization of large-scale hydropower system operations,a hybrid method based on decomposition-coordination and discrete differential dynamic programming is proposed.The basic principle of decompositioncoordination is to decouple linking hydraulic connections,split the whole system into independent subsystems,and coordinate the subsystems according to the solutions of subproblems and the objective of the whole system.After multiple iterations,optimal results can be obtained.The optimization of subsystems is implemented by discrete differential dynamic programming.In addition,three strategies are designed to improve the performance of the proposed method,including the decomposition strategy,the initial trajectory generation strategy,and the corridor generation strategy.Case study in a large-scale hydropower system in southwest China demonstrates the effectiveness of the proposed method.(2)To address the dimensionality curse in short-term hydrothermal scheduling,an improved proximal bundle method within the framework of Lagrangian relaxation is proposed.A dual problem is introduced through relaxing system-wide electrical constraints by Lagrangian relaxation.The dual problem is then solved by an improved proximal bundle method,which incorporates the expert system technique.By solving the dual problem,a near-optimal solution of the primal problem can be found.Case study in a large-scale hydrothermal system in Guizhou is implemented to demonstrate the effectiveness of the proposed method.Results in different cases indicate that the proposed method can reduce the total coal consumption and the computational time,demonstrating its practicability and robustness.(3)To alleviate the shortage of flexible generation capacity caused by the large-scale integration of wind power,short-term hydro-thermal-wind complementary scheduling considering wind power uncertainty and deep peak regulation of thermal units is studied.To represent the wind uncertainty,a novel scenario generation method is proposed,where higherorder Markov chain,multivariate Gaussian distribution,inverse transform sampling,backward reduction,and t-location scale distribution are coupled together.To explore the economic issues associated with deep peak regulation of thermal units,a three-stage peak regulation cost model is developed,including the stages of regular peak regulation,deep peak regulation without oil,and deep peak regulation with oil.Eventually,the wind scenarios and the three-stage peak regulation cost model of thermal units are incorporated into the short-term economic scheduling of hydro-thermal-wind systems to determine the optimal unit commitment.Case study in a hydro-thermal-wind system in Guizhou is conducted to demonstrate the effectiveness of the proposed method.Results indicate that the proposed method can reduce system operating costs and wind curtailment.(4)To handle the spinning reserve scheduling in hydro-thermal-wind-photovoltaic power systems,an improved formulation of spinning reserve based on the assembled mathematical techniques is proposed,which considers the ramping constraints of thermal units,the vibration zone constraints of hydropower units,and the hydropower disabled capacity.Moreover,with the scenario representation of wind-photovoltaic uncertainty,a stochastic programming model is developed to optimize the unit commitment and spinning reserve in hydro-thermal-windphotovoltaic systems.Case study in a hydro-thermal-wind-photovoltaic system in Guizhou demonstrates the potential of the proposed method in improving system economy and reliability.