| Energy,as the cornerstone and driving force of modern societal development,has led to increasingly severe resource depletion and environmental pollution due to the unrestrained exploitation of traditional fossil energy sources,becoming a Sword of Damocles hanging over humanity’s head.Therefore,the construction of regional integrated energy systems has become an important measure for China to address energy crises and environmental pollution.Regional integrated energy systems integrate various distributed energy,energy storage,microgrids,and demand-side resources at the distribution network side,achieving complementary operation of electricity,gas,and heat,and promoting the consumption of renewable energy and improving energy utilization efficiency.While realizing its energy efficiency value,on one hand,the system can enhance the reliability of integrated energy supply through the conversion and self-healing control of different energy forms.On the other hand,the diversity of components and the massive scale of the system,as well as the high dependence on multi-energy coupling,pose significant risks to system security.The main manifestations are:①The interconnection of various energy sources provides a channel for fault propagation,becoming a prominent hidden danger to system safety.②The introduction of numerous components exponentially increases the difficulty of traditional reliability assessment.Based on the above,it is imperative to propose a model and algorithm with both assessment accuracy and efficiency.To this end,this paper carries out a reliability assessment study of regional integrated energy systems based on a multi-level Monte Carlo simulation algorithm.Firstly,this paper introduces the temporal characteristics of the Monte Carlo algorithm and derives the expression for the computational cost of simulation.Subsequently,the principles of the multi-level Monte Carlo simulation algorithm are presented.By discretizing the total time to form different sampling levels and satisfying the required accuracy,the optimal sampling quantity for each level is derived,and the algorithmic process of multi-level Monte Carlo simulation is explained.Secondly,the optimization target function for the system and the operating constraints of various energy sources are constructed,and separate models are developed to analyze the multiple thermal inertia effects in the reliability assessment process.The impacts of heat source start-up inertia,heat network transmission inertia,and building thermal inertia on system reliability are examined.Based on the differentiated energy flow modeling concept,optimization models targeting operational cost-effectiveness and equivalent load shedding are established,proposing steady-state operation optimization models and dynamic optimal load shedding models that incorporate multiple thermal inertia effects.Lastly,the reliability of the regional integrated energy system is assessed using the multi-level Monte Carlo simulation algorithm.The four-state reliability model of combined heat and power(CHP)units,multi-energy complementarity,and thermal inertia effects on system reliability are thoroughly analyzed and compared with other algorithms.The accuracy,sampling quantity,and evaluation time of the proposed algorithm are also verified in larger test systems.These results validate the effectiveness of the model and the efficiency of the algorithm,providing reference for system planning and design. |
