# A Multi-Level Fuzzy Evaluation Method for the Reliability of Integrated Energy Systems
## 1 Introduction  
Energy is the basis for human survival and development and is the lifeblood of the economy and society [1]. Since traditional fossil energy sources such as coal and oil are not renewable, improving energy utilization efficiency, developing new energy sources and strengthening the comprehensive utilization of renewable energy sources become the inevitable choice, to solve the contradiction between the growth of energy demand and energy shortage, energy utilization and environmental protection [2; 3]. An integrated energy system (IES) provides an effective solution for optimizing energy supply and improving energy efficiency [4] and the ecological environment [5]. An IES can efficiently integrate and utilize various energy units such as renewable energy sources (RES) units, combined heat and power (CHP) units, energy storage (ES) units and several others [6]. However, safety, reliability and economy are the most basic requirements for an integrated energy system, which is similar to the existing power supply, gas supply and cooling/heat supply [7]. While an IES improves energy efficiency, the interaction between different energy systems creates multiple operational risks [8; 9]. A reliability assessment can reflect the risk level of an energy supply interruption of the system with qualitative or quantitative indicators and, thus, guide the planning, operation and other production practice activities of integrated energy systems [10]. Due to economic and societal development, people have higher and higher requirements for the reliability of energy supply, and the integrated energy system is directly connected with various loads such as electricity, gas, cooling and heat physically. Thus, it is especially important to ensure the reliability ofthe integrated energy system, and it is very important to carry out its reliability assessment research [11]. Relevant studies on integrated energy systems have achieved preliminary results in the concept and framework of an IES, multi-energy flow analysis and calculation, modeling and simulation, planning and operation control and economic analysis and optimization. As shown in Table 1.  
However, the uncertainties in the \"source-grid-load-storage\" links within IES seriously affect the coordinated operation of the system, and the relevant research for the reliability assessment of integrated energy systems is still in the initial stage [22]. Achieving an accurate quantitative assessment of an IES's operational reliability helps to realize the collaborative planning and optimal regulation of smart energy. In recent years, with the introduction of a series of assessment methodologies, assessment methods have realized a transitional development process from single-indicator evaluation to multi-indicator evaluation. [PERSON] [23] proposed a reliability assessment method of an electricity-gas integrated system under attack. [PERSON] [24] used a Monte Carlo simulation combined with order statistics to assess the reliability of supply. [PERSON] [25] proposed a reliability assessment method of an IES considering gas-thermal inertia. [PERSON] [26] proposed a reliability evaluation method for CIESs based on a fault incidence matrix (FIM). An energy supply reliability assessment method based on a sequential Monte Carlo simulation was proposed in [PERSON]'s work [27]. As IES systems generally suffer from a lack of energy data, low model accuracy and their own force majeure, the combined evaluation method tends to overcome the shortcomings of the single evaluation method and has a superior performance in terms of applicability conditions and scalability. Therefore, this paper proposed an advanced multi-level fuzzy evaluation model based on combined empowerment for the reliability evaluation of an IES. The contributions of this paper were three-fold. 1. A weight analysis method combining analytic hierarchy process and entropy weight method as proposed.