# Optimal Configuration of Integrated Energy System Based on Energy-Conversion Interface
## 1 Introduction  
Lack of co-ordination and co-operation between traditional energy systems, such as power systems, natural-gas systems, and thermal systems, results in dissatisfying advantageous complementary and synergy energy benefits, because these energy systems are separately planned and operated. An Integrated Energy System (IES) has different energy forms collaborating in development, conversion, storage, transportation to meet the needs of terminal consumers. To improve energy efficiency and economic benefits, reduce environmental influence, and satisfy various energy demands at the same time, an IES utilizes advanced technologies for load forecasting, data processing, and innovative management in a certain area to co-ordinate, optimize, and intelligently manage multiple energy sources, such as electricity, natural gas, petroleum, and coal [1; 2; 3]. At present, the optimization problems of regional integrated energy systems can be divided into two categories: (1) optimizing the capacity and model of devices for a given regional IES and (2) optimizing energy flows for existing system topologies. For the former, [PERSON] et al. [4] co-ordinated the capacity of cogeneration units, absorption chillers, gas boilers, and other devices. [PERSON] et al. [5] used the genetic algorithm to optimize the location and capacity of IES power supply with the aim of minimizing system network loss. [PERSON] et al. [6] planned devices in building an integrated energy system and analyzed the economic benefits of combined heat and power (CHP). For the latter, [PERSON] et al. [7] proposed a mixed-integer nonlinear model to optimize the system with the lowest operating cost. [PERSON] et al. [8] estimated the thermal and electrical flows within the system by analyzing the thermoelectric-energy system model on the distribution side. [PERSON] et al. [9] optimizedthe device output of the system after dealing with load volatility by a Monte Carlo simulation. [PERSON] et al. [10] proposed an optimal dispatching model of a electrothermal multienergy system with power-to-gas (P2G) facilities on the basis of considering the characteristics of P2G facilities, power systems, natural-gas systems, and heating systems. [PERSON] et al. [11] put forward sensible thermal-energy storage (TES) systems that can shift a portion or all of it to off-peak periods to help reduce peak demand and electrical-grid stress. With the development of IES, an increasing number of scholars have begun to turn their focus to a comprehensive benefit evaluation of the system. [PERSON] et al. [12] considered the economic cost-saving rate, primary energy-saving rate, pollution-gas emission-reduction rate, and other indicators, analyzed the four types of buildings, and finally concluded that buildings with higher heat-to-electric ratio were more suitable for energy supply by way of combined cooling, heating, and power. [PERSON] et al. [13] established a comprehensive IES indicator system that included economic, environmental, and social benefits, and combined the entropy weight method and the analytic hierarchy process to give weights of the indicators. [PERSON] et al. [14] proposed a comprehensive energy-utilization assessment indicator for multienergy flow characteristics existing in IES to reflect the system's acceptance level and energy-efficiency level of renewable energy. In summary, there are two difficulties in the study of IES: (1) simultaneously planning the topology and IES device capacity or model, that is, IES planning starts from scratch; and (2) combining IES energy-dispatch optimization with planning devices to support each other. In response to the above problems, this paper introduces the concept of the Energy Conversion Interface (ECI) [15; 16; 17], which is applied to regional load-side IES, as shown in Figure 1. The ECI connects to a multienergy transmission network and the demand side, which enables the distribution and conversion of multiple energy sources and regulates energy flowing into the demand side.