An integrated energy system (IES) contributes to improving energy efficiency and promoting sustainable energy development. For different dynamic characteristics of the system, such as demand/response schemes and complex coupling characteristics among energy sources, siting and sizing of multitype energy storage (MES) are very important for the economic operation of the IES. Considering the effect of the diversity of the IES on system reserve based on electricity, gas and heat systems in different scenarios, a two-stage MES optimal configuration model, considering the system reserve value, is proposed. In the first stage, to determine the location and charging/discharging strategies, a location choice model that minimizes the operating cost, considering the system reserve value, is proposed. In the second stage, a capacity choice model, to minimize the investment and maintenance cost of the MES, is proposed. Finally, an example is provided to verify the effectiveness of the MES configuration method in this paper in handling operational diversity and ensuring system reserve. Compared with the configuration method that disregards the system reserve value, the results show that the MES configuration method proposed in this paper can reduce the annual investment cost and operating cost and improve the system reserve value.

How to effectively use the multi-energy demand elasticity of users to bid in the multi-energy market and formulate multi-energy retail packages is an urgent problem which needs to be solved by integrated energy service providers (IESPs) to attract more users and reduce operating costs. This paper presents a unified clearing of electricity and natural gas based on a bi-level bidding and multi-energy retail price formulation method for IESPs considering multi-energy demand elasticity. First, we propose an operating structure of IESPs in the wholesale and retail energy markets. The multi-energy demand elasticity model of retail-side users and a retail price model for electricity, gas, heat and cooling are established. Secondly, a bi-level bidding model for IESPs considering multi-energy demand elasticity is established to provide IESPs with wholesale-side bidding decisions and retail-side energy retail price decisions. Finally, an example is given to verify the proposed method. The results show that the method improves the total social welfare of the electricity and natural gas markets by 7.99% and the profit of IESPs by 1.40%. It can reduce the variance of the electricity, gas, and cooling load curves, especially the reduction of the variance of the electricity load curve can which reach 79.90%. It can be seen that the research in this paper has a positive effect on repairing the limitations of integrated energy trading research and improving the economics of the operation of IESPs.