The energy structure of the integrated energy system is diverse, and the prices and performances of different models of the same equipment vary greatly. How to determine a reasonable energy structure, equipment model combination and installed capacity in the planning stage is the premise to achieve cost savings in the operation stage. This paper studies the optimization model of "energy structure-equipment model-installed capacity" planning considering carbon dioxide emissions. Firstly, a case-based reasoning technique based on K-nearest-neighbors (KNN) to obtain the energy structure suitable for the proposed park is constructed. Considering the carbon emission ladder cost, and taking the lowest total life cycle cost as the optimization objective, the combination of ant colony algorithm and genetic algorithm is used to solve the optimal equipment model combination and the optimal installed capacity. Finally, the effectiveness of the proposed model in reducing costs is verified by example analysis.

Zero-carbon park is one of the key points in the practice of carbon neutralization and emission peak. However, in the context of the new power system, the electric energy supply of the park is characterized by the high integration of water, electricity, gas and heat, strong uncertainty of source-grid-load-storage, and complex and diverse primary and secondary topologies, which makes it difficult for the existing planning and design technologies to meet the application requirements. To this end, this paper discusses the current status, key technologies and future development trends of the optimal planning and design of zero-carbon parks. Firstly, the current status of research on zero-carbon parks and their planning and design technologies is explained from the perspective of energy interconnection. Secondly, the key technologies for optimal planning of zero-carbon parks, including energy-transportation system coupling, multi-energy complementarity, energy gradient utilization, demand response, and progressive planning, are summarized and explained. Finally, the future development trend of park planning is analyzed in terms of sharing concept, digital twin and cloud energy storage, and the technical challenges and research directions of park planning are indicated from the perspectives of concept application, disciplinary intersection, information integration and situational awareness, in order to provide stronger technical support for the development of zero-carbon parks for energy internet in China.

As a typical form of integrated energy systems，electro-thermal coupling systems have to be comprehensively and rationally planned， in order to meet the low-carbon transformation demands under the "dual carbon" target. Thus， a low-carbon planning model of a park-level integrated electric and heating system （PIEHS） with photovoltaic system is formulated which takes the carbon emission trading and green certificate trading costs as the optimization objectives. The model comprehensively considers the coupling characteristics of electric and thermal heterogeneous energy flows and the operating characteristics of distributed photovoltaic and energy storage devices. A P6H10 system is utilized to simulate and verify the proposed model in 3 scenarios. The results demonstrate that the carbon trading and green certificate trading mechanisms can effectively promote the planning of low-carbon devices such as distributed photovoltaic， energy storage， and CHP units， which facilitates the low-carbon transformation of the PIEHS. Finally， a sensitivity analysis is carried out on the carbon trading price and green certificate trading price， and the results show that the reasonable prices will reduce the total cost of the PIEHS.

The park integrated energy system can significantly improve its operation economy through multi-energy complementary. However, the uncertainty of the controllable resource response will bring challenges to the formulation of the day-ahead dispatching strategy. Thus, a day-ahead optimal economic dispatching strategy considering the integrated demand response and its uncertainty is proposed for the park integrated energy system. Firstly, the uncertainty of photovoltaic and load forecast power and the uncertainty of flexible load response are described by triangular fuzzy number, and a day-ahead dispatching model considering uncertainty is established. Then, in order to minimize the total operation cost of the system, the controllable resources of the supply and demand sides of the system are optimized. According to the fuzzy scheduling theory, fuzzy expectation constraints and fuzzy chance constraints are equivalently converted into their certainty forms for easy solution. Finally, the case analysis shows that the proposed strategy can further reduce the operating cost through integrated demand response; and the impact of fuzzy chance constraint confidence level on the system operating cost is analyzed.