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The energy industry is undergoing a tremendous transformation from a centralized paradigm to a decentralized one with the employment of various distributed energy technologies and information technologies. Different from the traditional urban central heating system, the district heating system (DHS) with combined energy supply by multi-energy and multi-level energy stations is considered to be promising and can improve the efficiency and flexibility of the energy system. However, its complex system structure and multiple stakeholders bring new challenges to the operation optimization. Therefore, in the face of the DHS, two optimization models are applied in this study: 1) Independent Optimization Model (IOM): the operation strategies of each energy station are optimized independently, and each station then submits its own energy demand to the upper-level energy station; 2) Collaboration Optimization Model (COM): a model established for all energy stations for global optimization. A small number of existing papers on the operation optimization of such DHS have ignored the contradiction between social benefits and operators' profits, and do not study the gap between the two models. Therefore, this paper takes COM as the benchmark, quantitatively evaluating the potential of IOM for improving the overall energy efficiency under the interest game, and grasps the key reasons that restrict its energy saving potential, aiming to improve its comprehensive benefits. An actual DHS in China was used as a case study to explore the above problems. The results show that, although COM is more energy-saving, it loses 18.3% of the profits of energy integrators, and increases the profits of energy suppliers by 13.8%. Compared with COM, the primary energy consumption of IOM increases by 19.1%. For the results, this paper finally discusses whether it is possible to further improve the energy efficiency of IOM by adjusting the heat price without impairing the profits of the operators. The results indicate that the system's primary energy consumption reduces by 5.2% without impairing the profits of each operator. • The operation strategy of the multi-energy multi-level district heating system is optimized. • The contradiction between social benefits and operator profits is considered. • Independent optimization model and collaborative optimization model are established and quantitatively compared. • An actual case study is analyzed to explore why the energy saving potential of independent optimization is restricted. • The further improvement of independent optimization is discussed. [ABSTRACT FROM AUTHOR]

[Display omitted] The rapid development of urbanization has created high demand for central heating systems. This trend has led to an increase in energy consumption for central heating, which has made China's energy-saving transformation extremely difficult. However, the channel by which urbanization impacts and the future trends of energy consumption for central heating are still unclear. Therefore, this study employs the Logarithmic Mean Divisia Index (LMDI) method to decompose the effect of urbanization on changes in energy consumption for central heating during 2001–2019 in China. We investigate the contribution of urbanization from demographic, economic and spatial perspectives. Additionally, a scenario analysis is used to explore trends in energy consumption for central heating in different projected urbanization scenarios. The results show that urbanization has a positive impact on energy consumption for central heating, particularly in underdeveloped regions. Demographic urbanization has the strongest positive effect on energy consumption for central heating, followed by spatial urbanization and then economic urbanization. Compared with the expansion of area and economic development, population agglomeration will bring more energy consumption for central heating. The forecasting results indicate that energy consumption for central heating will reach 176–189 Mtce in 2030, which is approximately 1.4 times the current level. This work quantifies the energy consumption for central heating in the future under urbanization. The policy recommendations given at the end of the paper will provide a reference for the formulation of energy consumption for central heating. [ABSTRACT FROM AUTHOR]