Abstract
Taking Hunnan District of Shenyang City as an example, this paper investigates 32 government agencies, 17 tertiary first-class hospitals, and 15 colleges and universities in Hunnan region and analyzes the energy consumption characteristics of three types of public institutions. Through the use of DeST energy consumption software to simulate the energy consumption of three types of public institutions, combined with the load density method to predict the total energy demand of hospitals, universities, and government agencies in Hunnan area and the MARKAL model coupling mechanism, the coupling model of active and passive energy suitable for public institutions is presented. According to the forecast results of energy demand, combined with the energy consumption structure and energy conversion efficiency, the energy supply of each subitem of the public institution was solved and the energy supply of the public institutions in Hunnan District was optimized in accordance with the relevant constraints. Through calculation, it is found that by 2020, the passive energy supply of public institutions in Hunnan District will account for 19.79% and active energy sources such as coal and petroleum will still be the main type of energy used by public institutions. Based on the research on the active and passive energy coupling supply of public institutions in Hunnan District, the active and passive energy coupling model and algorithm of public institutions constructed can provide a reference basis for the active and passive energy coupling utilization of public institutions in China.
Highlights
At this stage, the energy consumption per unit area of public institutions in China is high and energy consumption is growing rapidly
Note: Table 9 data is taken from Shenyang Statistical Yearbook. rough the assumption of population growth in Hunnan District, the assumption of urbanization rate and the future trends of the first, second, and third industrial structures in Hunnan and the terminal energy demand of public institutions during the optimization period can be predicted
Taking the Hunnan District of Shenyang City as an example, this paper studies the active and passive energy coupling of public institutions and builds a model of active and passive energy coupling of public institutions
Summary
The energy consumption per unit area of public institutions in China is high and energy consumption is growing rapidly. China’s “ irteenth Five-Year Plan for Public Institutions” aims to use energy resource consumption in 2015 as a base. With the development of the economy, the number of public institutions in China will continue to increase, the energy consumption demand of public institutions will continue to increase, and insufficient supply of energy resources will restrict the development of our economy. Because this paper mainly uses Hunnan District of Shenyang City as an example to coordinate and optimize the supply of active and passive energy in public institutions, this paper first studies relevant optimization methods at home and abroad and investigates the current status of public institution research. E algorithm has good performance and can quickly find a highly suitable solution [6]. Meyarivan et al developed a series of algorithms for Mathematical Problems in Engineering
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