期刊
APPLIED ENERGY
卷 294, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2021.116931
关键词
Integrated energy system; Solar energy; Power flow calculation; Energy system optimization; Mixed integrated linear programming; Demand response
资金
- National Natural Science Foundation of China [52008328]
- National Key Research and Development Project [2018YFD1100202]
- Science and Technology Department of Shaanxi Province [2020SF393, 2018ZDCXLSF0304]
- Education Department of Shaanxi [19JS041]
- State Key Laboratory of Green Building in Western China [LSZZ202009]
This study found that controlled demand responses can significantly improve the utilization of solar energy and reduce system costs in a solar-based integrated energy system. Users furthest away from the energy source play a crucial role in reducing system costs through demand response. In the system, voltage amplitude in the electricity network decreases the most during peak hours, while mass flow rates in the heating network increase with heating demand. Increasing the number of Photovoltaic/thermal panels decreases the cost of the entire solar-based IES.
Driven by the search for alternatives to fossil fuel, the ability to include solar energy into an integrated energy system (IES) has become increasingly important, especially in areas abundant with solar energy resources. However, a method to comprehensively and accurately analyze the energy-flow between the generation, network, and demand side in a district-level solar-based IES do not yet exist. This study uses both system optimization and power-flow calculations to analyze the energy interaction between the different sides (generation/network/demand) of a district solar-based IES in Tibet. To simplify the calculation, a decoupling optimization framework is developed that can independently solve problems sequentially from the demand side to the generation side, and the benefit caused by demand response is allocated between users using cooperative game theory. The results indicate: (i) Controlled demand responses can significantly improve the usage of solar energy and decrease system cost. (ii) The users furthest away from the energy source are most important to reduce system cost via demand response. (iii) Voltage amplitude in the electricity network drop most during peak hours, while the mass flow rates in the heating network increase with increasing heating demand. (iv) Increasing the number of Photovoltaic/thermal panels reduces the cost of the entire solar-based IES.
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