Research on Power Generation Energy Sources Structure Adjustment Algorithm Based on HyperGraph
American Journal of Energy Engineering
Volume 7, Issue 2, June 2019, Pages: 49-54
Received: Jun. 5, 2019;
Accepted: Jun. 29, 2019;
Published: Jul. 10, 2019
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Chunhua Qiu, Department of Electrical Engineering, Tianjin University, Tianjin, China
Shaoyun Ge, Department of Electrical Engineering, Tianjin University, Tianjin, China
Ting Yang, Department of Electrical Engineering, Tianjin University, Tianjin, China
Jun Wei, Mining Department, Guizhou University, Guiyang, China
Guoxing Xiang, Department of Hydropower Engineering, Wuhan University, Wuhan, China
Nowadays, the energy structure is gradually changing to clean power generation. Clean energy mainly includes renewable energy and part of non-renewable energy. Non-renewable energy is depleting day by day, showing a shrinking trend. Renewable energy is not affected by energy shortage, and is the focus of future development. How to ensure the sustainable and healthy development of clean energy, it is necessary to adjust the existing power generation energy structure scientifically and rationally. In this paper, the theory of hypergraph is introduced to cluster the optimal combination information of clean energy, and a hypergraph model of power generation energy structure adjustment is established. The problem of replacing fossil energy in power generation energy consumption with clean energy is solved as the original objective. By mapping the generation energy structure adjustment with hypergraph, the problem of generation energy structure adjustment is transformed into the problem of solving hypergraph path. By using the two-point hyperpath algorithm, an optimal path for the development of clean power generation, reducing the proportion of fossil energy power generation, and gradually converting to clean energy is obtained. The application of hypergraph algorithm in the structural adjustment of power generation is of great significance to promote the diversification of power generation energy, especially in the clean development, low-carbon development and green development of the power industry.
Research on Power Generation Energy Sources Structure Adjustment Algorithm Based on HyperGraph, American Journal of Energy Engineering.
Vol. 7, No. 2,
2019, pp. 49-54.
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