Bio: Lijuan Song is an academic researcher from Shenyang Jianzhu University. The author has contributed to research in topics: China & Sustainable development. The author has co-authored 1 publications.
01 Aug 2020
TL;DR: Based on the development status of green building economy in China, Wang et al. as discussed by the authors expound the meaning of Green building economy and analyzes the necessity of its development, combined with the current situation of China and developed countries, they summarized and analyzed the shortcomings of the green building economic development in China.
Abstract: During the 13th Five Year Plan period, China's economic development has entered a new stage. “Green,” “low carbon,” and “ecology” in the construction field have become the global development trend. Based on the development status of green building economy in China, this paper expounds the meaning of green building economy and analyzes the necessity of its development. Then, combined with the current situation of China and developed countries, this paper summarizes and analyzes the shortcomings of green building economic development in China. Finally, through the method of investigation and literature review, it gives the opinions of sustainable development of green building economy. This paper has practical significance.
14 Jan 2023
TL;DR: In this article , a slime mold algorithm combined with an optimal neighborhood perturbation (OPSMA) is proposed to optimize the load distribution of thermal power units, where the cost of price-based demand response (PBDR) is considered.
Abstract: Despite the rapid development of clean energy, thermal power generation has remained the majority in recent years. The economy and stability of power grid operation are affected by load optimization and the allocation of thermal power units. When the load distribution of thermal power units is solved, the traditional method considers the cost of energy consumption of the thermal power unit, which ignores the cost of load response on the user side of the optimization algorithm. In the traditional algorithm, there are issues with poor convergence and it is easy to encounter problems of local optimal solutions. Therefore, a slime mould algorithm combined with optimal neighborhood perturbation (OPSMA) is proposed in this paper. OPSMA is used to optimize the load distribution of thermal power units. In addition, the paper considers the cost of price-based demand response (PBDR) and establishes a mathematical model of the optimization objective, where the sum of the cost of energy consumption and the cost of PBDR is the minimum. Finally, by comparing OPSMA algorithm with other intelligent algorithms, the practicability of OPSMA algorithm in unit load allocation is verified. The results show that the scheme formulated by OPSMA is optimal, and the economical operation of the unit is realized.