Application of day-ahead optimal scheduling model based on multi-energy micro-grids with uncertainty in wind and solar energy and energy storage station

Hongxin Zhang
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Abstract

Multi-energy micro-grid has received widespread attention in the wave of continuous promotion and development of renewable energy. However, in the face of wind and solar uncertainty, its scheduling model needs to be further optimized. Therefore, a multi-energy micro-grid day-ahead optimal scheduling model was proposed to construct wind and solar uncertainty scenarios, and the application of energy storage station was considered. Multiple algorithms were introduced to propose the multi-energy micro-grid day-ahead optimal scheduling model. Finally, the research content was validated. The results confirmed that the wind and solar power output probability model could describe the characteristics of wind and solar power output at different periods. The generated scenes had a large number of wind speeds in the range of 1.5 m/s to 5 m/s, and the light intensity reached its peak at 14:00, which was consistent with the historical data of the research object. In addition, the total pre-scheduling cost of this optimized scheduling model within a day was 45.16×105 yuan, while the actual scheduling cost within a day was only 21.46×105 yuan. It saved costs by 41.65% and 44.95%, respectively, compared to the comparison algorithms. The research has driven innovation and optimization of the multi-energy micro-grid scheduling model. This provides a useful theoretical and practical basis for addressing the uncertainty of wind and solar energy and improving the economic efficiency of energy systems, which is crucial for the sustainable development of new energy.
基于风能、太阳能和储能站不确定性的多能源微电网的日前优化调度模型的应用
在可再生能源不断推广和发展的浪潮中,多能源微电网受到了广泛关注。然而,面对风能和太阳能的不确定性,其调度模型需要进一步优化。因此,本文提出了多能源微电网日前优化调度模型,构建了风能和太阳能不确定性情景,并考虑了储能站的应用。引入多种算法,提出了多能源微电网日前优化调度模型。最后,对研究内容进行了验证。结果证实,风能和太阳能发电输出概率模型能够描述不同时期风能和太阳能发电输出的特征。生成的场景中有大量风速在 1.5 米/秒至 5 米/秒之间的场景,光照强度在 14:00 达到峰值,这与研究对象的历史数据一致。此外,该优化调度模型一天内的预调度总成本为 45.16×105 元,而一天内的实际调度成本仅为 21.46×105 元。与对比算法相比,分别节约成本 41.65% 和 44.95%。该研究推动了多能源微电网调度模型的创新和优化。这为解决风能和太阳能的不确定性、提高能源系统的经济效益提供了有益的理论和实践依据,对新能源的可持续发展至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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