This present study offers a novel approach for the improvement of energy planning. This has become increasingly important as higher penetration of variable energy resources and increased interconnection between the different energy sectors require more detailed planning in terms of spatiotemporal modeling in comparison to the presently available approaches. In this study, we present a method that soft-linked the energy planning and power flow models, which enabled fast and reliable solving of optimization problems. A linear continuous optimization model was used for the energy system optimization and the non-linear problem for the power system analysis. The method is used to compare different energy planning scenarios; further, this also offers the possibility for implementation assessment of the proposed scenarios. The method was applied to interconnected islands for five different scenarios. It was determined that the detailed spatial approach resulted in 26.7% higher total system costs, 3.3 times lower battery capacity, and 14.9 MW higher renewable energy generation capacities installed than in the coarser spatial representation. Moreover, the results of the power flow model indicated that the highest voltage deviation was 16% higher than the nominal voltage level. This indicates the need for inclusion of implementation possibility assessments of energy planning scenarios.

本研究为改进能源规划提供了一种新方法。这变得越来越重要，因为与目前可用的方法相比，可变能源的更高渗透率和不同能源部门之间增加的互连需要在时空建模方面进行更详细的规划。在这项研究中，我们提出了一种将能源规划和潮流模型软链接的方法，该方法能够快速可靠地解决优化问题。能源系统优化采用线性连续优化模型，电力系统分析采用非线性问题。该方法用于比较不同的能源规划场景；此外，这也提供了对拟议情景进行实施评估的可能性。该方法应用于五个不同场景的互连岛屿。结果表明，与较粗略的空间表示相比，详细的空间方法导致总系统成本高 26.7%，电池容量低 3.3 倍，可再生能源发电装机容量高 14.9 MW。此外，潮流模型的结果表明，最高电压偏差比标称电压水平高 16%。这表明需要包括能源规划方案的实施可能性评估。安装的可再生能源发电容量比粗略空间表示高 9 兆瓦。此外，潮流模型的结果表明，最高电压偏差比标称电压水平高 16%。这表明需要包括能源规划方案的实施可能性评估。安装的可再生能源发电容量比粗略空间表示高 9 兆瓦。此外，潮流模型的结果表明，最高电压偏差比标称电压水平高 16%。这表明需要包括能源规划方案的实施可能性评估。