Abstract The replacement of fossil fuels for producing energy with renewable sources is crucial to limit the climate change effects. However, the unpredictable nature of renewables, like sun and wind, complicates their integration within the power systems. This problem can be faced with the introduction of Hybrid Renewable Energy Systems (HRESs) where several energy sources can be incorporated. A key aspect is the assessment of the HRES configuration, which is fundamental to obtain a feasible system from both technical and economic points of view. In this paper, a novel Mixed Integer Linear Programming (MILP) optimization algorithm has been developed to design a tool capable of assessing the optimal sizing of a HRES. The algorithm has been applied to a real case study of a mountain hut located in South-Tyrol (Italy) with a hybrid system composed by solar, wind and diesel generators together with a battery storage. The algorithm compares several scenarios providing the optimal configurations of the HRES, which are characterized by different costs and energy deficits. This tool helps engineers to identify the best trade-off between costs and energy deficits in the planning phase of a HRES, still granting the demand of the users as well as the constraints.

中文翻译：

---

混合可再生能源系统的最佳规模：高度可变的可再生能源数据选择的重要性

摘要 用可再生能源替代化石燃料生产能源对于限制气候变化影响至关重要。然而，太阳能和风能等可再生能源的不可预测性使它们在电力系统中的整合变得复杂。引入混合可再生能源系统 (HRES) 时可能会遇到这个问题，其中可以合并多种能源。一个关键方面是对 HRES 配置的评估，这是从技术和经济角度获得可行系统的基础。在本文中，开发了一种新颖的混合整数线性规划 (MILP) 优化算法来设计一种能够评估 HRES 最佳大小的工具。该算法已应用于位于南蒂罗尔（意大利）的山间小屋的真实案例研究，该小屋具有由太阳能、风能和柴油发电机以及电池存储组成的混合系统。该算法比较了几种提供 HRES 最佳配置的场景，这些场景的特点是不同的成本和能量赤字。该工具可帮助工程师在 HRES 的规划阶段确定成本和能源赤字之间的最佳权衡，同时满足用户的需求和限制条件。