Stevanato Nicolò, Rocco Matteo V, Giuliani Matteo, Castelletti Andrea, Colombo Emanuela
Department of Energy, Politecnico di Milano, Milan, Italy.
Fondazione Eni Enrico Mattei, Milan, Italy.
PLoS One. 2021 Dec 2;16(12):e0259876. doi: 10.1371/journal.pone.0259876. eCollection 2021.
In state-of-the-art energy systems modelling, reservoir hydropower is represented as any other thermal power plant: energy production is constrained by the plant's installed capacity and a capacity factor calibrated on the energy produced in previous years. Natural water resource variability across different temporal scales and the subsequent filtering effect of water storage mass balances are not accounted for, leading to biased optimal power dispatch strategies. In this work, we aim at introducing a novelty in the field by advancing the representation of reservoir hydropower generation in energy systems modelling by explicitly including the most relevant hydrological constraints, such as time-dependent water availability, hydraulic head, evaporation losses, and cascade releases. This advanced characterization is implemented in an open-source energy modelling framework. The improved model is then demonstrated on the Zambezi River Basin in the South Africa Power Pool. The basin has an estimated hydropower potential of 20,000 megawatts (MW) of which about 5,000 MW has been already developed. Results show a better alignment of electricity production with observed data, with a reduction of estimated hydropower production up to 35% with respect to the baseline Calliope implementation. These improvements are useful to support hydropower management and planning capacity expansion in countries richly endowed with water resource or that are already strongly relying on hydropower for electricity production.
在最先进的能源系统建模中，水库水电与其他任何热电厂一样被表示：能源生产受到电厂装机容量和根据前几年发电量校准的容量因子的限制。不同时间尺度上的天然水资源变异性以及随后蓄水质量平衡的过滤效应未被考虑在内，导致最优电力调度策略存在偏差。在这项工作中，我们旨在通过在能源系统建模中推进水库水电发电的表示方式来引入该领域的一项创新，即明确纳入最相关的水文约束条件，如随时间变化的可用水量、水头、蒸发损失和梯级放水。这种先进的表征在一个开源能源建模框架中得以实现。然后在南非电力池的赞比西河流域对改进后的模型进行了演示。该流域估计水电潜力为20000兆瓦（MW），其中约5000兆瓦已得到开发。结果表明，电力生产与观测数据的匹配度更高，相对于基线Calliope实施情况，估计水电产量减少了高达35%。这些改进有助于支持水资源丰富或已严重依赖水电进行电力生产的国家的水电管理和规划能力扩展。
