Conacyt-Instituto Nacional de Electricidad y Energías Limpias, Cuernavaca, Mexico.
Instituto Nacional de Electricidad y Energías Limpias, Cuernavaca, Mexico.
PLoS One. 2020 Mar 12;15(3):e0230122. doi: 10.1371/journal.pone.0230122. eCollection 2020.
Nowadays, the global energy system is in a transition phase, in which the integration of renewable energy is among the main requirements for attenuating climate change. Wind power is a major alternative to supply clean energy; hence, its widespread penetration is being pursued in all end-use sectors. In particular, it is currently noteworthy to analyze the feasibility of deploying small-scale wind power technology to provide cleaner and cheaper energy in the residential sector. As a first step, a technical assessment must be carried out to provide crucial information to intensive energy consumers, providers of small-scale wind power technology, electric energy distribution utilities, and any other party, to help them decide whether or not to deploy small-scale wind turbines. With this aim, we propose to perform such an analysis using a suitable probabilistic paradigm to solve complex decision-making problems with uncertainty, namely Bayesian Intelligence, since wind resources and energy demands are intermittent variables, properly characterized by probability distribution functions. Then, the problem of determining the technical feasibility can be formulated as an investigation into whether or not small-scale wind turbine technology can produce enough energy to cover the excess demand of intensive energy residential consumers to get off high-priced tariffs. For this purpose, we introduce a novel model based on probabilistic reasoning to assess the suitability of small-scale wind turbine technology to produce the said energy, taking into consideration the availability of wind resources and the energy pricing structure. To demonstrate the usefulness and performance of the proposed model, we consider a case study of deploying 5 and 10 kW wind turbines and analyze the feasibility of their implementation in Mexico, where the energy pricing structure and scattered wind resource availability pose difficult challenges.
如今，全球能源系统正处于转型阶段，可再生能源的整合是减缓气候变化的主要要求之一。风力发电是供应清洁能源的主要替代方式；因此，正在所有终端使用部门中追求其广泛渗透。特别是，目前值得分析部署小型风力发电技术在住宅部门提供更清洁和更便宜能源的可行性。作为第一步，必须进行技术评估，为密集型能源消费者、小型风力发电技术提供商、电能分配公用事业公司以及任何其他方提供关键信息，以帮助他们决定是否部署小型风力涡轮机。为此，我们建议使用合适的概率范例来执行这样的分析，以解决具有不确定性的复杂决策问题，即贝叶斯智能，因为风力资源和能源需求是间歇性变量，适当地由概率分布函数来描述。然后，确定技术可行性的问题可以表述为调查小型风力涡轮机技术是否能够产生足够的能源来覆盖密集型能源住宅消费者的超额需求，以摆脱高价关税。为此，我们引入了一种基于概率推理的新模型，以评估小型风力涡轮机技术生产所述能源的适宜性，同时考虑到风力资源的可用性和能源定价结构。为了演示所提出模型的有用性和性能，我们考虑了部署 5 千瓦和 10 千瓦风力涡轮机的案例研究，并分析了在墨西哥实施它们的可行性，那里的能源定价结构和分散的风力资源可用性带来了困难的挑战。
