Battery energy storage systems are fundamental components in microgrids operations, therefore it is important to adopt models suitable to properly evaluate the performance of these electrical systems. Different methodologies for battery modeling have been developed and tested in this work: (i) Empirical model, in which batteries are described by analytic expressions not based on electrochemical processes; (ii) Equivalent electrical circuit model, in which batteries are described in terms of electrical quantities. These approaches allow to adapt the model to different battery technologies: both the emerging Li-ion and the consolidated lead acid are considered in this paper. The proposed models are implemented in the software Poli.NRG, a Matlab based procedure for microgrid sizing developed by Energy Department of Politecnico di Milano. Simulations are based on a real case study relevant to a microgrid in a rural area: Ngarenanyuki Secondary School in Tanzania. The proposed methodology is used to design a new microgrid based on photovoltaic and energy storage system, comparing the results obtained adopting different modeling approaches and different technologies. Eventually, results are critically analyzed and discussed in order to compare accuracy, computational effort, costs and opportunities.
The scientific community is active in developing new models and methods to help reach the ambitious target set by UN SDGs7: universal access to electricity by 2030. Efficient planning of distribution networks is a complex and multivariate task, which is usually split into multiple subproblems to reduce the number of variables. The present work addresses the problem of optimal secondary substation siting, by means of different clustering techniques. In contrast with the majority of approaches found in the literature, which are devoted to the planning of MV grids in already electrified urban areas, this work focuses on greenfield planning in rural areas. K-means algorithm, hierarchical agglomerative clustering, and a method based on optimal weighted tree partitioning are adapted to the problem and run on two real case studies, with different population densities. The algorithms are compared in terms of different indicators useful to assess the feasibility of the solutions found. The algorithms have proven to be effective in addressing some of the crucial aspects of substations siting and to constitute relevant improvements to the classic K-means approach found in the literature. However, it is found that it is very challenging to conjugate an acceptable geographical span of the area served by a single substation with a substation power high enough to justify the installation when the load density is very low. In other words, well known standards adopted in industrialized countries do not fit with developing countries’ requirements.
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