Juan David Garcia Racines

The challenges of today’s energy landscape, marked by the search for sustainable development, the expansion of coverage, and the diversification of the energy matrix, allow for electricity systems focusing on renewable energy resources. Microgrids are considered an efficient paradigm for managing distributed renewable energy generation and providing reliable access to electricity in remote areas where the grid has not been extended. However, their planning is a complex task that requires a thorough understanding of various multi-dimensional aspects and decision-making scenarios to define feasible and sustainable alternatives. In this context, this study presents a new planning framework based on a two-stage strategy. The strategy seeks to optimize the capacity of generation resources, considering the microgrid’s operational knowledge in various scenarios and aspects related to its sustainability. The framework was evaluated through a case of planning a microgrid for a remote community in Vaupés, Colombia, considering the local energy potential and demand requirements. Twenty optimized alternatives were identified based on the best compromise levels achieved for a set of performance criteria in the technical, economic, environmental, and social dimensions.

The growing interest in deploying photovoltaic systems and achieving their benefits as sustainable energy supplier raises the need to seek reliable medium-term and long-term operations with optimal performance and efficient use of economic resources. Cleaning scheduling is one of the activities that can positively impact performance. This work proposes a methodological framework to define the optimal scheduling of the cleaning activities of photovoltaic systems. The framework integrates a forecast model of the performance ratio, including the environmental variables’ effect. In addition, an economic analysis involving the economic losses and maintenance costs of cleaning is used. This framework is applied to a case study of a photovoltaic system located in Yumbo, Colombia. Based on the historical data on irradiance, active energy, temperature, rainfall, and wind speed, the obtained forecast model of the photovoltaic system’s performance ratio in a 60-day horizon has a mean absolute percentage error lesser of than 11%. The next cleaning date is forecasted to be beyond the horizon in a 19-day range, which will decrease as time goes by. This framework was applied to historical data and compared to actual cleaning dates performed by the utility company. The results show a loss of USD 33.616 due to unnecessary, early, or late cleaning activities.

The smart grid involves a set of interconnected ecosystems applications (electrical, electronic, computer and communications), so the modernization is needed of information, security and infrastructure systems that monitor, control and manage them are increasingly evident. The upgrading smart grid process is a complex interaction between different alternatives and adequate selection of assessment criteria, where tangible and intangible items must be chosen with little information or with uncertain data. This work presents a framework within the context of the Smart Grid, to provide electric energy companies with a tool for planning the modernization of their generation, transmission, distribution and marketing systems. The planning of the modernization networks under the smart grid concepts is represented based on Smart Grid Architecture Model (SGAM) reference model. Furthermore, it presents how to integrate a pilot project (Smart Grid information source) into the SGAM reference model, through the identification of key performance indicators defining it. Multi-criteria analysis (MCA) combined with cost/benefit analysis (CBA) concept is explored, providing a novel insight into the approaches used in smart grid research applied at a case study: a distribution grid for rural smart grids.