Optimal planning of collective photovoltaic arrays in energy communities through a multi-cut benders’ decomposition strategy

With the deregulation and the urgent necessity of decarbonizing the electricity sector, end users have been empowered to actively partake in the operation of the system. In this context, energy communities arise as a regulatory framework that allows aggregating a group of domestic consumers (or prosumers) in order to share own resources such as storage or photovoltaics. However, such collective assets should be properly designed in order to exploit them in an optimal way as well as avoid oversizing components, which may result in higher expenditures economically harmful. This new paradigm calls for developing proper computational tools for optimally planning and operating energy communities. In this paper, a novel tool for optimally planning collective photovoltaic arrays in cooperative energy communities is developed. This planning problem encompasses continuous and binary variables, which are evaluated over long time horizons and characterized through representative sets. These features make the problem computationally costly or even unaffordable for average machines. To overcome this issue, a novel solution strategy based on the multi-cut Benders’ decomposition is developed. The new proposal exploits the particular structure of the multi-year problem to produce dense cuts strategies that rely on multiple computational benefits, while the optimization framework allows including long-time parameters (such as panel degradation) in an intuitive way. The new approach is tested on a number of scenarios, comparing it with the traditional solution method without applying decomposition. Results reveals that the original intractable problem becomes manageable by average machines when applying the proposed decomposition technique, thus demonstrating its practicability and importance. In addition, the results obtained serve to highlight the importance of increasing local generation in energy communities, in order to reduce the dependency of the grid as well as reducing the total energy cost for users. In particular, the total project cost reduces by 19 % in our particular case study. Other aspects have been also highlighted, as the importance of photovoltaics to increase the exportable capacity of the community observing an increment of 96 % in the exportable energy in our case study. In this sense, the developed tool results valuable for community planners, allowing them to take decisions on pursuing to improve the economy and efficiency of the entire community.