The present paper considers some technical issues related to the energy blockchain paradigm applied to microgrids. In particular, what appears from the study is that the superposition of energy transactions in a microgrid creates a variation of the power losses in all the branches of the microgrid. Traditional power losses allocation in distribution systems takes into account only generators while, in this work, a real-time attribution of power losses to each transaction involving one generator and one load node is done by defining some suitable indices. Besides, the presence of P-V nodes increases the level of reactive flows and provides a more complex technical perspective. For this reason, reactive power generation for voltage support at P-V nodes poses a further problem of reactive power flow exchange, that is worth of investigation in future works in order to define a possible way of remuneration. The experimental section of the paper considers a Medium Voltage microgrid and two different operational scenarios.

In this paper, an optimal power dispatch problem on a 24-h basis for distribution systems with distributed energy resources (DER) also including directly controlled shiftable loads is presented. In the literature, the optimal energy management problems in smart grids (SGs) where such types of loads exist are formulated using integer or mixed integer variables. In this paper, a new formulation of shiftable loads is employed. Such formulation allows reduction in the number of optimization variables and the adoption of real valued optimization methods such as the one proposed in this paper. The method applied is a novel nature-inspired multiobjective optimization algorithm based on an original extension of a glowworm swarm particles optimization algorithm, with algorithmic enhancements to treat multiple objective formulations. The performance of the algorithm is compared to the NSGA-II on the considered power systems application.

In this paper, a generalized double-shell framework for the optimal design of systems managed optimally according to different criteria is developed. Optimal design is traditionally carried out by means of minimum capital and management cost formulations and does not typically consider optimized operation. In this paper, the optimized multiobjective management is explicitly considered into the design formulation. The quality of each design solution is indeed defined by the evaluation of operational costs and capital costs. Besides, the assessment of the operational costs term is deduced by means of the solution of a multiobjective optimization problem. Each design solution is evaluated using the outcomes of a multiobjective optimization run: a Pareto hyper-surface in the n-dimensional space of the operational objectives. In the literature, commonly the evaluation of each design solution is carried out based on an approximate evaluation of the operational costs, not considering the real multiobjective optimized management. In this paper, such assessment is carried out using a suitable convergence indicator typically used for multiobjective optimization algorithms. The application is devoted to the problem of optimal sizing of distributed energy resources in medium voltage or low voltage microgrids. For this problem, the identification of the multiple operational impacts comes along with the solution of the optimal unit commitment of distributed generators. After the introductory section, the problem formulation is presented and an interesting application of the considered approach to the design of distributed energy sources in a microgrid is shown.