The paper focuses on the day-ahead operational planning of a grid-connected local energy community (LEC) consisting of an internal low-voltage network and several prosumers including generation units, battery storage systems, and local loads. In order to preserve, as much as possible, the confidentiality of the features of prosumers' equipment and the production and load forecasts, the problem is addressed by designing a specific distributed procedure based on the alternating direction method of multipliers (ADMM). The distributed procedure calculates the scheduling of the available energy resources to limit the balancing action of the external grid and allocates the internal network losses to the various power transactions. Results obtained for various case studies are compared with those obtained by a centralized optimization approach. The results confirm that, in the considered LEC framework, each of the prosumers achieves a reduction in costs or increases revenues in case it participates to the LEC with respect to the case in which it can only transact with an external energy provider. Index Terms-alternating direction method of multipliers, distributed optimization, energy management system, local energy community, mixed integer linear programming, mixed integer quadratic programming.

The paper deals with the day-ahead operational planning of a grid-connected local energy community (LEC) consisting of several prosumers each equipped with generating units, loads and battery energy storage units. The prosumers are connected to the same low-voltage distribution network. In order to preserve, as much as possible, the confidentiality of the features and forecast of prosumers' equipment, the problem is addressed by designing a specific distributed procedure based on the alternating direction method of multipliers (ADMM). The distributed procedure provides the scheduling of the batteries to limit the balancing action of the external grid. Results obtained for various case studies are compared with those obtained by a centralized approach. The values of the objective function, the profiles of the power exchanged with the utility grid and the profile of the energy stored in the batteries provided by the distributed approach are in close agreement with those calculated by the centralized one. Index Terms--alternating direction method of multipliers, distributed optimization, energy management, local energy community, mixed integer programming, mixed integer quadratic programming. I.

The paper deals with the day-ahead optimization of the operation of a local energy system consisting of photovoltaic units, energy storage systems and loads aimed at minimizing the electricity procurement cost. The local energy system may refer either to a small industrial site or to a residential neighborhood. Two mixed integer linear programming models are adopted, each for a different representation of the battery: a simple energy balance constraint and the Kinetic Battery Model. The paper describes the generation of the scenarios, the construction of the scenario tree and the intraday decision-making procedure based on the solution of the multistage stochastic programming. Moreover, the daily energy procurement costs calculated by using the stochastic programming approach are compared with those calculated by using the Monte Carlo method. The comparison is repeated for two different sizes of the battery and for two load profiles.

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