This paper presents an algorithm to be implemented in a distribution management system (DMS) that is capable of managing an active distribution network (ADN). This goal is achieved by minimizing the cost of system operation, which is expressed in terms of cost of energy losses, cost of curtailed energy, cost of reactive support, and cost of shed energy. Furthermore, the exploitation of network reconfiguration in ADNs is investigated. This paper shows that the coordination of flexible network topology with the continuous active management of energy resources allows improving the efficiency of power delivery. The proposed DMS algorithm allows reducing the risk of energy loss rise, caused by the bigger generation capacity and the deferment of network upgrade that may be a follow-up of ADNs. The proposed method has been applied on a test network to verify the validity of the approach.

The interconnection of large amounts of nontraditional generation causes problems in a network designed for 'conventional' operation. A microgrid consists of a combination of generation sources, loads and energy storage interfaced through fast acting power electronics. The aim of operating microgrid sub-systems is to move away from considering DG as badly behaved system components, of which a limited amount can be tolerated in an area, to 'good citizens'. The paper is focused on the development of a novel energy management system (EMS) based on the application of neural networks (NN). The EMS is able to autonomously make decisions and determine hour by hour the correct dispatch of generators with the final goal of minimising the global energy costs. The application of the EMS to a small test case has showed significant saves in the global energy bill by using typical Italian energy and fuel price data

Nowadays, response to electricity consumption growth is mainly supported by efficiency; therefore, this is the new main goal in the development of electric distribution networks, which must fully comply with the system’s constraints. In recent decades, the issue of independent reactive power services, including the optimal placement of capacitors in the grid due to the restructuring of the electricity industry and the creation of a competitive electricity market, has received attention from related companies. In this context, a genetic algorithm is proposed for optimal planning of capacitor banks. A case study derived from a real network, considering the application of suitable daily profiles for loads and generators, to obtain a better representation of the electrical conditions, is discussed in the present paper. The results confirmed that some placement solutions can be obtained with a good compromise between costs and benefits; the adopted benefits are energy losses and power factor infringements, taking into account the network technical limits. The feasibility and effectiveness of the proposed algorithm for optimal placement and sizing of capacitor banks in distribution systems, with the definition of a suitable control pattern, have been proved.

The paper presents an advanced distribution management system capable to manage an active distribution network economically and safely. The DMS optimizes the power flows in the network, regulates the voltage profiles, acting on reactive flows and tap changers in substation, minimizes the energy losses, reconfigures the network, exploits storage devices and responsive loads in an integrated way. The optimization algorithm finds the optimal combination of such operation options to minimize system costs without causing violations of the technical constraints. The system costs include the energy losses, the cost of generation curtailment, the cost of reactive power, the cost of load shedding, and the cost of storages. The proposed method has been applied on a model test network to verify the validity of the approach.