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

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Energy management systems for the operation of\ud distributed energy resources, distribution storage devices, and\ud responsive loads will be embedded in distribution management\ud systems (DMSs) as advanced functions that rely on accurate input\ud data and fast communication signals. For a proper DMS design,\ud the impact of the state estimation uncertainties and of the communication\ud system delays should be evaluated. The paper presents\ud an integrated software package for the cyber-physical simulation\ud of DMS taking into account the accuracy of state estimation and\ud measurements. The effectiveness of a wireless Wi-Max communication\ud system has been tested on the rural Italian representative\ud network produced by the research project ATLANTIDE. Results\ud proved the need of cosimulation packages in modern distribution\ud systems

This paper proposes an optimization algorithm that is suitable for choosing the optimal number and position of the measurement devices in distribution state estimation (DSE) procedures used in modern electric distribution networks. The algorithm is based on the techniques of dynamic programming, and its goal is to guarantee both the minimum cost and the accuracy required for the measured data needed to operate management and control issues, such as energy dispatch and protection coordination. Both the uncertainty introduced by the measurement devices and the tolerance in the knowledge of the network parameters (line impedances) are taken into account in the proposed approach. The aggregation of the quantities to be measured in a few measurement points has been favored to reduce the overall cost of the measurement system. Random changes in the loads are considered to establish adequate reference conditions for the tests. Tests relevant to real distribution networks are presented to show the validity of the proposed approach. The results emphasize how both the influence of the tolerance on the network parameters and the cost of the measurement system can dramatically be minimized by suitably choosing the algorithm to be implemented to solve the DSE problem

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