Abstract-In this paper, the overvoltage problems that might arise from the integration of photovoltaic panels into low-voltage distribution networks is addressed. A distributed scheme is proposed that adjusts the reactive and active power output of inverters to prevent or alleviate such problems. The proposed scheme is model-free and makes use of limited communication between the controllers, in the form of a distress signal, only during emergency conditions. It prioritizes the use of reactive power, while active power curtailment is performed only as a last resort. The behavior of the scheme is studied using dynamic simulations on a single low-voltage feeder and on a larger network composed of 14 low-voltage feeders. Its performance is compared to a centralized scheme based on the solution of an Optimal Power Flow problem, whose objective function is to minimize the active power curtailment. The proposed scheme successfully mitigates overvoltage situations due to high photovoltaic penetration and performs almost as well as the Optimal Power Flow based solution with significantly less information and communication requirements.Index Terms-low-voltage photovoltaic systems, active distribution network management, voltage control

Abstract-When a smart meter, be it single-phase or threephase, is connected to a three-phase network, the phase(s) to which it is connected is (are) initially not known. This means that each of its measurements is not uniquely associated with a phase of the distribution network. This phase information is important because it can be used by Distribution System Operators to take actions in order to have a network that is more balanced.In this work, the correlation between the voltage measurements of the smart meters is used to identify the phases. To do so, the constrained k-means clustering method is first introduced as a reference, as it has been previously used for phase identification. A novel, automatic and effective method is then proposed to overcome the main drawback of the constrained k-means clustering, and improve the quality of the clustering. Indeed, it takes into account the underlying structure of the low-voltage distribution networks beneath the voltage measurements without a priori knowledge on the topology of the network. Both methods are analysed with real measurements from a distribution network in Belgium. The proposed algorithm shows superior performance in different settings, e.g. when the ratio of single-phase over threephase meters in the network is high, when the period over which the voltages are averaged is longer than one minute, etc.

Abstract:The emergence of electric vehicles (EVs), combined with the rise of renewable energy production capacities, will strongly impact the way electricity is produced, distributed and consumed in the very near future. This position paper focuses on the problem of optimizing charging strategies for a fleet of EVs in the context where a significant amount of electricity is generated by (distributed) renewable energy. It exposes how a mobile application may offer an efficient solution for addressing this problem. This app can play two main roles. Firstly, it would incite and help people to play a more active role in the energy sector by allowing photovoltaic (PV) panel owners to sell their electrical production directly to consumers, here the EVs' agents. Secondly, it would help distribution system operators (DSOs) or transmission system operators (TSOs) to modulate more efficiently the load by allowing them to influence EV charging behaviour in real time. Finally, the present paper advocates for the introduction of a two-sided market-type model between EV drivers and electricity producers.

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This paper highlights the importance of the knowledge of the phase identification for the different measurement points inside a low-voltage distribution network. Besides considering existing solutions, we propose a novel method for identifying the phases of the measurement devices, based exclusively on voltage measurement correlation. It relies on graph theory and the notion of maximum spanning tree. It has been tested on a real Belgian LV network, first with simulated unbalanced voltage for which it managed to correctly identify the phases of all measurement points, second, on preliminary data from a real measurement campaign for which it shows encouraging results.