Browsing by Keyword "info:eu-repo/grantAgreement/EC/H2020/646531/EU/Real proven solutions to enable active demand and distributed generation flexible integration, through a fully controllable LOW Voltage and medium voltage distribution grid/UPGRID"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Adopting smart meter events as key data for low-voltage network operation(2017-10-01) García Prado, Jesús; González, Ana; Riaño, Sandra; SISTEMAS FOTOVOLTAICOSA pioneering analysis of smart meter events aimed to enhance low-voltage (LV) network operation by the detection of voltage deviations, repetitive incidents or even outage prevention is presented. The main challenge of using smart meters events is the vast amount of data collected: the average of events gathered in an area per day is around 40% higher than the number of smart meters installed. To transform this huge quantity of information in network improvements, a set of strategies have been undertaken. The core purpose of this analysis is to establish a more rational and automated processing of smart meter events, aimed to embrace them as key information for network operation.Item Optimal Phase Swapping in Low Voltage Distribution Networks Based on Smart Meter Data and Optimization Heuristics(Springer Verlag, 2017) Mendia, Izaskun; Gil-López, Sergio; Del Ser, Javier; Bordagaray, Ana González; Prado, Jesús García; Vélez, Manuel; Del Ser, Javier; Tecnalia Research & Innovation; IAIn this paper a modified version of the Harmony Search algorithm is proposed as a novel tool for phase swapping in Low Voltage Distribution Networks where the objective is to determine to which phase each load should be connected in order to reduce the unbalance when all phases are added into the neutral conductor. Unbalanced loads deteriorate power quality and increase costs of investment and operation. A correct assignment is a direct, effective alternative to prevent voltage peaks and network outages. The main contribution of this paper is the proposal of an optimization model for allocating phases consumers according to their individual consumption in the network of low-voltage distribution considering mono and bi-phase connections using real hourly load patterns, which implies that the computational complexity of the defined combinatorial optimization problem is heavily increased. For this purpose a novel metric function is defined in the proposed scheme. The performance of the HS algorithm has been compared with classical Genetic Algorithm. Presented results show that HS outperforms GA not only on terms of quality but on the convergence rate, reducing the computational complexity of the proposed scheme while provide mono and bi phase connections.