The increasing penetration of PV into the distribution grid leads to congestion, causing detrimental power quality issues. Moreover, the multiple small photovoltaic (PV) systems and battery energy storage systems (BESSs) result in increasing conversion losses. A low-voltage DC (LVDC) backbone to interconnect these assets would decrease the conversion losses and is a promising solution for a more optimal integration of PV systems. The multiple small PV systems can be replaced by shared assets with large common PV installations and a large BESS. Sharing renewable energy and aggregation are activities that are stimulated by the European Commission and lead to a substantial benefit in terms of self-consumption index (SCI) and self-sufficiency index (SSI). In this study, the benefit of an LVDC backbone is investigated compared to using a low-voltage AC (LVAC) system. It is found that the cable losses increase by 0.9 percent points and the conversion losses decrease by 12 percent points compared to the traditional low-voltage AC (LVAC) system. The SCI increases by 2 percent points and the SSI increases by 6 percent points compared to using an LVAC system with shared meter. It is shown that an LVDC backbone is only beneficial with a PV penetration level of 65% and that the BESS can be reduced by 22% for the same SSI.
This paper presents an in-depth comparison of the benefits and limitations of using a low-voltage DC (LVDC) microgrid versus an AC microgrid with regard to the integration of low-carbon technologies. To this end, a novel approach for charging electric vehicles (EVs) on low-voltage distribution networks by utilizing an LVDC backbone is discussed. The global aim of the conducted study is to investigate the overall energy losses as well as voltage stability problems on DC and AC microgrids. Both architectures are assessed and compared to each other by performing a power flow analysis. Along this line, an actual low-voltage distribution network with various penetration levels of EVs, combined with photovoltaic (PV) systems and battery energy storage systems is considered. Obtained results indicate significant power quality improvements in voltage imbalances and conversion losses thanks to the proposed backbone. Moreover, the study concludes with a discussion of the impact level of EVs and PVs penetration degrees on energy efficiency, besides charging power levels’ impact on local self-consumption reduction of the studied system. The outcomes of the study can provide extensive insights for hybrid microgrid and EV charging infrastructure designers in a holistic manner in all aspects.
Photovoltaic (PV) installations located in the northern hemisphere must be oriented to the south in order to obtain maximal annual yield. This is mainly driven by the remuneration mechanisms which incentivize maximal energy production to a certain extent. Nowadays, such support mechanisms are declining or even phased out in many countries. Hence, self-consuming the produced energy is getting more viable. In order to match better the load demand pattern, the azimuth angle of a PV installation could be changed or oriented towards multiple directions. This article investigates the benefits of PV installations facing other directionsthan the south. Therefore, the Hay & Davies transposition model has been used to calculate the in-plane irradiance, as it is found in the literature to be the most accurate for non-south faced PV installations. In order to determine the benefit, a large dataset of real measured consumption profiles has been used and then divided according to their annual consumption. Large consumers with an oversized east/west-oriented PV installation especially take advantage. The self-sufficiency index (SSI) is found to increase with almost 0.94 percent points, while the self-consumption index (SCI) increases with 6.46 percent points. The peak reduction is assessed by calculating the annual moving average of the month peaks. It is found that this moving average month peak reduction is marginal. Lastly, the reduction in storage capacity is found to be not that significant, although in terms of battery utilization it is found that the number of discharge cycles is reduced with 6%.
This paper proposes a novel feature construction methodology aiming at both clustering yearly load profiles of low-voltage consumers, as well as investigating the stochastic nature of their peak demands. These load profiles describe the electricity consumption over a one-year period, allowing the study of seasonal dependence. The clustering of load curves has been extensively studied in literature, where clustering of daily or weekly load curves based on temporal features has received the most research attention. The proposed feature construction aims at generating a new set of variables that can be used in machine learning applications, stepping away from traditional, high dimensional, chronological feature sets. This paper presents a novel feature set based on two types of features: respectively the consumption time window on a daily and weekly basis, and the time of occurrence of peak demands. An analytic expression for the load duration curve is validated and leveraged in order to define the the region that has to be considered as peak demand region. The clustering results using the proposed set of features on a dataset of measured Flemish consumers at 15-min resolution are evaluated and interpreted, where special attention is given to the stochastic nature of the peak demands.
The European Commission introduced recently the new concept of energy communities which are aiming at accelerating the energy transition. RE/SOURCED, which stands for Renewable Energy SOlutions for URban communities based on Circular Economy policies and Dc backbones, is a project that aims at implementing a renewable energy community at the former power plant site in Belgium. One of the novel aspects of the project is the interconnection of the different energy storage systems and renewable energy sources by means of a LVDC backbone. In this paper, a power flow analysis of the LVDC backbone is performed in order to determine the appropriate cable size. Based on this analyses the energy losses are computed for a LVDC backbone architecture. Subsequently, the benefit in terms of energy savings, self-consumption and self-sufficiency is investigated compared to the traditional grid architecture.
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