São Miguel Island as a case study on a possible usage of Electric vehicle to store energy

Energy systems operation in isolated areas is frequently based on imported fossil fuels, which is a problem in different dimensions including environmental, economic and security of supply, with the latter being particularly relevant for any isolated system like Islands. Renewable energy is regarded as a solution to this problem, mainly in its transformation to electricity. This, however, excludes the impact of the transportation sector that represents a significant component of the imported fuels consumption. Other main limitation associated to renewable electricity consists on the need to increase the storage capacity that might attenuate the effect of intermittence of renewable energy sources and the disparity between supply and demand. In both problems - that are associated with renewable energy management - Plug-in Electric Vehicles (PEV) could be a part of the solution in that the use of vehicle to grid (V2G) technology can provide storage of electric energy during low demand times and use it to match the demand in peak hours and/or to avoid fossil fuel consumption.Therefore, some of the main questions are: could the large scale PEV penetration lead to increases in the fraction of electricity produced from renewable? Is the usage of PEV batteries as a storage system truly the best solution?São Miguel Island is the main electricity consumer in the whole Azores’s archipelago. There is no power connection to any major grid or even with other Islands. This work analyses a case study of isolated electricity grid, where energy systems modelling is used to assess to different roll out scenarios for large scale PEV penetration and discuss the possibility to increase the potential for the use of renewable electricity

Overloading protection of future low voltage distribution networks

The future distribution networks are going to be challenged by increasing penetration of distributed generators and simultaneously by increasing loading (inter alia heat pumps, air conditioners or electric vehicles). The increasing penetration of those appliances can escalate and jeopardize the functionality of current protection devices. Therefore, this article proposes a new overloading protection scheme applicable at low voltage level distribution networks to tackle this situation. The overloading problem is presented and the new protection scheme is demonstrated in a case study. The proposed protection should help to increase the flexibility of distribution networks, their safety and reliability

Smart transformer for mitigation of voltage fluctuations in MV networks

This paper describes the application of the smart medium to low voltage transformer to increase the flexibility of distribution networks, support the accommodation of distributed generation and to attenuate the voltage fluctuations originating from medium voltage network. The theoretical framework is set and three possible control strategies are investigated and their performance to mitigate voltage fluctuations is compared. The most suitable control strategy is chosen on basis of performance and suitability for practical implementation. In addition, a new application of voltage control in low voltage network is proposed

Future LV distribution network design and current practices in the Netherlands

The current distribution networks are going to be challenged by new developments on the side of generation and simultaneously also on the side of consumption. Therefore this paper provides an overview of LV network design aspects with emphasis on the implications of the future challenges on LV networks. The attention is especially given to the future aspect of the network design, substation automation, protection and mitigation of the issues accompanying distributed generation. The current operational and power quality measurements undertaken in LV distribution networks are presented as well as new additional measurements. The need to increase flexibility and assets utilization of LV networks is discussed together with the technical means enabling them. The outcomes related to the future LV network design are presented in conclusions

Theft detection and smart metering practices and expectations in the Netherlands

This paper provides insight into the illegal use or abstraction of electricity in the Netherlands. The importance and the economic aspects of theft detection are presented and the current practices and experiences are discussed. The paper also proposes a novel methodology for automated detection of illegal utilization of electricity in the future distribution networks equipped with smart metering infrastructure. The necessary data requirements for smart meters and distribution substations are defined, in order to unlock this feature in distribution network The paper also proposes the measures, which should be undertaken by the smart metering standard

Assessment of demand response possibilities by means of voltage control with intelligent MV/LV distribution substation

Demand response is considered as one of the possibilities, which should help to keep our power systems in balance of generation and production. To keep the system balanced will become more difficult, when large shares of electricity are generated from intermitted renewable resources. The availability and response speed of demand response are going to be the crucial factors enabling the integration into the future power system as a reliable option. Therefore, taking into account those factors, the possible demand response by the means of local voltage control is proposed in this paper. The constraints and the availability of the proposed new demand response tool are addressed in this paper and are underpinned with results from a field test experiment with experimental MV/LV substation allowing local implementation of voltage control

Theft detection and smart metering practices and expectations in the Netherlands

This paper provides insight into the illegal use or abstraction of electricity in the Netherlands. The importance and the economic aspects of theft detection are presented and the current practices and experiences are discussed. The paper also proposes a novel methodology for automated detection of illegal utilization of electricity in the future distribution networks equipped with smart metering infrastructure. The necessary data requirements for smart meters and distribution substations are defined, in order to unlock this feature in distribution network The paper also proposes the measures, which should be undertaken by the smart metering standard

Theft detection and smart metering practices and expectations in the Netherlands

This paper provides insight into the illegal use or abstraction of electricity in the Netherlands. The importance and the economic aspects of theft detection are presented and the current practices and experiences are discussed. The paper also proposes a novel methodology for automated detection of illegal utilization of electricity in the future distribution networks equipped with smart metering infrastructure. The necessary data requirements for smart meters and distribution substations are defined, in order to unlock this feature in distribution network The paper also proposes the measures, which should be undertaken by the smart metering standard

Power quality data evaluation in distribution networks based on data mining techniques

With the increasing amount of data available from the harmonic monitoring systems in the distribution grid, it is becoming more important to evaluate the harmonic data. This paper presents an algorithm using data mining technique, in particular mixture modeling based on the Minimum Message Length (MML) method, to classify the harmonic data into clusters and identify useful patterns within the data. The resulted clusters are applied to distinguish the sources of disturbances and the time schedule of the disturbances in the distribution grid. In addition, the C5.0 algorithm as a supervised learning is used to produce rules about how the measured data is classified into various clusters using decision tree technique. These generated rules can then be utilized to predict which cluster any new data belongs to without calculating again