Smart Grid Technologies in Europe: An Overview

The old electricity network infrastructure has proven to be inadequate, with respect to modern challenges such as alternative energy sources, electricity demand and energy saving policies. Moreover, Information and Communication Technologies (ICT) seem to have reached an adequate level of reliability and flexibility in order to support a new concept of electricity network—the smart grid. In this work, we will analyse the state-of-the-art of smart grids, in their technical, management, security, and optimization aspects. We will also provide a brief overview of the regulatory aspects involved in the development of a smart grid, mainly from the viewpoint of the European Unio

Impact on the Distribution System due to Plug-In Electric Vehicles and Changes in Electricity Usage

Replacing conventional vehicles by Plug-in Electric Vehicles (PEVs) would likely increase electricity demand and put higher stress on the electrical power system. This thesis presents an approach to evaluate the impact on electrical distribution systems (DSs) caused by charging PEVs and load management of heating loads. The approach considers both vehicle usage statistics and demographic data to estimate when PEVs could be charged in different parts of a DS.A case study was performed on a residential and a commercial part of the DS in Gothenburg. Three different control strategies for the charging were investigated, i.e. uncontrolled, loss-optimal and price-optimal strategies. The control strategies would have a significant effect on the timing of the charging, as well as the access of available infrastructure for charging.The results showed that if all vehicles were PEVs and charged uncontrolled, peak demand would increase by between 21 - 35% in the residential area and by between 1-3% in the commercial area. If customers were directly exposed to the spot price at the Nordic day-ahead market and would charge according to the price-optimal control strategy, peak power would increase by 78% for the residential area and 14% for the commercial area. If the charging were controlled according to the loss-optimal control strategy, the charging would be conducted during off-peak hours without increasing peak demand, even if all vehicles were PEVs.By controlling the heating loads in the residential area according to the price-optimal control strategy peak demand would increase by more than 80%, while peak demand would be reduced by almost 10% if the loss-optimal control strategy were applied

Impact on the Distribution System due to Plug-In Electric Vehicles and Changes in Electricity Usage

Replacing conventional vehicles by Plug-in Electric Vehicles (PEVs) would likely increase electricity demand and put higher stress on the electrical power system. This thesis presents an approach to evaluate the impact on electrical distribution systems (DSs) caused by charging PEVs and load management of heating loads. The approach considers both vehicle usage statistics and demographic data to estimate when PEVs could be charged in different parts of a DS.A case study was performed on a residential and a commercial part of the DS in Gothenburg. Three different control strategies for the charging were investigated, i.e. uncontrolled, loss-optimal and price-optimal strategies. The control strategies would have a significant effect on the timing of the charging, as well as the access of available infrastructure for charging.The results showed that if all vehicles were PEVs and charged uncontrolled, peak demand would increase by between 21 - 35% in the residential area and by between 1-3% in the commercial area. If customers were directly exposed to the spot price at the Nordic day-ahead market and would charge according to the price-optimal control strategy, peak power would increase by 78% for the residential area and 14% for the commercial area. If the charging were controlled according to the loss-optimal control strategy, the charging would be conducted during off-peak hours without increasing peak demand, even if all vehicles were PEVs.By controlling the heating loads in the residential area according to the price-optimal control strategy peak demand would increase by more than 80%, while peak demand would be reduced by almost 10% if the loss-optimal control strategy were applied

Методика и программное средство поиска аномалий в данных телеметрии солнечной электростанции на основе анализа нормализованных значений мощности

Objectives. In connection with the increase in the number of solar power plants, the automation of monitoring their performance becomes an urgent task. The search for anomalies in the operation of solar power plants is one of the main components of monitoring. The purpose of the study is to develop new methods and software algorithms for finding anomalies in the operation of solar panels based on the results of a digital twin created and trained according to the telemetry data of a solar power plant.Methods. The developed technique is based on statistical studies of deviations of power values at the point of maximum efficient operation of the solar panel calculated by the digital twin. In addition, a normalized value of the power in the maximum efficient operation of the solar panel was introduced for more accurate clustering and anomaly search.Results. Using the developed method of static search for half a year of observations, 18 anomalies were detected in the operation of the solar panels of the power plant. All cases are analyzed for the causes of anomalies in the operation of solar panels.Conclusion. It has been established that when using normalized power values in the analysis of deviations at the point of maximum power PN, it is possible to detect abnormal operation of individual panels. The level of deviation of the normalized values at the point of maximum power was calculated, indicating the presence of an anomaly in the operation of solar panel.Цели. В связи с увеличением количества солнечных электростанций актуальной задачей становится автоматизация мониторинга их работоспособности. Поиск аномалий в работе солнечных электростанций – одна из основных составляющих мониторинга. Цель исследования заключается в разработке новых методик и программных алгоритмов поиска аномалий в работе солнечных панелей на основе результатов работы цифрового двойника, созданного и обученного по данным телеметрии солнечной электростанции.Методы. Методика основана на статистических исследованиях отклонений значений мощности в точке максимально эффективной работы солнечной панели, рассчитанной цифровым двойником. Кроме того, введено нормализованное значение мощности максимально эффективной работы солнечной панели для более точной кластеризации и поиска аномалий.Результаты. С помощью разработанной методики поиска аномалий в данных телеметрии за полгода наблюдений обнаружены 18 аномалий в работе солнечных панелей электростанции. Все случаи проанализированы на предмет причин возникновения аномалий в работе солнечных панелей.Заключение. Установлено, что при использовании в анализе отклонений нормализованных значений мощностей в точке максимальной мощности PN возможно обнаружение аномальной работы отдельных панелей. Рассчитан уровень отклонения нормализованных значений в точке максимальной мощности, свидетельствующий о наличии аномалии в работе солнечной панели

Stochastic Operation Scheduling Model for a Swedish Prosumer with PV and BESS in Nordic Day-Ahead Electricity Market

In this paper, an optimal stochastic operation\ua0scheduling model is proposed for a prosumer owning\ua0photovoltaic (PV) facility coupled with a Battery Energy\ua0Storage System (BESS). The objective of the model is to\ua0maximize the prosumer’s expected profits. A two-stage\ua0stochastic mixed-integer nonlinear optimization (SMINLP)\ua0approach is used to cope with the parameters’ uncertainties.\ua0Artificial Neural Networks (ANN) are used to forecast themarkets’ prices and the standard scenario reduction\ua0algorithms are applied to handle the computational\ua0tractability of the problem. The model is applied to a case\ua0study using data from the Nordic electricity markets and\ua0historical PV production data from the Chalmers University\ua0of Technology campus, considering a scaled up 5MWp power\ua0capacity. The results show that the proposed approach could\ua0increase the revenue for the prosumer by up to 11.6% as\ua0compared to the case without any strategy. Furthermore, the\ua0sensitivity analysis of BESS’s size on the expected profit shows\ua0that increasing BESS size could lead to an increase in the net\ua0profits

Failure mode identification and end of life scenarios of offshore wind turbines: a review

In 2007, the EU established challenging goals for all Member States with the aim of obtaining 20% of their energy consumption from renewables, and offshore wind is expected to be among the renewable energy sources contributing highly towards achieving this target. Currently wind turbines are designed for a 25-year service life with the possibility of operational extension. Extending their efficient operation and increasing the overall electricity production will significantly increase the return on investment (ROI) and decrease the levelized cost of electricity (LCOE), considering that Capital Expenditure (CAPEX) will be distributed over a larger production output. The aim of this paper is to perform a detailed failure mode identification throughout the service life of offshore wind turbines and review the three most relevant end of life (EOL) scenarios: life extension, repowering and decommissioning. Life extension is considered the most desirable EOL scenario due to its profitability. It is believed that combining good inspection, operations and maintenance (O&M) strategies with the most up to date structural health monitoring and condition monitoring systems for detecting previously identified failure modes, will make life extension feasible. Nevertheless, for the cases where it is not feasible, other options such as repowering or decommissioning must be explored