Control of a utility connected microgrid

This paper describes the control algorithm of a utility connected microgrid, based on independent control of active and reactive power (PQ control) and working in centralized operation mode. The microgrid under investigation is composed of three configurable units: a generation unit, a storage unit and a load. These units are interfaced with the microgrid through a Voltage Source Converter (VSC) and are controlled by the nodes of the communication system by means of IEC 61850. A set of tests have been conducted to evaluate the microgrid behavior.Postprint (published version

Quantifying flexibility in EV charging as DR potential : analysis of two real-world data sets

The increasing adoption of electric vehicles (EVs) presents both challenges and opportunities for the power grid, especially for distribution system operators (DSOs). The demand represented by EVs can be significant, but on the other hand, sojourn times of EVs could be longer than the time required to charge their batteries to the desired level (e.g., to cover the next trip). The latter observation means that the electrical load from EVs is characterized by a certain level of flexibility, which could be exploited for example in demand response (DR) approaches (e.g., to balance generation from renewable energy sources). This paper analyzes two data sets, one from a charging-at-home field trial in Flanders (about 8.5k charging sessions) and another from a large-scale EV public charging pole deployment in The Netherlands (more than 1M sessions). We rigorously analyze the collected data and quantify aforementioned flexibility: (1) we characterize the EV charging behavior by clustering the arrival and departure time combinations, identifying three behaviors (charging near home, charging near work, and park to charge), (2) we fit statistical models for the sojourn time, and flexibility (i.e., non-charging idle time) for each type of observed behavior, and (3) quantify the the potential of DR exploitation as the maximal load that could be achieved by coordinating EV charging for a given time of day t, continuously until t vertical bar Delt

Adaptive control for active distribution networks

Rise of the global environmental awareness and climate change impacts caused by greenhouse gases emissions brings about a revolution in the power and energy industries to reduce fossil fuels and promote low-carbon and renewable distributed generation (DG). The new dimensions, mainly encouraged by the governments’ legislative targets and incentives, have allowed the development of DG worldwide. In the U.K., renewable DG especially wind is being connected on distribution networks and ranges widely in scales. Despite the growing number of potential DG sites, the surplus generation present on the passive networks can lead to some technical problems. In particular, rural networks where wind farms exist are prone to voltage rise and line thermal constraints. In order to accommodate new DG and ensure security of supply and network reliability, active management to mitigate these issues are required. In addition, the duties to provide cost-effective DG connections at avoided expensive investment incurred from conventional solutions, e.g., reinforcement and maintain robust network are a major challenge for Distribution Network Operators (DNOs). This thesis endeavours to develop an adaptive control scheme that provides local and real-time management against voltage variations and line capacity overload at the point of wind connections on rural distribution networks. Taking into account maximising power exports and providing an economically-viable control scheme, the wind turbine’s capability, comprising reactive power control and active power curtailment, is used. Whilst the thesis concentrates on the decentralised control applying several different algorithms, in addition, semi-coordinated and centralised approaches that adopt on-load tap changing transformers’ regulation and Optimal Power Flow tool are developed. Comparisons of these approaches based upon measures, i.e., economics, DG penetration and performance are determined. As an outcome, the developed scheme can enable growing integration of renewable DG on distribution networks and can be seen as an interim solution for the DNOs towards Smart Distribution Networks