Operational Analysis of Distribution Systems Featuring Large-scale Variable RES: Contributions of Energy Storage Systems and Switchable Capacitor Banks

In the last decade, the level of variable renewable energy sources (RESs) integrated in distribution network systems have been continuously growing. This adds more uncertainty to these systems, which also face many traditional sources of uncertainty, and those pertaining to other emerging technologies such as demand response and electric vehicles. As a result, distribution system operators are finding it increasingly difficult to maintain an optimal operation of such network systems. These challenges/limitations are, however, expected to be alleviated when distribution systems undergo the transformation process to smart grids, equipped with appropriate technologies such as energy storage systems (ESSs) and switchable capacitor banks (SCBs). These technologies offer more flexibility in the system, allowing effective management of the uncertainty and variability pertaining to most RESs (such as wind and solar PV power sources). This dissertation presents a stochastic mixed integer linear programming (S-MILP) model, aiming to optimally operate distribution network systems, featuring large-scale variable renewables, and alleviate the negative impacts of RESs on the overall performance of such systems by means of ESSs and SCBs. The optimization model is based on a linearized AC network model. Furthermore, the proposed operational model is formulated in a stochastic environment, particularly accounting for both variability and uncertainty pertaining to demand, wind and solar power productions. Such considerations allow one to make a more realistic analysis, under various operational conditions. The objective function of the proposed model is to minimize the sum of expected costs of operation, unserved power and emissions while meeting the most relevant technical and economic constraints. The analysis covers several issues, but with the perspective of maximizing the utilization level of variable RESs, and most importantly, without endangering the stability and integrity of the system as well as the quality of power delivered to the consumers. In this line, the dissertation presents an extensive analysis concerning the impacts of SCBs and ESSs of different efficiencies (either collectively or individually) in the system. In particular, the overall system performance in terms of costs, losses, voltages and energy mix has been extensively analysed, which is one of the main contributions of this dissertation. Simulation results indicate that strategically placed ESSs and SCBs can substantially increase the usage level of RES power, and simultaneously alleviate the negative impacts of RES intermittency in the considered system. For example, network losses are slashed by more than 70% and total system costs by 69%. Furthermore, the presence of ESSs and SCBs leads to as high as 96.1% share of RESs in the overall energy mix in the considered system. The energy imported through the substation in this case is limited to 3.9%, which means that the system operates in island mode for most of the time during the 24-hour period. This means that distribution network systems can go "carbon-free" by meeting a large portion of the demand using "cleaner" power locally produced