Abstract

The main outcome of this research is the development of a Probabilistic Impact Assessment methodology to comprehensively understand the effects of low carbon technologies (LCTs) in low voltage (LV) distribution networks and the potential solutions available to increase their adoption.The adoption of LCTs by domestic customers is an alternative to decreasing carbon emissions. Given that these customers are connected to LV distribution networks, these assets are likely to face the first impacts of LCTs. Thus, to quantify these problems a Monte Carlo-based Probabilistic Impact Assessment methodology is proposed in this Thesis. This methodology embeds the uncertainties related to four LCTs (PV, EHPs, µCHP and EVs). Penetration levels as a percentage of houses with a particular LCT, ranging from 0 to 100% in steps of 10%, are investigated. Five minute time-series profiles and three-phase four-wire LV networks are adopted. Performance metrics related to voltage and congestion are computed for each of the 100 simulations per penetration level. Given the probabilistic nature of the approach, results can be used by decision makers to determine the occurrence of problems according to an acceptable probability of technical issues.To implement the proposed methodology, electrical models of real LV networks and high resolution profiles for loads and LCTs are also developed. Due to the historic passive nature of LV circuits, many Distribution Network Operators (DNOs) have no model for them. In most cases, the information is limited to Geographic Information Systems (GIS) typically produced for asset management purposes and sometimes with connectivity issues. Hence, this Thesis develops a methodology to transform GIS data into suitable computer-based models. In addition, thousands of residential load, PV, µCHP, EHP and EV profiles are created. These daily profiles have a resolution of five minutes. To understand the average behaviour of LCTs and their relationship with load profiles, the average peak demand is calculated for different numbers of loads with and without each LCT.The Probabilistic Impact Assessment methodology is applied over 25 UK LV networks (i.e., 128 feeders) for the four LCTs under analysis. Findings show that about half of the studied feeders are capable of having 100% of the houses with a given LCT. A regression analysis is carried out per LCT, to identify the relationships between the first occurrence of problems and key feeder parameters (length, number of customers, etc.). These results can be translated into lookup tables that can help DNOs produce preliminary and quick estimates of the LCT impacts on a particular feeder without performing detailed studies. To increase the adoption of LCTs in the feeders with problems, four solutions are investigated: feeder reinforcement, three-phase connection of LCTs, loop connection of LV feeders and implementation of OLTCs (on-load tap changers) in LV networks. All these solutions are embedded in the Probabilistic Impact Assessment. The technical and economic benefits of each of the solutions are quantified for the 25 networks implemented.

Abstract

Most modern distribution networks are experiencing an energy evolution to satisfy the need of sustainable, secure and clean sources of energy. New technologies are driving this transition, including photovoltaics, energy storage systems and electric vehicles. The integration and deployment of these technologies in the distribution network is having a positive impact on system efficiency. However, their behaviour in the power system introduces technical challenges such as reverse power flow, voltage variation and other power quality issues. The integration of these technologies requires careful planning and operation to maintain or improve system stability and reliability. This work reviews the challenges imposed by deploying these low carbon technologies on low voltage systems. The main contributions of this study can be summarized as follows: Firstly, it generally reviews the solution methodologies and power management strategies applied in the distribution network in the presence of low carbon technologies. Secondly, it outlines some important facts and statistics about their deployment. Finally, it discusses the energy evolution of the Northern Ireland network highlighting challenges and solutions and providing recommendations for future research.