AC Network Planning of Microgrids with Storage and Renewable Energy

Abstract

The goal of this research is to develop a methodology and computational tool that will help us design power systems that are more secure and reliable. In this thesis, we focus on identifying transmission line and reactive power resource reinforcements. Our study investigates both traditional networks and micro-grids that incorporate renewable energy sources like solar panels and batteries. The methodology is based on carrying out a DC optimal power flow (DC-OPF) at the time of peak demand, first on the base-case when all lines are available and next on a series of line outages, one at a time, to test the ability of the system to transmit real power from sources to load centers. Throughout the analysis, fictitious generators are installed at load nodes to represent load-sheds that may be needed in case lines are at their limits and no feasible solution is obtained. When fictitious generators are used, this is either due to a shortage of generation or to a transmission line limitation. If generation is less than demand plus spinning reserve, then it is concluded that the system needs generation reinforcement, which then added at the candidate nodes with the highest local marginal price (LMP). However, if the system has enough generation, then it is concluded that line reinforcements are needed. The line that is selected for reinforcement is the one that is observed to be at its limits when using a fictitious generator. Once the network is deemed adequate in terms of active power transmission, we analyze its base-case, i.e. when all lines are available, using an AC-OPF system, again at peak demand time throughout representative weeks of the year to determine its ability to supply the reactive power demands. If reactive power sources are not sufficient, then static-var-compensation (SVC) systems are added at nodes in a way to minimize the cost of operation. Our methodology is also applicable for micro-grid systems that entail renewable energy sources (e.g. PV panels) and storage units (e.g. batteries). However, the analysis of micro-grids with renewable energy sources requires identifying the specific hour that is most crucial, which varies depending on the characteristics of the renewable sources and storage sizes. In this case we need to study the system over the different seasons at several hours of the day and select the time at which the system is mostly stressed. Here several options are available for renewable energy sources and storage placement and sizes. The transmission reinforcement study will be carried out on several alternatives and the design to be implemented is the one that leads to a minimum levelized cost of electricity (LCOE) that include capital and operating costs throughout one year of operation. The computational tool that we have developed uses MATPOWER to carry out DC-OPF and AC-OPF analyses and is illustrated on the IEEE 5-bus, 30-bus, and 118-bus systems. We made adjustments to the 30-bus and estimated the transmission lines and transformers’ ratings of the 118-bus systems. By implementing these simulations, we verify the accuracy and effectiveness of our methodology.