Electric power systems are one of the fundamental pillars of modern society. Power systems require careful planning to ensure enough capacity for future electric demand, and simultaneously requiring meticulous operation to maintain a continuous supply-demand balance, which ensures a reliable and stable system. In this complex context, our electric systems are being decarbonized, moving away from fossil fuel based systems into more renewable ones, with larger contribution from wind and solar energy sources, reducing emissions of greenhouse gases which negatively contribute to climate change.

The consequences of this transition to renewable systems are multi-fold. First, renewable sources, like wind and solar, are variable and face uncertainty that complicates future planning of these energy systems. Second, the integration of Distributed Energy Resources (DERs), like rooftop photovoltaic systems, changes the paradigm of how our electric system operates, where power was once only generated in large generating units, and delivered via high-voltage transmission lines to the demand hubs—commonly large cities. Traditional energy sources, such as coal or gas, inject power via synchronous generators, however renewable resources are mostly interfaced into the grid using power electronics, that creates a fundamental difference in how electricity is produced. All of these changes are affecting our understanding of the grid, in multiple aspects and with different problems, which force us to reevaluate the tools and techniques used to study power systems.

This work focus on understanding the different challenges that are occurring in power systems due to the integration of variable Renewable Energy Sources (RESs), both in planning studies and day-to-day system operation. Thus, the main goal of this thesis is to study and analyze the changes in power systems with increasing shares of RESs, across multiple time- and space- scales.

The first part of this dissertation investigates dynamic simulations that are necessary for analyzing power system stability and dynamic response in the presence of Inverter-based Resources (IBRs). We introduce the Julia package PowerSimulationDynamics.jl to study the effects of load and line modeling when grid-forming and grid-following inverters. A discussion is presented between phasor-type and electromagnetic transient-type simulations. Results confirm that rooted assumptions in transient simulations may not be valid in systems with large presence of IBRs. By enabling PowerSimulationDynamics.jl as a flexible software tool, we discover that more detailed network and load models are becoming more necessary to properly assess stability of future power systems, as the integration of IBRs increases.

The second part focuses on DER investment in peer-to-peer and sharing economy setups. In particular, we propose an optimization model for distributed rooftop Photovoltaic (PV) investment to analyze how PV investment decisions can vary when consumers are subjected to different tariff schemes. Our results showcase how peer-to-peer tariff schemes, rather than traditional net-metering or feed-in-tariffs, can promote investment in rooftop PV.

Finally, the third part of this dissertation discuss the Switch expansion planning model, and specifically the effects of Electric Vehicles (EVs) flexibility in the future Western Electricity Coordinating Council (WECC) grid. Motivated by future decarbonization scenarios in California, we added a new EV module to the Switch model to study the influence of EV flexibility in installed capacity in WECC by 2050. Our results confirms that demand flexibility can reduce system's peak load to defer large investment decisions, achieving savings in both planning and operation costs.




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