The transportation sector is a largest emitter of greenhouse gases in the U.S., accounting for 28.6% of all 2016 emissions, the majority of which come from the passenger vehicle fleet [1,2]. One major technology that is being investigated by researchers, planners, and policy makers to help lower the emissions from the transportation sector is the plug-in electric vehicle (PEV). The focus of this work is to investigate and model the impacts of increased levels of PEVs on the regional electric power grid and on the net change in CO2 emissions due to the decrease tailpipe emissions and the increase in electricity generation under current emissions caps. The study scope includes all of New England and New York state, modeled as one system of electricity supply and demand, which includes the estimated 2030 baseline demand and the cur- rent generation capacity plus increased renewable capacity to meet state Renewable Portfolio Standard targets for 2030. The models presented here include fully electric vehicles and plug-in hybrids, public charging infrastructure scenarios, hourly charging demand, solar and wind generation and capacity factors, and real-world travel derived from the 2016-2017 National Household Travel Survey. We make certain assumptions, informed by the literature, with the goal of creating a modeling methodology to improve the estimation of hourly PEV charging demand for input into regional electric sector dispatch models. The methodology included novel stochastic processes, considered seasonal and weekday versus weekend differences in travel, and did not force the PEV battery state-of-charge to be full at any specific time of day. The results support the need for public charging infrastructure, specifically at workplaces, with the “work” infrastructure scenario shifting more of the unmanaged charging demand to daylight hours when solar generation could be utilized. Workplace charging accounted for 40% of all non-home charging demand in the scenario where charging infrastructure was “universally” available. Under the increased renewable fuel portfolio, the reduction in average CO2 emissions ranged from 90 to 92% for the vehicles converted from ICEV to PEV. The total emissions reduced for 15% PEV penetration and universally available charging infrastructure was 5.85 million metric tons, 5.27% of system-wide emissions. The results support the premise of plug-in electric vehicles being an important strategy for the reduction of CO2 emissions in our study region. Future investigation into the extent of reductions possible with both the optimization of charging schedules through pricing or other mechanisms and the modeling of grid level energy storage is warranted. Additional model development should include a sensitivity analysis of the PEV charging demand model parameters, and better data on the charging behavior of PEV owners as they continue to penetrate the market at higher rates.

Replacing conventional generation with renewable generation in power systems is essential for reducing CO2 emissions. It is important to know how effective renewables are in reducing CO2 emissions. Since CO2 reduction cannot be measured directly, different methods have been used to estimate reduction of CO2 emissions. The two most common methods are econometric models and dispatch models. Econometric models apply regression analysis using historical data for CO2 emissions, power production, and electricity demand to estimate CO2 reduction. On the other hand, dispatch models are detailed optimization simulations of power systems where the objective is to calculate the cost-optimal dispatch of the power plants. The dispatch model finds the optimal dispatch for a base case and counterfactual case. In the counterfactual case, the renewable generation in the system is modified. From the difference in CO2 emissions between the two cases, an estimation of CO2 reduction can be made. Recent studies have shown that dispatch models and econometric models can give different estimations of CO2 reduction. However, these studies did not include several factors that can increase CO2 emissions, such as; transmission constraints, security requirements, and non-linear factors. Examples of non-linear factors are; minimum dispatched energy of generating units, start up emissions, minimum up- and downtime for generating units, and energy generated during start-up and shut-down. This thesis examines if there is an agreement between econometric models and dispatch models for estimating CO2 reduction and if the agreement changes when more non-linear factors are considered. To examine these questions a systematic comparison has been done. Two econometric models are constructed, a linear econometric model and a polynomial linear econometric model. The polynomial linear econometric model is constructed to take into account non-linear factors. Eight dispatch models are constructed with increasing modelling complexity. Four model versions do not include any non-linear factors and four include non-linear factors. The results showed that the agreement between econometric and dispatch models is fairly good, except for versions that contain transmission constraints. The simulation is executed in a fictional test system that is not dimensioned for wind power generation at the given buses. Therefore is possible that transmission constraints impacts the reduction of CO2 too heavily. Furthermore, the results show that the non-linear factors contribute to CO2 emission and consequently lower the estimation of CO2 reduction. However, no conclusion can be made if the agreement between econometric and dispatch models divert when more non-linear factors are considered. / Världens utsläpp av CO2 måste minska för att inte jorden ska drabbas av drastiska klimatförändringar som temperaturhöjningar. Idag står elproduktionen för ungefär en fjärdedel av världens utsläpp av CO2. Därmed måste dagens elproduktion och elkraftsystem minska sina utsläpp av CO2 . Ett viktigt verktyg för att kraftsystem ska minska sina utsläpp av CO2 är expansion av förnybar elproduktion. Dock så går det inte att mäta direkt hur mycket CO2-utsläppen minskar vid expansion av förnybar elproduktion. Därför har flera olika estimeringsmetoder utvecklats för att uppskatta CO2-reduktion. De två vanligaste metoderna är ekonometriska modeller och produktionssimuleringsmodeller. Ekonometriska modeller använder sig av regressionsanalys med historiska tidsserier som; CO2 -utsläpp, kraftproduktion och elförbrukning för att uppskata CO2 -minskningen. Produktionssimuleringsmodeller är detaljerade optimeringssimuleringar där avsikten är att beräkna den kostoptimala användningen av kraftverk i ett system. Tidigare studier har visat att ekonometriska modeller och produktionssimuleringsmodeller kan ge olika uppskattningar av CO2 -reduktion. Dock har produktionssimuleringsmodellerna i studierna inte tagit hänsyn till flera faktorer som kan påverka CO2-utsläppen, som t.ex. överföringsbegränsningar, säkerhetsbegräsningar och icke-linjära faktorer. Exempel på icke-linjära faktorer är minimal produktion av energi för varje kraftverk, CO2 -utsläpp vi uppstart, minimal upp- och nertid och produktion vid uppstart och nedstänging för varje generator. Den här uppsatsen undersöker om de två metoderna ekonometriska modeller och produktionssimuleringsmodeller liknade uppskattningar av CO2 -reduktion och hur överrenstämmelsen mellan modellerna påverkas när man beaktar icke-linjära faktorer. För att försöka besvara dessa frågor har en systematisk jämförelse utförts. Två ekonometriska modeller har konstruerats, en linjär och en polynom-linjär ekonometrisk modell. Den polynom-linjära ekonometriska modellen tar i beaktning icke-linjära faktorer. Åtta produktionssimuleringsmodeller har konstruerats och de åtta olika modellerna har formulerats i en ökande ordning av noggrannhet. Fyra av modellerna tar inte hänsyn till några icke-linjära faktorer och fyra av modellerrna tar hänsyn till icke-linjära faktorer.

The UK’s decarbonisation strategy to increasingly electrify heating and transport will change the demand requirement on the electricity system. Additionally, under a climate change future, it is projected that the decarbonised grid will need to be able to operate under higher average temperatures in the UK, increasing the need for comfort cooling during summer and leading to additional electricity demand. These new demands will result in greater variation between minimum and peak demand as well as a significant increase in overall demand. Concurrently, supply-side decarbonisation programmes may lead to more intermittent renewables such as wind, PV, tidal and wave, elevating variability in electricity generation. Coupled with the anticipated higher variation in demand this brings on several challenges in operating the electricity grid. In order to characterise these challenges this research develops a bespoke electricity dispatch model which builds on hourly models of demand and generation. The hourly demand profiles are based on a high electrification of heating, transport and cooling coupled with future temperatures premised on the UKCP09 high emission scenario climate projections. The demand profiles show a significant increase in peak demand by 2050 reaching 194 GW, mainly due to summer cooling loads which contribute 70% of the demand. The cumulative CO2 emissions budgets of the GB power sector that are consistent with avoiding global climate change to 2°C are used to develop two low carbon generation scenarios distinguished by the amount of intermittent renewable generation technologies. The dispatch model tests the capability of generation scenarios with the use of hourly generation models in meeting future demand profiles out to 2050.The outputs from dispatch model indicate that there are shortages and excesses of generation relative to demand from 2030 onwards. The variability analysis outlines low and high generation periods from intermittent technologies along with the pace at which intermittent generation increases or decreases within an hour. The characterisation of variability analysis reveals the type of reserve capacity or smart solutions that are required to maintain the security of electricity supply. The solutions that could address the challenges quantified from the model outputs in operating a decarbonised GB electricity grid are explored using expert interviews. The analysis of the stakeholder interviews suggests smart grid solutions that include technologies as well as changes in operational procedures in order to enhance the operational resilience of the grid. Active Network Management through monitoring and control, demand management, storage systems and interconnectors are proposed to address challenges arising from varying demand and generation variability.