Browsing by Subject "Vehicle to Grid"

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    Analysis of Engineering, Socio-Political and Market Aspects of Energy Policies Using Examples from Carbon Tax, Market Diffusion of Combined Heat and Power and Vehicle-to-Grid Services
    (2019-05) Bhandari, Vivek
    Excelling at formulating, analyzing and implementing effective energy policies requires a holistic understanding of its economic, socio-political and engineering aspects. However, both in academia and in practice, one (or more) of these perspectives is often neglected or understudied. Considering this, this dissertation studies three examples of energy policies focusing on a lesser known, and often-neglected aspect. The examples are compiled as three independent, self-contained essays. The first essay analyses the power engineering aspect of a carbon tax. Using U.S. market practices and policies as an example, a carbon tax is operationalized in a wholesale electricity market. Its effect is examined on the Institute of Electrical and Electronics Engineers (IEEE) Reliability Test System 28-bus model examining both transmission congestion and other energy policies. The results show how a carbon tax affects emission savings, and revenue streams for generators, loads and the government. They indicate that such interactions could lead to ineffective emissions reduction. The second essay analyzes the socio-political aspect of Combined Heat and Power (CHP). By using expert elicitation and document analysis, the non-financial barriers for CHP are analyzed. The results show three significant barriers a) the business model of the electrical utility b) negative subjective impressions and c) challenges in allocating the risks and benefits. The third essay analyzes the economic/market aspect of Vehicle-to-Grid (V2G). Model of a centralized V2G system is developed and applied to the 2015 wholesale electricity market in Texas (Houston Hub). Three scenarios are examined. In the first scenario, electric vehicles are paid based on a fixed retail market price; in the second, they are paid a time-varying retail market price; in the third, the virtual power plant shares 50% of its total reward with the participating vehicles. The results demonstrate that, while this system is always financially profitable to the virtual power plant and the system operator gets grid services, the electric vehicles could lose money. Further, results show that these vehicles with lower per unit output-battery cost could lose more money because of extensive battery over-use and insufficient reward at current market prices. The results have several important policy implications. Study of a power-engineering aspect of a carbon tax reveals that due to operational interactions, in the short term, a carbon tax might not reduce emissions. Study of the socio-political issue of CHP reveals that economically viable technologies may sometimes not gain traction in the market because of internal business models and negative subjective impressions. Similarly, the study of the economic/market aspect of a V2G reveals that lower battery costs, subsidies for participation, and more rewarding market products could all make V2G more economically viable to the vehicle owners. More importantly, these results also imply thorough analysis would reveal the intricacies and allow the policymaker to understand the impacts of such a policy holistically.
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    Optimized Scheduling Of Electric Vehicle Charging And Discharging In A Vehicle-To-Grid System
    (2015-06) Hosseinpour, Shima
    The increase in electric vehicle (EV) demand and the associated electricity load on the power network have made researchers to start working on managing and controlling EVs' connection time to the electricity grid. Vehicle to grid concept was introduced to enable EVs to connect to the grid and discharge their extra electricity to the network so that the utility company could use it for regulation purposes. In this thesis, offline and online scheduling optimization models are developed for EV charging and discharging. The objective of the optimization models is to maximize the satisfaction of EV customers. Customer satisfaction is incorporated using different factors through multiple scenarios. In the offline model, all EVs and grid information are known for the V2G management to decide the scheduling for EVs. Mixed integer linear programming is used to solve the offline model. The result of the offline model is the optimum solution the scheduling problem could get. On the other hand in the online model, which is a more realistic case, EVs arrival and departure times and their parameters are not identified in advance. For this model, rolling horizon optimization is used in the online scheduling algorithm. Applying rolling horizon enables the author to get the optimal solution for the online model. Mixed integer linear programing is linked with a MATLAB algorithm to solve the online scheduling model. A numerical example, including a large number of EVs in a parking lot is generated to test the efficacy of both proposed models.