3,875 research outputs found

    Grid integration of intermittent renewable energy sources using price-responsive plug-in electric vehicles

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    Plug-in electric vehicles (PEVs) are expected to balance the fluctuation of re-newable energy sources (RES). To investigate the contribution of PEVs, the availability of mobile battery storage and the control mechanism for load man-agement are crucial. This study therefore combined the following: a stochastic model to determine mobility behavior, an optimization model to minimize vehicle charging costs and an agent-based electricity market equilibrium model to esti-mate variable electricity prices. The variable electricity prices are calculated based on marginal generation costs. Hence, because of the merit order effect, the electricity prices provide incentives to consume electricity when the supply of renewable generation is high. Depending on the price signals and mobility behavior, PEVs calculate a cost minimizing charging schedule and therefore balance the fluctuation of RES. The analysis shows that it is possible to limit the peak load using the applied control mechanism. The contribution of PEVs to improving the integration of intermittent renewable power generation into the grid depends on the characteristic of the RES generation profile. For the Ger-man 2030 scenario used here, the negative residual load was reduced by 15 to 22 percent and the additional consumption of negative residual load was be-tween 34 and 52 percent. --Plug-in electric vehicles,demand-side management,variable prices,intermittent generation

    Comparison of intelligent charging algorithms for electric vehicles to reduce peak load and demand variability in a distribution grid

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    A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium, price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage

    Review of trends and targets of complex systems for power system optimization

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    Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107

    Optimizing plug-in electric vehicle charging in interaction with a small office building

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    This paper considers the integration of plug-in electric vehicles (PEVs) in micro-grids. Extending a theoretical framework for mobile storage connection, the economic analysis here turns to the interactions of commuters and their driving behavior with office buildings. An illustrative example for a real office building is reported. The chosen system includes solar thermal, photovoltaic, combined heat and power generation as well as an array of plug-in electric vehicles with a combined aggregated capaci-ty of 864 kWh. With the benefit-sharing mechanism proposed here and idea-lized circumstances, estimated cost savings of 5% are possible. Different pricing schemes were applied which include flat rates, demand charges, as well as hourly variable final customer tariffs and their effects on the operation of intermittent storage were revealed and examined in detail. Because the plug-in electric vehicle connection coincides with peak heat and electricity loads as well as solar radiation, it is possible to shift energy demand as desired in order to realize cost savings. --Battery storage,building management systems,dispersed storage and generation,electric vehicles,load management,microgrid,optimization methods,power system economics,road vehicle electric propulsion

    Enabling Sustainable Public Transport in Smart Cities through Real-time Decision Support

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    The growing consumption of fossil fuels and its negative environmental consequences have been a major concern during the last few decades. In line with that, public transport operators face global pressure to replace diesel buses by battery-electric buses (BEBs) in many countries. However, BEBs need to be recharged several times throughout the day to avoid running out of energy due to their limited driving range and slow charging rate. Accordingly, operating BEBs is substantially more sensitive to unanticipated delays and excess energy consumption, which raises serious challenges with respect to charging schedules. Moreover, BEBs are only a truly sustainable alternative if they are powered by renewable energy generators (REGs), which have intermittent and uncertain generation. Thus, we design and propose a real-time decision support system to overcome these uncertainties and maximize the utilization of REGs and minimize the impact on the grid while guaranteeing a feasible operation for the BEBs
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