Improving power grid transient stability by plug-in electric vehicles

Plug-in electric vehicles (PEVs) can serve in discharge mode as distributed energy and power resources operating as vehicle-to-grid (V2G) devices and in charge mode as loads or grid-to-vehicle (G2V) devices. It has been documented that PEVs serving as V2G systems can offer possible backup for renewable power sources, can provide reactive power support, active power regulation, load balancing, peak load shaving,% and current harmonic filtering, can provide ancillary services as frequency control and spinning reserves, can improve grid efficiency, stability, reliability, and generation dispatch, can reduce utility operating costs and can generate revenue. Here we show that PEVs can even improve power grid transient stability, that is, stability when the power grid is subjected to large disturbances, including bus faults, generator and branch tripping, and sudden large load changes. A control strategy that regulates the power output of a fleet of PEVs based on the speed of generator turbines is proposed and tested on the New England 10-unit 39-bus power system. By regulating the power output of the PEVs we show that (1) speed and voltage fluctuations resulting from large disturbances can be significantly reduced up to 5 times, and (2) the critical clearing time can be extended by 20-40%. Overall, the PEVs control strategy makes the power grid more robust.Comment: 15 pages, 4 figures, submitted to New Journal of Physic

Supporting transient stability in future highly distributed power systems

Incorporating a substantial volume of microgeneration (consumer-led rather than centrally planed) within a system that is not designed for such a paradigm could lead to conflicts in the operating strategies of the new and existing centralised generation technologies. So it becomes vital for such substantial amounts of microgeneration among other decentralised resources to be controlled in the way that the aggregated response will support the wider system. In addition, the characteristic behaviour of such populations requires to be understood under different system conditions to ascertain measures of risk and resilience. Therefore, this paper provides two main contributions: firstly, conceptual control for a system incorporating a high penetration of microgeneration and dynamic load, termed a Highly Distributed Power System (HDPS), is proposed. Secondly, a technical solution that can support enhanced transient stability in such a system is evaluated and demonstrated

Scenarios for the development of smart grids in the UK: literature review

Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids

Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid

Nonlinear model predictive control for thermal management in plug-in hybrid electric vehicles

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A nonlinear model predictive control (NMPC) for the thermal management (TM) of Plug-in Hybrid Electric Vehicles (PHEVs) is presented. TM in PHEVs is crucial to ensure good components performance and durability in all possible climate scenarios. A drawback of accurate TM solutions is the higher electrical consumption due to the increasing number of low voltage (LV) actuators used in the cooling circuits. Hence, more complex control strategies are needed for minimizing components thermal stress and at the same time electrical consumption. In this context, NMPC arises as a powerful method for achieving multiple objectives in Multiple input- Multiple output systems. This paper proposes an NMPC for the TM of the High Voltage (HV) battery and the power electronics (PE) cooling circuit in a PHEV. It distinguishes itself from the previously NMPC reported methods in the automotive sector by the complexity of its controlled plant which is highly nonlinear and controlled by numerous variables. The implemented model of the plant, which is based on experimental data and multi- domain physical equations, has been validated using six different driving cycles logged in a real vehicle, obtaining a maximum error, in comparison with the real temperatures, of 2C. For one of the six cycles, an NMPC software-in-the loop (SIL) is presented, where the models inside the controller and for the controlled plant are the same. This simulation is compared to the finite-state machine-based strategy performed in the real vehicle. The results show that NMPC keeps the battery at healthier temperatures and in addition reduces the cooling electrical consumption by more than 5%. In terms of the objective function, an accumulated and weighted sum of the two goals, this improvement amounts 30%. Finally, the online SIL presented in this paper, suggests that the used optimizer is fast enough for a future implementation in the vehicle.Accepted versio

Prospects for Plug-in Hybrid Electric Vehicles in the United States and Japan: A General Equilibrium Analysis

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/)The plug-in hybrid electric vehicle (PHEV) may offer a potential near term, low carbon alternative to today's gasoline- and diesel-powered vehicles. A representative vehicle technology that runs on electricity in addition to conventional fuels was introduced into the MIT Emissions Prediction and Policy Analysis (EPPA) model as a perfect substitute for internal combustion engine (ICE-only) vehicles in two likely early-adopting markets, the United States and Japan. We investigate the effect of relative vehicle cost and all-electric range on the timing of PHEV market entry in the presence and absence of an advanced cellulosic biofuels technology and a strong (450ppm) economy-wide carbon constraint. Vehicle cost could be a significant barrier to PHEV entry unless fairly aggressive goals for reducing battery costs are met. If a low cost vehicle is available we find that the PHEV has the potential to reduce CO2 emissions, refined oil demand, and under a carbon policy the required CO2 price in both the United States and Japan. The emissions reduction potential of PHEV adoption depends on the carbon intensity of electric power generation and the size of the vehicle fleet. Thus, the technology is much more effective in reducing CO2 emissions if adoption occurs under an economy-wide cap and trade system that also encourages low-carbon electricity generation.BP Conversion Research Project and the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial sponsors and Federal grants

Impact of stochastic loads and generations on power system transient stability

Randomness in physical systems is usually ultimately attributed to external noise. Dynamic systems are driven not only by our own control inputs, but also disturbances which cannot be modeled deterministically. A linear system model is justifiable for a number of reasons, often such a model is adequate for the purpose at hand, and when non-linearities do exist, the typical engineering approach is to linearize about some nominal point or trajectory to achieve a perturbation or error model. However, in order for the resulting model to fit data generated by the real world, these disturbances need to be modeled stochastically. The traditional approach to power system stability studies is based on a deterministic transient energy function. However, such a deterministic analysis does not provide a realistic evaluation of system transient performance where the intermittency and variability of energy production associated with any renewable technology needs to be reflected and accurately modeled in system stability and performance assessments. In the papers that make up this dissertation, the random variations of system components is modeled by a Gaussian stationary process (white noise) with constant spectral density and the effect on the stability of the power system is examined. The stochastic perturbation of power loads has a significant effect on the transient stability of the power system. The load behavior is found in the random effect of system parameter arising from cumulative impacts of a number of independent events. The random load characteristic is considered to develop a structure-preserved power system transient stability using stochastic energy functions. The stochastic power system stability was analyzed both through the stochastic Lyapunov function and numerically using the Euler- Maruyama method --Abstract, page iv

Control Strategies for Smart Charging and Discharging of Plug- In Electric Vehicles

This chapter aims to provide an overview of the plug-in electric vehicle (PEV) charging and discharging strategies in the electric power system and the smart cities, as well as an application benefiting both consumers and power utility. The electric vehicle technology will be introduced. Then, the main impacts, benefits and challenges related to this technology will be discussed. Following, the role of the vehicles in smart cities will be presented. Next, the major methods and strategies for charging and discharging of plug-in electric vehicles available in the literature will be described. Finally, a new strategy for the intelligent charging and discharging of electric vehicles will be presented, which aims to benefit the consumer and the power utility