Remco A. Verzijlbergh

Network Impacts and Cost Savings of Controlled EV Charging

This paper investigates the distribution system impacts of electric vehicle (EV) charging. The analysis is based on a large number of operational distribution networks in The Netherlands. Future load profiles have been constructed by adding different EV charging profiles to household loads and solving the power flows to assess the network impacts on various network levels. The results indicate that controlled charging of EVs leads to significant reduction of overloaded network components that have to be replaced, but the impact varies per network level. Overall, in the uncontrolled charging scenarios roughly two times more replacements are needed compared to the controlled charging scenario. Furthermore, it was shown that for the controlled charging scenario the overall reduction in net present value due to energy losses and the replacement of overloaded network components is approximately 20% in comparison with the uncontrolled charging scenario. The results suggest that the deployment of a flexible and intelligent distribution network is a cost-beneficial way to accommodate large penetrations of EVs.

Renewable Energy Sources and Responsive Demand. Do We Need Congestion Management in the Distribution Grid

Possible congestion management mechanisms for price-responsive electric vehicle demand in electricity distribution networks are investigated. Because a high penetration of renewable energy sources weakens the correlation between wholesale electricity prices and network demand, cost-minimizing electric vehicles may cause high peaks in network load. Managing congestion is not costly in theory but difficult to implement efficiently. Grid tariffs that are fixed ex ante, based on network load, were found to make the problem worse compared to the base-case scenario of flat tariffs. An optimal dynamic grid tariff yields desirable outcomes but is difficult to determine in case of realistic forecasting uncertainties. An iterative approach of a distribution grid capacity market has practical barriers related to IT infrastructure and computational requirements. Advance capacity allocation is more straightforward to implement, but the inter-temporal constraints of the electric vehicles continue to pose a challenge.

Distribution Grid Impacts of Smart Electric Vehicle Charging From Different Perspectives

As a consequence of the developments in electric transportation and the evolution toward smart grids, large-scale deployment of smart charging strategies for electric vehicles (EVs) becomes feasible. This leads to opportunities for different market parties to use the flexibility of EVs for various objectives that may be conflicting and result in a nonoptimal shifting of peak demands for the distribution grids. In this paper, we assess the financial impact of various EV charging strategies on distribution grids. We compare a strategy that minimizes network peak loads (from a network operators perspective) with a strategy to minimize charging costs (from the perspective of a commercial party). In a scenario with a high wind penetration in the system, the electricity prices are, for a significant part, determined by the instantaneous wind production. Therefore, we additionally study the effect of wind energy on electricity prices and, consequently, on the resulting EV load and network impacts. We obtain the network costs by calculating the impacts expressed in the net present value (NPV) of the investments costs and energy losses. We found that, in the case where EVs are basing their charge schedules on electricity prices, the increase in NPV compared with a no EV scenario was found to be 25% higher than in the case where the extra peak load due to EVs was minimized. The large difference in network impacts between the price based and network based charging strategies was only observed in the case with a high wind penetration. The results strongly suggest that the situation where EVs are controlled with a strategy to minimize charging costs that does not take the distribution grids into account may not lead to an optimal situation when the entire electricity delivery system is regarded.

The impact of controlled electric vehicle charging on residential low voltage networks

This papers investigates the impact of electric vehicle charging on residential low-voltage networks. The analysis is based on real life data of both driving patterns and a large number of electricity networks. The focus is on comparing uncontrolled an controlled charging scenarios. The results indicate that a significant number of LV-transformers will be overloaded if no charge control is applied. Moreover, a substantial portion of LV-feeder cables will be overloaded in the case of uncontrolled charging, although much less cables are overloaded than transformers. Controlled charging of EVs can reduce the number of overloaded tranformers and cables with approximately 25 % and 8% compared to the base case scenario of 1% growth of household electricity consumption.

Comparing different EV charging strategies in liberalized power systems

Electric vehicles (EVs) can be an important building block of future power systems due to the flexibility of the charging process. In liberalized power systems, the objectives of using this flexibility vary for different actors in the system. In this paper we formulate the optimization problem of EV charging from the perspective of three different actors: 1) consumers (represented by an aggregator), 2) distribution network operators and 3) wind power producers. The respective objectives of these actors can be summarized as minimizing charge costs, minimizing network losses and maximizing profits on a day-ahead market. The results show that the three different perspectives lead to markedly different EV demand profiles. These differences are partly caused by the fact that, due to its stochastic nature, wind power generation weakens the correlation between electricity prices, network load and imbalance volumes.

Deriving electric vehicle charge profiles from driving statistics

The impacts of EV charging on electricity grids is becoming an increasingly important subject of study, but detailed knowledge about the future charging profiles of EVs appears to be missing. In this study we construct EV charge profiles based upon a large dataset of driving patterns. We consider both controlled and uncontrolled charging scenarios, where the main rationale of the controlled charging scenario is to shift the EV electricity demand away from the standard household peak. We show that applying charge control results in only slightly higher peaks compared to the situation without EVs, whereas in the uncontrolled case, the peaks will be significantly higher. Moreover, it is shown that the aggregated charge profiles give a good approximation for the demand of approximately 50 EVs or more. The EV charge profiles can be used as a tool for future network planning and EV impact studies.

The role of electric vehicles on a green island

This paper investigates the potential of electric vehicles (EVs) to support a high penetration of renewable energy generation on the Portuguese island of Flores. By acting as responsive loads capable of delivering energy back to the grid, EVs can potentially reduce shortages or surplus of wind generation and minimize the use of backup diesel generation. The electricity demand, transportation patterns, wind power generation and electricity price are modeled based on a combination of data from Flores and other countries. Optimal charge policies of a fleet of EVs are defined using a dynamic programming algorithm. The results indicate that the controlled charging of EVs leads to a significant reduction in the deployment of backup generation capacity. Furthermore, the amount of spilled wind energy is reduced strongly, which has obvious economic advantages. The most important conclusion from this work is that the total emissions due to transport and electricity generation can be reduced by as much as 90% compared to the situation where all electricity and transportation demand is met by diesel.

System impacts of electric vehicle charging in an evolving market environment

Reductions in greenhouse gas emissions are a strong incentive for the large scale introduction of electric vehicles. Studies that quantify these environmental benefits have to incorporate emissions caused by generating the electricity used to power the vehicles. We show that an approach that uses the average CO2 intensity of power generation is inaccurate and one needs to consider the generation capacity that is deployed for the extra load of electric vehicles. Moreover, we show the strong sensitivity of the results on different market environment aspects like charging patterns, generation portfolios, the share of wind energy and CO2 prices. This strong sensitivity implies that it is very hard to accurately predict future emission reductions of electric vehicles.

Conceptual model of a cold storage warehouse with PV generation in a smart grid setting

This paper presents a model of a cold storage warehouse combined with PV generation in a smart grid setting. We formulate an optimization problem that maximizes profits of sold PV energy minus the cost of electricity withdrawn from the grid under constraints dictated by the temperature dynamics. We focus on the influence of different electricity tariff structures on the optimal cooling schedule that results from the optimization. The results show that the various tariff structures lead to markedly different optimal cooling trajectories, that can be understood in terms of the trade-offs between thermal leakage to the environment, time dependent PV revenues and prices for consuming electricity. The value of the optimized energy management vs uncontrolled cooling was found to be largest for the case where electricity prices were low during PV generation. This type of responsive demand can therefore facilitate the efficient integration of renewable energy sources in the power system.

Organizing flexibility: How to adapt market design to the growing demand for flexibility

The increase in variable renewable energy sources for power generation is creating a demand for more flexibility in the other parts of the value chain: networks, consumption and potentially storage facilities. Interfaces with other infrastructures may also provide flexibility. Implementation of these options for flexibility requires a more integrated approach to the regulation of the power sector (and therefore also to its analysis). We explore the dimensions along which system integration is required: geography, infrastructure, interfaces with other energy carriers and time scales.