Patrick Jochem

Electricity storage systems in the future German energy sector

Due to the growing feed-in of electricity based on renewables, electricity storage systems will be essential in the future energy sector. Because of the volatile feed-in, electricity will have to be shifted temporally. Additionally, load centers and regions of potentially high wind-based electricity production are located far away from each other in Germany, resulting in the need to transport electricity from the north to the south. According to the targets defined by the German government, more than 60% of electricity generation in 2040 is to be based on renewables. A strategic allocation of storage systems might help to improve the utilization of grid capacities and integrate renewables at the same time. To analyze this, we implemented the possibility to commission storage systems throughout Germany in the energy system model PERSEUS-NET-ESS. This investment and dispatch model includes a DC approach of the German transmission grid and, thus, calculates not only the installed capacities, but also their optimal allocation. Besides storage systems, gas turbines or load shift potentials can be used for the integration of renewables. In this paper, we use PERSEUS-NET-ESS to evaluate the alternatives taking the grid restrictions into account. Results indicate that it is beneficial to commission about 3.2GW of battery storage systems until 2040, provided that storage investment will drop to about 150?/kWh until then. The main part of the capacity is to be deployed in northern Germany close to the sea, where electricity from off-shore wind parks will be fed into the grid. At the same time, the storage systems will be located mainly close to congested grid lines. For the case of battery storage systems being impossible in the model, gas turbines are commissioned instead. Modeling will also consider the load shift potential due to electric mobility. It can substitute almost all of the commissioned storage systems and at the same time reduce the total generation capacity needed. A deterministic dispatch and investment model focusing on electricity storage systems.Analyses of the future German electricity system until 2040.Identification of convenient storage allocations in the German transmission grid.Load shifting by electric vehicle charging is an alternative to storage systems.Endogenous storage allocation mainly close to grid congestions.

How to integrate electric vehicles in the future energy system

Main challenges within the energy system of tomorrow are more volatile, less controllable and at the same time more decentralized electricity generation. Furthermore, the increasing research and development activities on electric vehicles (EV) make a significant share of electric vehicles within the passenger car fleet in 2030 more and more likely. This will lead to a further increase of power demand during peak hours. Answers to these challenges are seen, besides measures on the electricity supply side (e.g. investing in more flexible power plants or storage plants), in (1) grid extensions, which are expensive and time consuming due to local acceptance, and in (2) influencing electricity demand by different demand side management (DSM) approaches. Automatic delayed charging of electric vehicles as one demand side management approach can help to avoid peaks in household load curves and, even more, increase the low electricity demand during the night. This facilitates integrating more volatile regenerative power sources, too. Bidirectional charging (V2G) and storing of electricity extends the possibilities to integrate electric vehicles into the grid. But, comparing electricity storage costs and availability of electric vehicles with costs and technical conditions of other technologies leads to the conclusion, that vehicle to grid (V2G) is currently not competitive—but might be competitive in the future, e.g. within the electricity reserve market. In summary, the chapter gives an overview of the future electricity market with the focus on electric vehicles and argues for automatic delayed charging of electric vehicles due to economic and technical reasons.

An efficient two-stage algorithm for decentralized scheduling of micro-CHP units

In this paper we present an efficient two-stage hierarchical decomposition algorithm aiming at determining economically improved operation schedules for residential proton exchange membrane fuel cell micro-combined heat and power (PEMFC micro-CHP) units and optimizing local charging of electric vehicles (EV) in the same household. Based on an individual short-term load forecasting (STLF) approach (imperfect forecast) for households implemented as an adaptive network-based fuzzy inference system (ANFIS), a mixed-integer linear program (MILP) and a two-stage greedy algorithm are used for determining optimized schedules based on a rolling-window approach. The results of the case study performed for eight variants in exemplary German households reveal that with both the MILP and the algorithmic approach, significant economic savings can be achieved compared to the standard heat-led strategy. Compared to the MILP, however, the two-stage algorithm has the additional advantage of a reduced computing time of only about 115. Deviations from the MILP solutions are mostly smaller than 3 percent regarding the annual supply costs. Moreover, the comparison between the use of perfect and imperfect demand forecasts quantifies additional average losses due to forecasting errors of 2 percent and 3.3 percent at the maximum. Altogether, the algorithmic approach seems to be convincing for real applications in households due to its good results, high reliability, easy implementation, and short computing times. The combination of a micro-CHP unit and an EV is highly synergetic.

The Costs of Privacy in Local Energy Markets

Many renewable sources for electricity generation are distributed and volatile by nature, and become inefficient and difficult to coordinate with traditional power transmission paths. As a part of the transition from fossil fuel to renewable sources, local energy markets allow an efficient allocation and distribution of energy from local sources to nearby households. When using a discrete time double auction model, bids in such markets reflect the supply and demand of energy. However, since the energy demand of a household contains personal information, such markets are not in line with privacy legislation. In this paper, we investigate the influence of anonymization methods on local energy markets. In particular, we anonymize the bids of the order book, and we compare the CO2 emissions and the expenses of market participants of this allocation with a non-anonymous one. We have modeled the flows of personal data for a local energy auction platform, and we have developed a model for the supply and demand of electricity of a small town in the near future. Our experiments show that with elementary anonymization methods, the impact of anonymization on the costs and on the CO2 emissions is small.

When will electric vehicles capture the German market? And why

Market development of electric vehicles in the coming years is a highly relevant issue for many stakeholders, e.g. automobile- and energy-industry, investors as well as policy makers and the public. The market forecasts, however, differ strongly and underlying assumptions are often hard to find. Furthermore, for stakeholders from such diverse fields it can be difficult to convey their own assumptions and views to each other. Therefore, we try to shed light on this debate in presenting a simple and clear forecast model which reduces the excessive complexity down to a coherent approach. The central aspect of this model is to work with two essential, widely accepted parameters: The Total Cost of Ownership (TCO) and Diffusion Factors (DIF). These two parameters are easily deduced and can be evaluated by all stakeholders. Based on them, a third element, the TCO demand function, leads to a forecast of xEV volumes. The PTD-model (Prognosis on TCO and Diffusion factor) thus allows a common view of diverse stakeholders by combining scientific accuracy with a plain and intelligible design. It has been already successfully applied for different groups, which all had in common that they were heterogeneous and interdisciplinary staffed. Examples are academic seminars, commercial strategy projects, and the German National Platform for Electric Mobility (NPE). This paper mainly refers to the process and the results of the NPE in which, based on the approach presented here, the need for subsidies of xEVs was discussed. In addition, we discuss how the approach can be utilized for a classification of boundary conditions in different countries.

On the Necessity and Nature of E-Mobility Services – Towards a Service Description Framework

After years of focusing exclusively on the technological side of electric mobility (e-mobility), services are getting more and more in the focus of scientists. Many recent works concentrate on the identification and analysis of the potential of new business models in this field. Although the relevancy of services for the success of e-mobility is becoming more obvious among industry and science, there is still a lack in scientific contributions when asking for a comprehensive overview of existing e-mobility services. With this paper, we try to bridge this gap by providing a framework that enables the description and classification of services around the usage of an electric vehicle (EV). The framework captures six dimensions which allows to characterize and compare different services. This enables the identification of commonalities and differences between the services and provides an interdisciplinary playground for developing new services and further research in this field.

Interdependencies of Home Energy Storage between Electric Vehicle and Stationary Battery

Decentralized power generation in private homes, especially by photovoltaic systems, is already common in Germany. The developments of batteries, both for electric vehicles (EV) and for stationary storage might lead to a mass market for those batteries. In this paper we evaluate the economy of stationary battery storage with photovoltaic system at home in the context of available EV and its integration level into the home. Therefore, we use an optimization model with one year detailed operation planning and maximize the net present value of the storage investment. We integrate restriction functions for the technical parameters of the storage systems and limit EV availability and usage on the basis of German mobility studies for single vehicles. The results show, that an investment in a stationary battery system in combination with a photovoltaic system is profitable in Germany under the assumptions considered. The observed high numbers of battery cycles lead to strong requirements for battery lifetime, i. e. cycle stability and long calendar life time. Therewith, Li-ion batteries are a promising technology. In combination with an EV, the net present value of the stationary battery system is smaller when the EV is integrated into the home by controlled charging or the vehicle to home (V2H) concept, which allows discharging into the home system. The size of the EV battery, the availability at daytime and the load curve of the home are the main influencing factors for the profitability of the battery system.

CO 2 Mitigation Potential of Plug-in Hybrid Electric Vehicles larger than expected

The actual contribution of plug-in hybrid and battery electric vehicles (PHEV and BEV) to greenhouse gas mitigation depends on their real-world usage. Often BEV are seen as superior as they drive only electrically and do not have any direct emissions during driving. However, empirical evidence on which vehicle electrifies more mileage with a given battery capacity is lacking. Here, we present the first systematic overview of empirical findings on actual PHEV and BEV usage for the US and Germany. Contrary to common belief, PHEV with about 60 km of real-world range currently electrify as many annual vehicles kilometres as BEV with a much smaller battery. Accordingly, PHEV recharged from renewable electricity can highly contribute to green house gas mitigation in car transport. Including the higher CO2eq emissions during the production phase of BEV compared to PHEV, PHEV show today higher CO2eq savings then BEVs compared to conventional vehicles. However, for significant CO2eq improvements of PHEV and particularly of BEVs the decarbonisation of the electricity system should go on.

Electric Vehicles with Range Extenders: Evaluating the Contribution to the Sustainable Development of Metropolitan Regions

AbstractElectric vehicles play a key role in strategic development plans of urban regions in Europe because they are seen as a promising technology to promote environmental quality, livability, and...

Empirical Fuel Consumption and CO2 Emissions of Plug‐In Hybrid Electric Vehicles

Plug‐in hybrid electric vehicles (PHEVs) combine electric and conventional propulsion. Official fuel consumption values of PHEVs are based on standardized driving cycles, which show a growing discrepancy with real‐world fuel consumption. However, no comprehensive empirical results on PHEV fuel consumption are available, and the discrepancy between driving cycle and empirical fuel consumption has been conjectured to be large for PHEV. Here, we analyze real‐world fuel consumption data from 2,005 individual PHEVs of five PHEV models and observe large variations in individual fuel consumption with deviation from test‐cycle values in the range of 2% to 120% for PHEV model averages. Deviations are larger for short‐ranged PHEVs. Among others, range and vehicle power are influencing factors for PHEV model fuel consumption with average direct carbon dioxide (CO2) emissions decreasing by 2% to 3% per additional kilometer (km) of electric range. Additional simulations show that PHEVs recharged from renewable electricity can noteworthily reduce well‐to‐wheel CO2 emissions of passenger cars, but electric ranges should not exceed 200 to 300 km since battery production is CO2‐intense. Our findings indicate that regulations should (1) be based on real‐world fuel consumption measurements for PHEV, (2) take into account charging behavior and annual mileages, and (3) incentivize long‐ranged PHEV.