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In this paper, we present a comprehensive assessment of the effects of residential loads, electric vehicles (EVs), and electric heat pumps (HPs) on low-voltage (LV) grids in urban, suburban, and rural areas of Germany. Firstly, real data are used to determine the typical structures for each LV grid region. Secondly, nine scenarios are defined with different levels of EV and HP penetration. Thirdly, the Low Voltage Load Flow Calculation in the DIgSILENT PowerFactory is performed for all scenarios while taking the simultaneity factor (SF) for each load type into consideration to calculate the minimum voltage and maximum loadings of transformer and lines in each grid; this allows for the grid's potential bottlenecks to be identified. The network simulations are carried out with the consideration of charging powers of 11 kW and 22 kW in order to evaluate how an increasing EV load in the future may affect the grid's parameters. To the best of our knowledge, no study in the literature has simultaneously addressed all of the aforementioned topics. The results of this study provide a useful framework that distribution system operators (DSOs) may apply to anticipate the forthcoming challenges and figure out when grid reinforcement will be required. [ABSTRACT FROM AUTHOR]

• Effects of two EEVs openings on the CO 2 vapor-injection heat pump were studied. • The regulation characteristics of EEV1 and EEV2 were experimentally analyzed. • The maximum cooling COP occurs as the refrigerant from EEV1 is in a saturated state. • A control strategy for optimal COP was formulated. The regulation characteristics of electronic expansion valves (EEVs) are critical to improving the comprehensive energy efficiency of the heat pump system for electric vehicles. In this paper, a vapor-injection transcritical CO 2 heat pump system for electric vehicles was first established to experimentally study the impacts of EEV1 and EEV2 openings on the overall system performance. The results show that the cooling capacities of the vapor-injection system are respectively increased by 3.13% / 5.75% with the EEV1's opening of 15% / 25% and injection ratio of 0.0975 / 0.8305, compared against these of the basic system without vapor injection. As the injection ratio rises, the cooling capacity increment tends to increase while the cooling coefficient of performance (COP) declines from 1.7 to 1.51. Then, the regulation characteristics of EEV1 and EEV2 were quantitively analyzed, indicating that the evaporation pressure is mainly determined by EEV2's openings. By adjusting EEV1's opening, the COP of the CO 2 vapor-injection heat pump can be maximized at 1.9, with EEV1's opening at 20% and outdoor/indoor ambient temperature at 0°C / 20°C. When adjusting EEV2's opening, the maximum injection pressure corresponds to the maximum COP of 1.84, with EEV2's opening at 65% under 35°C/ 27°C. When the COP reaches the maximum, the refrigerant at the outlet of EEV1 is just saturated liquid under cooling conditions, while it is located in the two-phase region under heating conditions. Besides, the optimal COP regulation strategy of the CO 2 vapor-injection heat pump was further formulated based on two modes, as the strategy in the cooling mode differs from that in the heating mode. [ABSTRACT FROM AUTHOR]

Passenger comfort takes precedence over heating performance for electric vehicle heat pumps. However, frost formation will cause the heat exchange performance to decrease, leading to the heating capacity dissipation. The dynamics of an electric vehicle CO 2 heat pump under constant heating capacity operation during the frosting process were revealed. Moreover, it was found that the dynamic characteristics of parameters under constant heating capacity operation were significantly different from those under constant compressor speed operation. The application of defrosting initiation judgment criteria based on traditional heat pumps to electric vehicle heat pumps would lead to some serious false defrosting phenomena and even damage the compressor and pipelines. Therefore, a new defrosting initiation criterion was proposed for electric vehicle heat pumps based on the dynamic characteristics. Then, the reliability of the new initiation was verified by applying it in different heating demand operations. Finally, the average performance of electric vehicle heat pumps adopting the new defrost initiation was compared with the traditional PTC auxiliary heating method. The conclusion demonstrated that the heat pump with the new defrost initiation criterion had obvious performance advantages under different environmental conditions. [ABSTRACT FROM AUTHOR]

The wide speed ratio range and continuously variable ratio characteristics of continuously variable transmission (CVT) can effectively improve the energy economy of electric vehicle (EV). However, the relatively low mechanical efficiency and high hydraulic loss limit its application in EV. Therefore, an electric CVT configuration based on electric oil pump (EOP) is proposed, a dynamic model of the EV equipped with CVT is constructed and verified through bench tests, subsequently the model is used to study the factors affecting the energy economy of EV in driving cycles. The simulation results indicate that reasonable selection of speed ratio range can reduce power loss and improve energy consumption economy, optimized speed ratio matching strategy can effectively improve electric drive efficiency, and adopting EOP to supply oil can decrease hydraulic loss. The analysis results provide a clear reference for further exploring the energy-saving potential of EV equipped with CVT. [ABSTRACT FROM AUTHOR]

• A novel simulation method is proposed to identify the causes of lubrication failure in high-speed coolant pumps for electric vehicles. • Experimental validation confirms the accuracy of simulations for both the pump and bearing. • The steady radial forces of the pump rotor are effectively balanced by the bearing load capacity. • The rotor–stator interaction results in unsteady radial forces, inducing substantial whirl in the bearing. • The bearing whirl reduces lubricant film pressure gradient and load capacity, ultimately leading to lubrication failure. The high-speed coolant pump is essential for electric vehicle thermal management, ensuring optimal module temperatures. The pump impeller and bearing are combined into a rotor and then fit on a fixed shaft with a clearance, aiming to generate a complete lubricant film between the stationary journal and rotating bearing during pump operations. However, during the pump durability test under off-design conditions, severe wear occurred on both the journal and bearing. A novel simulation method based on computational fluid dynamics and dynamic mesh is developed to investigate the lubrication failure. User-defined functions are programmed to articulate the simultaneous rotation and whirl of the bearing, and the effects of temperature and cavitation are considered. Both the pump and bearing simulations closely align with experimental results. When the radial force of the pump rotor is steady, the bearing only rotates without whirling, and the bearing load capacity can counteract the maximum radial force of the rotor. However, the rotor experiences fluctuating radial forces over time, primarily attributed to elevated pressure levels at the volute tongue caused by the rotor–stator interaction. This phenomenon results in the bearing to rotate and whirl simultaneously. The load capacity generated by the backward whirl of the bearing is greater than that of the forward whirl. Nevertheless, the bearing whirl initiates a decline in the extremum values of lubricant film pressure. Subsequently, both load capacity and minimum film thickness exhibit a continuous decrease, eventually culminating in the breakdown of the complete lubricant film and resulting in contact wear failure. These new findings contribute to proposing measures to reduce wear under unsteady excitations. [ABSTRACT FROM AUTHOR]

[Display omitted] • A direct thermal controlling system based on CO 2 heat pump was proposed. • System dynamic performance under WLTC driving conditions was evaluated. • Optimal discharge pressures response to multiple operating modes was revealed. • Battery and motor cooling via optimal vapor quality control was proposed. Efficient integrated thermal management scheme is crucial for improving the driving range, thermal comfort, and safety of electric vehicles. Compared with the synthetic refrigerant heat pump indirect cooling/heating on the vehicle electrical system, the natural refrigerant CO 2 heat pump direct thermal controlling integrated into the thermal management system has advantages in the thermal cycle performance and environmental friendliness. The present study proposed a thermal management system based on CO 2 heat hump with multiple working modes for enhancing vehicle energy utilization coefficient. The system thermal performance under the World Light Vehicle Test Cycle was investigated via energy and exergy analyses. The operational control strategies of the thermal management system were optimized for the thermal controls of the cabin, battery and motor. The results show that the minimum exergy destruction of the thermal system occurs at the optimal discharge pressure corresponding to the highest coefficient of performance. Ensuring two-phase latent heat transfer for battery cooling is the most effective measure to maintain battery temperature uniformity via dynamic collaborative regulation of expansion valves' openings and compressor speed. Compared with constant expansion valve's opening, the coefficient of performance of the system can be improved by a maximum of 10% with the saturated CO 2 vapor at the outlet of battery cooling plate. Due to the low thermal capacitance and minimal thermal inertia of driving motor, its cooling performance is significantly influenced by the heat generation rate and refrigerant flow. Optimal motor cooling efficiency is achieved when controlling the refrigerant quality to 0.85 at the cooling passage outlet. Under the World Light Vehicle Test Cycle, the thermal management system effectively regulated the temperatures across different operating modes while operating at optimal discharge pressures. [ABSTRACT FROM AUTHOR]

Managers in electric utilities face the disruption of their conventional business model of selling electricity per kilowatt-hour for invariant prices. However, the forthcoming widespread uptake of sustainable energy technologies – such as rooftop solar, batteries, heat pumps and electric vehicles – by residential customers also represents a chance for local utilities to diversify their service portfolio. To appropriately market these technologies to households, utilities need data on consumers. In this paper, we present a novel data-driven service bundle recommendation model incorporating technologies and tariffs for residential customers based on individual household data. We validate the model in a case study and quantify the utility of sharing different levels of household data. We find substantial synergies of flexible sustainable technologies and time-varying tariffs, leading to higher cost reductions for customers than tariff-switching alone that can be recommended based on easy-to-obtain data. This demonstrates a large potential for energy service bundle marketing by local utilities. The presented Machine Learning recommendation models enable more reliable recommendations than a naive benchmark. Our research thus demonstrates the potential of data-driven utility marketing strategies that focus on service bundling and the integration of customers' energy consumption data. [ABSTRACT FROM AUTHOR]

This paper develops quantitative predictions for residential electricity demand and the potential for load shifting for Europe at a fine spatial scale for years 2022–2050. To date only theoretical and spatially coarse measurements of this potential exist for a subset of technologies used in the residential sector. As the EU moves towards an 'Energy Union', it will be increasingly necessary to consider the whole integrated energy system across the EU and thereby databases with large spatial coverage are needed. To fill this need, we generate hourly load profiles for the residential sector for key electricity consuming devices that take into account the most recent empirical studies of usage patterns, and of the cost and willingness of households to participate in load shifting programs. Additionally, we extend the list of investigated technologies by the important classes of electric mobility and heat pumps for electric space heating. Predictions and insights provided in our article serve multiple use cases, i. they can be used in energy system models to assess the value of load shifting for the future energy system including system costs, ii. they enable infrastructure planners and grid operators to calibrate their expectations of the future role of load shifting in the electricity systems and iii. enable policy makers and to include load shifting in their considerations of future market designs. • Quantitative predictions for residential electricity demand and the potential for load shifting for Europe at a fine spatial scale for years 2022–2050. • Residential coverage of electric vehicles, heat pumps, storage heaters, water heaters, air conditioners, refrigeration, and washing equipment. • Substantial potentials are identified for electric vehicles and heat pumps. [ABSTRACT FROM AUTHOR]

In order to keep a lithium-ion battery within optimal temperature range for excellent performance and long lifespan, it is necessary to have an effective control strategy for a battery thermal management system (BTMS) consisting of electric pump, cooling plate and radiator. In this paper, a control-oriented model for BTMS is established, and an intelligent model predictive control (IMPC) strategy is developed by integrating a neural network-based vehicle speed predictor and a target battery temperature adaptor based on Pareto boundaries. The strategy is applied to plug-in electric vehicles operating in electric vehicle mode. Results show its superiority in terms of battery temperature control, battery lifespan extension and energy saving. Under the new European driving cycle, average difference between the real-time battery temperature under the novel IMPC and its target temperature is 0.26 °C, and maximum temperature difference among modules is 1.03 °C. Moreover, compared with the on-off controller, model predictive control (MPC), and MPC with VSP, state of health under IMPC at the end of the driving cycle is 0.016%, 0.012%, and 0.008% higher, respectively. At this moment, the energy consumption of IMPC is 24.5% and 14.1% lower than that of the on-off controller and traditional MPC, respectively. [ABSTRACT FROM AUTHOR]

Air-source heat pump with vapour injection is a prospective efficient heating method for electric railway vehicles in cold regions. A heating performance analysis modelling for air source heat pump with vapour injection is set up for performance optimization in this paper. The maximum errors of the program are within 15%. Heating performance, as well as the optimal injection ratio is analysed. The optimal injection ratio varies mainly from 0.12 to 0.3 under the typical working condition of railway vehicles in winter. It goes up with increasing inlet air temperature of condenser and goes down with increasing ambient temperature. The ambient temperature has very little effect on the optimal injection temperature of the internal heat exchanger. The results indicate that the expander valve opening of the injection branch can be controlled by its outlet temperature to get the optimal heating performance. [ABSTRACT FROM AUTHOR]

Summary: Automotive air‐conditioning heat pump systems are particular interest worldwide in energy conservation and emission reduction for electric vehicles, hybrid electric vehicles, and fuel cell electric vehicles. Refrigerant charge amount is a key factor for the air‐conditioning heat pump system optimization affecting the condensing pressure and subcooling in both heating and cooling modes. In this paper, the influence of the refrigerant charge on system performances was investigated using the experiment method on a secondary loop air‐conditioning heat pump system. The typical heat transfer and flow parameters were recorded, and both cooling and heating performances of the system were investigated and illustrated by pressure‐enthalpy diagrams. The critical refrigerant charges were determined in both heating and cooling modes. Three typical void fraction correlation models were also applied for the refrigerant charge determination modeling as a system off‐design method. Results show that the Hughmark void fraction correlation method has the best prediction of the critical refrigerant charge in both cooling and heating modes. [ABSTRACT FROM AUTHOR]

• Air conditioning load reduction strategy in vehicles using recirculated air is provided. • Utilizing the recirculated air can extent the annual driving range by 11−30%. • Energy saving of heat pump heating in electric vehicle air conditioning is provided. The stock of electric vehicle is booming recently. However, the range of the electric vehicle is still a main barrier in its adoption. Air conditioning system is the second largest energy consumption device on vehicle, which will cause significant range reduction during operation. In this paper, the energy-saving effect of utilizing the recirculated air in air conditioning system is evaluated. The outside air ventilation rate based on CO 2 limits and windshield anti-fog requirements are calculated, and the energy-saving effect of this strategy in 30 cities across China is evaluated using an annual energy consumption model. It is found that utilizing the recirculated air can save 14–46% heating energy when using PTC heater, and 33–57% heating energy in heat pump AC system. Throughout a year, utilizing the recirculated air can extend the driving range by 11–30%. Image, graphical abstract [ABSTRACT FROM AUTHOR]

• Residential heat pumps have a 5–70% higher consumption than electric vehicles. • Heat pumps contribute 14% more to national peak load hours than electric vehicles. • The coincidence factor of residential vehicle charging is a maximum of 25%. • Socioeconomic characteristics less impactful on consumption than technologies. Residential electrification of transport and heat is changing consumption and its characteristics significantly. Previous studies have demonstrated the impact of socio-techno-economic determinants on residential consumption. However, they fail to capture the distributional characteristics of such consumer groups, which impact network planning and flexibility assessment. Using actual residential electricity consumption profile data for 720,000 households in Denmark, we demonstrate that heat pumps are more likely to influence aggregated peak consumption than electric vehicles. At the same time, other socio-economic factors, such as occupancy, dwelling area and income, show little impact. Comparing the extrapolation of a comprehensive rollout of heat pumps or electric vehicles indicates that the most common consumer category deploying heat pumps has 14% more maximum consumption during peak load hours, 46% more average consumption and twice the higher median compared to households owning an electric vehicle. Electric vehicle show already flexibility with coincidence factors that ranges between 5 and 15% with a maximum of 17% whereas heat pumps are mostly baseload. The detailed and holistic outcomes of this study support flexibility assessment and grid planning in future studies but also the operation of flexible technologies. [ABSTRACT FROM AUTHOR]

When an energy storage system (ESS) operates in cold conditions, the power and capacity of the battery critically fade. Therefore, an appropriate battery thermal management strategy (BTMS) is essential to prevent severe driving range loss at low ambient temperatures. However, none of existing studies considered the effect of BTMS on the driving range from a systematic perspective. Thus, we evaluated the trade-off between the performance enhancement by ESS heating and the additional energy consumption for ESS heating. We suggested and analyzed three BTMSs combined with a secondary heat pump: self-heating, active heating, and heat recovery. Active heating of the battery augmented the driving range of the EV by up to 18.8% over the self-heating strategy when the battery was used to full depletion, whereas the heat recovery strategy reduced the state-of-charge (SOC) decrease and thus increased EV driving range in nondepleted conditions. Furthermore, battery preheating with the heat pump achieved a temperature rise of 20 °C within an hour, consuming 38.4% less battery power than with conventional electric heater preheating. We expect this study contributes to the range extension of EV by suggesting the optimal BTMS depending on the driving conditions. • Experiments on the battery performance were conducted at low temperatures. • Battery thermal model was established and integrated with transient heat pump model. • Three strategies for battery thermal management were suggested. • Integrated thermal management model derived the optimal strategy under cold-start. [ABSTRACT FROM AUTHOR]

With the decreasing cost of green technologies and the increasing ambitions to reach the net-zero carbon emissions target, more communities are engaged in renewable deployment and energy-intensive technologies such as heat pumps and electric vehicles will be intensively adopted in the near future. The integration of these appliances in lower grid levels will likely require grid reinforcements. However, some of these appliances are flexible and there is an opportunity to explore their flexibility potential to optimise the investment costs further. This paper proposes an optimal design strategy for a grid-connected site that returns the renewable generation and storage's optimal sizing capacities and the required network reinforcement capacity. The novelty of the work is integrating network upgrade costs and considering flexibility from distributed flexible resources across planning and operation. The problem is formulated as a mixed integer piecewise linear problem, with the capacities of generation, storage and network upgrade as decision variables. The piecewise linear cost function related to the upgrade costs figuring in the objective function is then recast as a mixed-integer problem, and the flexible resources are modelled through an approximation method as a single virtual flexible asset. The application of the strategy on the Perth West smart city project as a case study demonstrates the importance of considering flexibility in the planning phase. The costs related to the storage system can decrease by up to 76%, and the overall costs by up to 35%, with the highest levels of savings, reached for the highest rates of electric vehicle adoption. [Display omitted] • An optimal sizing strategy for grid-connected microgrids is proposed. • Both flexibility from distributed assets and network upgrade costs are incorporated. • The problem is formulated as MINLP and recast into an MILP. • The value of the methods are demonstrated for the Perth West Smart City project. • Considering flexibility from EVs, the overall costs can decrease by up to 35 %. [ABSTRACT FROM AUTHOR]

Accurately estimating the operational performance of electric coolant pump (ECP) can support long-term sensorless operational monitoring and reduce the cost and energy consumption of a vehicle thermal management system. However, there are some problems such as low estimation precision of theoretical model and back propagation neural network (BPNN) models, and the input parameters of existing studies are difficult to obtain at the ECP. In this study, a novel ISSA-BPNN estimation model is proposed that combines a hybrid strategy improved sparrow search algorithm (SSA) with the BPNN after hyperparameter optimization, and for the first time analyzes and uses the total power easily obtained as the input data of the model. Multiple experimental results show that the estimation precision and reliability of the proposed ISSA-BPNN model are much higher than those of the present theoretical models and BPNN methods. The average training time of the proposed ISSA-BPNN model is 226.9 s, and the average real-time operation time is about 5 ms, which meets the real-time application requirements. The proposed model is also applicable to the operational state estimation of other types of integrated pumps. • Operating state estimation of integrated pumps using easily accessible parameters. • High-performance Improved Sparrow Search Algorithm Based on Hybrid Strategy. • Swarm intelligence algorithm solves artificial neural network premature problem. • High precision pump operation performance estimation based on hybrid improved model. • Support long-term sensorless monitoring and reduce vehicle energy consumption. [ABSTRACT FROM AUTHOR]

Improving driving range is very important for electric vehicles (EVs). The use of CO 2 heat pumps to replace Positive Temperature Coefficient (PTC) heaters for cabin heating is one of the most efficient choices for improving driving range in EVs. The combination of CO 2 heat pumps and electric vehicles matches well with the social requirements of low-carbon, cleaner production, and sustainable development. However, heat pumps may frost under a conventional optimal discharge pressure control, resulting in a rapid drop in driving range. To solve this problem, the impact of frost on the driving range under different ambient conditions was assessed, and the failure of performance guarantee under conventional control in frost-prone conditions was deeply studied. Based on the experimental data, a heating capacity decline map was developed, and a new global performance improvement control method was proposed. Moreover, the dynamic characteristics between optimal discharge pressure control and the new control process were experimentally compared. Furthermore, a comparative analysis of driving range improvement under the global performance improvement control was carried out in three cities with typical climates. The results indicated that driving range improvement of the new method could be even as high as 10% in some conditions. Finally, the global performance improvement control method was recommended in regions with low ambient temperatures and high humidity. • A HP global heating efficiency improvement method is proposed to avoid frosting. • The new control method can increase the EV driving range even by up to 10%. • Guidance for optimal control method selection in different areas is provided. • The energy attenuation map under optimal discharge pressure control is developed. • The EV driving range decay under optimal discharge pressure control is revealed. [ABSTRACT FROM AUTHOR]

The decarbonisation of heat and transport using heat pumps (HPs) and electric vehicles (EVs) will require significant investment in low voltage (LV) networks both in terms of network reinforcement and in the provision of flexibility to avoid network upgrades where appropriate. In this paper, a heuristic methodology is presented to estimate headroom available for domestic EV charging optimisation in LV networks at different penetrations of HPs and a novel zonal approach is applied to EV optimisation. It was found that optimised charging of EVs can allow for a significantly higher penetration of EVs for a given HP penetration within the network, without the need for reinforcement. Significant improvements in terms of network hosting capacity were realised: for example, an increase from 34% EV and 50% HP penetration for dumb charging to 72% EV and 57% HP penetration for optimised charging was available for one particular case study. The level of improvement in hosting capacity was found to be strongly dependent on particular network topology and pre-existing demand; this reinforces the need for further study in unlocking the potential synergies of EV and HP uptake. • Heat pump and optimised electric vehicle capacity assessed on low voltage networks. • Novel 'zonal' probabilistic headroom optimisation for electric vehicle charging. • Method enables up to two times more electric vehicles than uncoordinated charging. • Tractable method for congestion management on low voltage networks. • Hosting capacity strongly dependent on network topology and pre-existing demand. [ABSTRACT FROM AUTHOR]

Rapid deployment of solar photovoltaics (PV), electric heat pumps (HP) and electric vehicles (EV) is needed to decarbonize the economy. However, the integration of these technologies into the power system creates challenges for the distribution grid infrastructure. It is therefore vital to analyse to which extent grid reinforcement is needed to enable decarbonization strategies while also studying alternative flexibility measures. In this GIS-based study, we model the impact of the deployment of PV, HP and EV on a low-voltage distribution grid network serving 170'000 households in Switzerland, and analyse scenarios for their penetration in the years 2035 and 2050. Using a detailed grid model in collaboration with a distribution system operator, we find that PV leads to 18.5% and 13.7% more voltage violation issues compared to HP and EV respectively, which on the other hand, cause slightly more line overloading, 0.5% and 2.5%, respectively. We also find that grid reinforcement costs markedly depend on the type of urban setting ranging between 51–213 CHF/kW p , 46–1'385 CHF/kW and 34–143 CHF/kW for PV, HP and EV, respectively, with the higher limit corresponding to rural areas. The total distribution grid reinforcement costs can amount up to 11 billion CHF until 2050 i.e. 2'900 CHF per household in Switzerland. Interestingly, we find that batteries, even with current costs, have the potential to defer grid reinforcement for up to 15% of the transformer stations with the highest specific grid reinforcement costs. Our study aims to inform various stakeholders about the required grid investments to enable the massive deployment of low carbon technologies. • Distribution grid impacts due to deployment of PV, heat pumps and EV charging assessed. • Scenarios are built for PV, HP and EV penetration in 2035 and 2050. • Grid reinforcement costs in rural areas higher compared to urban and suburban areas. • Variations in grid reinforcement costs are explained by technology additions (R 2 > 94%). • Batteries with current costs can defer reinforcement in up to 15% transformer stations. [ABSTRACT FROM AUTHOR]

• A microchannel heat exchanger with plain-louvered fins is proposed. • Frosting characteristics on plain- and corrugated-louvered fins are compared. • The heat exchanger with plain-louvered fins shows 16.7% higher performance. • Miles per gallon of electric vehicle with plain-louvered fins increases by 25.2%. Air source heat pumps have been proposed as effective climate control systems in electric vehicles. However, during cabin heating, air can condense on the cold surface of an outdoor heat exchanger in the air source heat pump. Frost can accumulate on the outdoor heat exchanger when the surface temperature drops below the freezing point. In this study, a novel microchannel heat exchanger with plain-louvered fins was developed as an outdoor heat exchanger to improve the frosting and defrosting characteristics of the air source heat pump in electric vehicles. Comparative performance evaluations of microchannel heat exchangers with the plain- and conventional corrugated-louvered fins were conducted during periodic frosting and defrosting cycles. The frosting period and peak heating capacity of the air source heat pump with the plain-louver fin heat exchanger were 102.7% and 14.0% higher than those with the corrugated-louvered fin heat exchanger, respectively. Miles per gallon equivalent of electric vehicle with the plain-louvered fins was 25.2% higher than that with electric heating. Overall, the microchannel heat exchanger with the plain-louvered fin is recommended as a preferred outdoor heat exchanger in the air source heat pump for electric vehicles. [ABSTRACT FROM AUTHOR]

The adoption of electric vehicles is incentivized by governments around the world to decarbonize the mobility sector. Simultaneously, the continuously increasing amount of renewable energy sources and electric devices such as heat pumps and electric vehicles leads to congested grids. To meet this challenge, several forms of flexibility markets are currently being researched. So far, no analysis has calculated the actual flexibility potential of electric vehicles with different operating strategies, electricity tariffs and charging power levels while taking into account realistic user behavior. Therefore, this paper presents a detailed case study of the flexibility potential of electric vehicles for fixed and dynamic prices, for three charging power levels in consideration of Californian and German user behavior. The model developed uses vehicle and mobility data that is publicly available from field trials in the USA and Germany, cost-optimizes the charging process of the vehicles, and then calculates the flexibility of each electric vehicle for every 15 min. The results show that positive flexibility is mostly available during either the evening or early morning hours. Negative flexibility follows the periodic vehicle availability at home if the user chooses to charge the vehicle as late as possible. Increased charging power levels lead to increased amounts of flexibility. Future research will focus on the integration of stochastic forecasts for vehicle availability and electricity tariffs. [ABSTRACT FROM AUTHOR]

Thermal management systems of passenger vehicles are fundamental to provide adequate cabin thermal comfort. However, for battery electric vehicles they can use a significant amount of battery energy and thus reduce the real driving range. Indeed, when heating or cooling the vehicle cabin the thermal management system can consume up to 84% of the battery capacity. This study proposes a model-based approach to design an energy-efficient control strategy for heating electric vehicles, considering the entire climate control system at different ambient conditions. Specifically, the study aims at reducing the energy demand of the compressor and water pumps when operating in heat pump mode. At this scope, the climate control system of the reference vehicle is modelled and validated, enabling a system efficiency analysis in different operating points. Based on the system performance assessment, the optimized operating strategy for the compressor and the water pumps is elaborated and the results show that the demand-based control achieves up to 34% energy reduction when compared to the standard control. [ABSTRACT FROM AUTHOR]

The city of Stockholm is close to hitting the capacity limits of its power grid. As an additional challenge, electricity has been identified as a key resource to help the city to meet its environmental targets. This has pushed citizens to prefer power-based technologies, like heat pumps and electric vehicles, thus endangering the stability of the grid. The focus of this paper is on the district of Hammarby Sjöstad. Here, plans are set to switch from district heating to heat pumps. A previous study verified that this choice will cause overloadings on the electricity distribution grid. The present paper tackles this problem by proposing a new energy storage option. By considering the increasing share of electric vehicles, the potential of using the electricity stored in their batteries to support the grid is explored through technical performance simulations. The objective was to enable a bi-directional flow and use the electric vehicles' (EVs)' discharging to shave the peak demand caused by the heat pumps. It was found that this solution can eliminate overloadings up to 50%, with a 100% EV penetration. To overcome the mismatch between the availability of EVs and the overloadings' occurrence, the minimum state of charge for discharging should be lower than 70%. [ABSTRACT FROM AUTHOR]

Vapor injection heat pumps have been proposed for cabin heating in electric vehicles (EVs) to improve the performance and reliability under severe weather conditions. However, the geometric optimizations of the injection-port and internal heat exchanger (IHX) in vapor injection heat pumps designed for EVs have rarely been investigated. The objective of this study is to investigate the effects of the injection-port angle and IHX length in a vapor injection heat pump for use in EVs at various startup conditions. The heating performance of a vapor injection heat pump with R134a is measured by varying the IHX length from 100 to 400 mm and injection-port angle from 320° to 440° at various cabin temperatures. The effects of the IHX length and injection-port angle are analyzed in terms of coefficient of performance (COP) and heating capacity. The optimum IHX length and injection-port angle for the maximum COP are determined to be 300 mm and 400°, respectively. • An IHX type vapor injection heat pump for EV is investigated. • Experiments are conducted under various startup conditions. • Effects of design parameters on the heating performance are analyzed. • The optimum injection-port angle and IHX length are suggested in terms of COP. [ABSTRACT FROM AUTHOR]

• Investigation of el. load of inner-city area in detail. • Use of validated stochastic bottom-up model for electricity, heat and mobility. • Seasonal variation increases due to PV, CHP and heat pumps. • Intra-day fluctuations will increase. • Annual peak load will rise by 32% due to the electric back-up heaters of air-source heat pumps and electric vehicles. Technological progress and the ambition to de-carbonise the energy sector are changing the way electricity is generated and used. In the residential sector, more efficient electric devices, electrification of mobility and heating systems, as well as on-site PV and battery systems are the main technologies driving this change. These changes will impact the characteristics of the electric demand. A comprehensive understanding of these changes is essential to efficiently design the energy system of tomorrow. The target of this research is to explore the possible changes of the electric load profiles with the current technological development, both at an individual household level and at an aggregate level. An inner-city area of 1550 houses is simulated with a time resolution of 1 minute using a stochastic bottom-up approach. Three scenarios considering refurbishment of buildings, efficiency increase in devices and emerging technologies are simulated. Differences in the load profiles are then analysed. Results show that future load profiles will change significantly. A strong seasonality will appear due to the increased penetration of PV, μ -CHP and heat pumps. Intra-day fluctuations will also increase, mainly due to the introduction of electric vehicles and PV. Annual peak load will rise significantly mainly due to the electric back-up heaters of air-source heat pumps. Increased electrification increases annual electricity demand, but results show that this will be partly compensated by better insulated buildings, more energy efficient household devices, and on-site production from PV-Battery systems and μ -CHP. [ABSTRACT FROM AUTHOR]