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.

The number of supermarkets offering grocery delivery has increased in recent years. Many studies conclude that CO₂ emission savings result from this concept. Since the delivery of groceries also consumes energy and produces emissions, break-even points can be calculated, where the delivery is environmentally beneficial compared to customer pickup. In this paper, influences of differing vehicle use on break-even points for savings of energy and CO₂ emissions are analyzed for the case of Haidhausen Süd, a district in Munich, Germany. Internal combustion engine and electric vehicles are investigated to depict current as well as future trends. After an introduction to the methodology used, the potential to save energy and CO₂ emissions related to the delivery of groceries in the chosen district of Munich are evaluated. Subsequently, influences on the break-even points are presented and discussed. As the results show, a delivery of groceries leads to energy and carbon dioxide savings in a wide range of private vehicle use for grocery shopping trips. Nevertheless, if the complete customer vehicle fleet is electrified, the use of delivery vehicles with an internal combustion engine could cause an additional environmental impact at the current modal split for shopping trips in Germany.

Heating systems such as heat pumps and combined heat and power cycle systems (CHP) represent a key component in the future smart grid. Their capability to couple the electricity and heat sector promises a massive contribution to the energy transition. Hence, these systems are continuously studied numerically and experimentally to quantify their potential and develop optimal control methods. Although numerical simulations provide time and cost-effective solutions for system development and optimization, they are exposed to several uncertainties. Hardware in the loop (HiL) approaches enable system validation and evaluation under different real-life dynamic constraints and boundary conditions. In this paper, a HiL system of a heat pump testbed is presented. It is used to present two case studies. In the first case, the conventional heat pump testbed operation method is compared to the HiL operation method. Energetic and dynamic analyses are performed to quantify the added value of the HiL and its necessity for dynamics analysis. In the second case, the HiL testbed is used to validate a model of a single family house with a heat pump participating in a local energy market. The energetic analysis indicates a deviation of 2% and 5% for heat generation and electricity consumption of the heat pump model, respectively. The model dynamics emphasized its capability to present the dynamics of a real system with a temporal distortion of 3%.

There is a continuous growth of heat pump installations in residential buildings in Germany. The heat pumps are not only used for space heating and domestic hot water consumption but also to offer flexibility to the grid. The high coefficient of performance and the low cost of heat storages made the heat pumps one of the optimal candidates for the power to heat applications. Thus, several questions are raised about the optimal integration and control of heat pump system with buffer storages to maximize its operation efficiency and minimize the operation costs. In this paper, an experimental investigation is performed to study the performance of a ground source heat pump (GSHP) with a combi-storage under several configurations and control factors. The experiments were performed on an innovative modular testbed that is capable of emulating a ground source to provide the heat pump with different temperature levels at different times of the day. Moreover, it can emulate the different building loads such as the space heating load and the domestic hot water consumption in real-time. The data gathered from the testbed and different experimental studies were used to develop a simulation model based on Modelica that can accurately simulate the dynamics of a GSHP in a building. The model was validated based on different metrics. Energetically, the difference between the developed model and the measured values was only 3% and 4% for the heat generation and electricity consumption, respectively.

Heating systems such as heat pump and combined heat and power cycle systems (CHP) are representing a key component in the future smart grid. Their capability to couple the electricity and heat sector promises a massive potential to the energy transition. Hence, these systems are continuously studied numerical and experimental to quantify their potential and develop optimal control methods. Although numerical simulations provide time and cost-effective solution for system development and optimization, they are exposed to several uncertainties. Hardware in the loop (HiL) system enables system validation and evaluation under different real-life dynamic constraints and boundary conditions. In this paper, a HiL system of heat pump testbed is presented. This system is used to present two case studies. In the first case, the conventional heat pump testbed operation method is compared to the HiL operation method. Energetic and dynamic analyses are performed to quantify the added value of the HiL and its necessity for dynamics analysis. The second case, the HiL testbed is used to validate the heat pump operation in a single family house participating in a local energy market. It enables not only the dynamics of the heat pump and the space heating circuit to be validated but also the building room temperature. The energetic analysis indicated a deviation of 2% and 5% for heat generation and electricity consumption of the heat pump, respectively. The model dynamics emphasized the model capability to present the dynamics of a real system with a temporal distortion of 3%.