Many Demand Side Management (DSM) approaches use energy prices as steering signals. This paper shows that such steering signals may result in power quality problems and high losses. As an alternative, this paper proposes to use desired (e.g., flat) power profiles as steering signals and presents an efficient scheduling algorithm that can follow desired power profiles. This paper investigates the complexity of price and profile steering, and presents an algorithm for profile steering.The evaluation of this algorithm studies the results of a best possible uniform pricing and profile steering for a case of 121 houses, each with an electrical vehicle of which the power consumption can be controlled and shifted in time. In contrast to the other evaluated approaches, our profile steering algorithm results in a much flatter profile and keeps the voltage between 220 V and 235 V at each node. It reduces distribution losses by 57 % compared to no control, and by 48 % compared to uniform pricing.

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Various Demand Side Management (DSM) approaches have been developed the last couple of years to avoid costly grid upgrades. However, evaluation of these DSM methodologies is usually restricted to a use-case specific example, making comparison between different DSM approaches hard. This paper presents a novel, open source, load profile generator to evaluate and compare DSM approaches. In addition to static load profiles for both active and reactive power, it also provides flexibility information for various classes of controllable domestic devices. Load profiles and flexibility information are generated using a simple behavioural simulation. The output data uses 1 minute intervals and incorporates device measurements. The generated profiles are in sound with the measurement data obtained in a field test on both the household level and aggregated neighbourhood level. The same dynamics, such as unbalanced loading and rapid power consumption fluctuations, are observed in the generated model.

To evaluate the impact of the energy transition on distribution grids, a year 2025 scenario stress test was conducted in a real Dutch distribution grid. For this, the authors confronted the local low-voltage grid of a village with 20 electrical vehicles and ovens. The result was a short service interruption which could not be avoided by control. Furthermore, severe unbalance and high peak load were observed, resulting in large voltage drops and severe neutral point shifts. The obtained measurements are used to validate simulation models used to study the effect of novel control strategies to balance the local grid. This is an open access article published by the IET under the Creative Commons Attribution License

The number of (hybrid) electric vehicles is growing, leading to a higher demand for electricity in distribution grids. To investigate the effects of the expected peak demand on distribution grids, a stress test with 15 electric vehicles in a single street is conducted and described in this paper. The test is conducted in a neighbourhood where both transformers and households are equipped with measurement devices. A significant maximum power consumption increase (more than double) is observed at one transformer when both the electric vehicles and domestic loads stress the network. The observed voltage drop in the network is 17V. Analysis further shows that the hosting capacity is around 15%-20% for the investigated networks and that under voltage is unlikely to occur. The measurements are compared to a simulation and the results show that the simulations predict the actual measurement accurately.