The growing integration of renewable energy sources presents significant challenges for the reliability of the energy infrastructures in The Netherlands. To address these challenges, dynamic electricity pricing has been proposed as a potential solution to align the electricity demand with the variable supply. While dynamic pricing can incentivize the shifting of flexible loads, its impact on the low-voltage grid remains under-investigated. This thesis explores the impact of dynamic pricing on grid congestion, especially in combination with EV charging and PV systems.


It is hypothesized that while dynamic pricing can effectively shift electricity consumption, it may also lead to concentrated periods of high demand. When consumers synchronize their electricity usage during low-price times, grid congestion can occur.
The study creates a simulation model using Python and PowerFactory to analyse the effects of dynamic pricing on the low-voltage grid. The simulations are based on real-world data from 2023, making use of hourly intervals of loads, EV charging profiles, and solar energy generation across three representative weeks. The model evaluates the voltage levels and power flows to assess the potential for grid congestion under various scenarios of EV and PV adoption.

The results indicate that dynamic pricing can lead to concentrated EV-charging loads, resulting in voltage dips and power spikes. These findings show that the current low-voltage grid may not be equipped to handle the increased demand and variability caused by dynamic pricing schemes. Thus, while dynamic pricing can offer a promising tool for demand-side management, additional measures are necessary to ensure grid stability and to avoid future congestion issues.

In conclusion, the study underscores the dual nature of dynamic pricing as both a valuable tool and a potential risk for the low-voltage grid. Both the voltage and power limits of the grid were found to be causes of congestion, highlighting the need to investigate both. Future research should focus on optimizing dynamic pricing schemes and developing robust grid infrastructure to fully leverage the benefits of renewable energy integration while ensuring grid reliability and resilience.

The effectiveness of ultraviolet (UV) irradiation for disinfection has been well-known for more than a century. Recent advances in light­-emitting diode (LED) technology have brought UV LEDs to the consumer market. These offer many advantages over traditional gas­-discharge lamps, allowing UV radiation to be generated with higher reliability in a much smaller form factor. In this thesis, the design of a portable battery­-powered sterilizer based on UV LEDs is described. The sterilizer is intended for the sterilization of personal items such as mobile phones, face masks, and keys.

The design of the sterilizer consisted of two parts: the LED array and the LED driver. For their design, a model­-based approach was taken to ensure high performance and low cost. For the LED array, a radiometric model was developed and applied in an optimization procedure. The design of the LED driver was based on an analytical loss model in MATLAB and LTspice simulations.

The UV LED array provides a radiant power of 113 mW to the disinfection area, resulting in an irradiation dose of 195 μW/cm2. This allows for more than 99.9% disinfection in less than 15 min. The LED driver is a boost converter operating at 750 kHz in the discontinuous conduction mode. This converter supplies the array with a nominal input power of 4.3 W at a simulated efficiency of 91%.

The design of the LED driver is verified with a prototype. Measurements show efficiencies around 83% at 4.1 W output power. Incorporating several improvements over the prototype, efficiencies between 85–87% can be expected for the LED driver in the sterilizer.