This thesis describes the design and implementation of a subsystem within a larger medical monitoring system. This subsystem will make bidirectional audio communication possible between a patient and their caregivers or family members. The patient in question can be premature babies that have to stay inside of incubators and elderly people that need to be monitored for their health. The designed subsystem is tasked with creating an audio stream that goes bidirectionally between a speaker with a handsfree functionality and the front end via a server. On the server the audio from the patient should be stored on a hard drive. Whether the audio communication should be stopped or started and whether the audio should be stored will be controlled by the front-end user. Initially the goal was to implement the solution on a Pine singleboard computer (SBC), but due to unforeseen delays of the delivery of the necessary Pine SBC, it was decided that a proof of concept would be developed. The future work in this thesis will discuss the portability of the solution to the Pine SBC.

In response to the urgent need for sustainable energy solutions and climate change mitigation, international agreements such as the Paris Agreement have been instrumental in advocating reduced greenhouse gas emissions. As the world shifts towards renewable energy sources and electrification, there arises a heightened challenge of increased congestion and a greater demand for flexibility within electrical networks. Batteries emerge as a crucial source of added flexibility and congestion relief. However, these commercially owned batteries are not obliged to assist with grid congestion, possibly focusing solely on energy arbitrage pursuits for example. This thesis undertakes an exploration of optimizing the efficiency of energy arbitrage batteries by repositioning them to alleviate congestion. Additionally, it delves into the divergence between preferred battery locations for grid operators and battery owners. A comparative analysis is performed among energy arbitrage batteries, congestion relief batteries, and traditional reinforcements. These aspects are evaluated in terms of their contribution to grid flexibility, congestion relief, and load curtailment requirements. The study is conducted using a medium voltage network of a region in the North Rotterdam as a case study. The investigation involves the creation of a linear programming day-ahead market model and a linear programming energy arbitrage battery model. The day-ahead market model generates a price signal that guides the energy arbitrage battery’s charging and discharging decisions for profit maximization. Load and generation forecasts are provided by Stedin for the case study. A Powerfactory model simulates the effect of a congestion relief battery capacity on congestion. Through a heuristic algorithm, the optimal location and size of the energy arbitrage battery capacity are determined. By analyzing these scenarios, the study unveils the positive impact of strategically positioned energy arbitrage batteries that align discharge timing with congestion patterns. The study also highlights the significance of positioning batteries at the deepest points of radial lines to maximize benefits, even though these locations may diverge from battery owner preferences, such as solar farm sites. Interestingly, the addition of energy arbitrage batteries to these solar farm sites can exacerbate congestion due to their relatively low congestion levels. A comparative evaluation reveals that batteries surpass traditional grid reinforcement in enhancing flexibility, with congestion relief batteries outperforming energy arbitrage batteries in alleviating congestion. With the energy arbitrage battery being able to reduce congestion by 27% and the congestion relief batteries being able to reduce it by 94% with the same amount of installed capacity. Energy arbitrage scenarios may necessitate load curtailment to address congestion challenges, they may not independently resolve all congestion. In conclusion, while energy arbitrage batteries show promise in addressing congestion, their effectiveness depends on synergistic technologies and further refinement. Future research avenues may explore enhanced market models, extended predictive analyses, and intricate hybrid strategies to tackle congestion relief, considering the intricate complexities introduced by diverse network topologies.