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Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data
(2023)
The transition towards climate neutrality will result in an increase in electrical vehicles, as well as other electric loads, leading to higher loads on electrical distribution grids. This paper presents an optimisation algorithm that enables the integration of more loads into distribution grid infrastructure using information from smart meters and/or smart meter gateways. To achieve this, a mathematical programming formulation was developed and implemented. The algorithm determines the optimal charging schedule for all electric vehicles connected to the distribution grid, taking into account various criteria to avoid violating physical grid limitations and ensuring non-discriminatory charging of all electric vehicles on the grid while also optimising grid operation. Additionally, the expandability of the infrastructure and fail-safe operation are considered through the decentralisation of all components. Various scenarios are modelled and evaluated in a simulation environment. The results demonstrate that the developed optimisation algorithm allows for higher transformer loads compared to a P(U) control approach, without causing grid overload as observed in scenarios without optimisation or P(U) control.
This paper presents a series of flow and temperature measurements on the principal heat network of :metabolon in Lindlar, Germany. These measurements intend to show the behaviour of the system on specific production areas of :metabolon for future monitoring and optimisation purposes. Such measurements allow the analysis of the system’s heat flow through the network, which showed that losses exist, some areas. The results demonstrate successfully that the temperature and flow changes deserve more detailed and fixed monitoring in specific areas to help the user decide the optimum measuring point.