Power control of flexible loads will play a significant role in energy transition. This work has developed a mixed-integer linear power control (MILP) model that manages electric vehicle (EV) chargers, heat pumps (HPs), and PV rooftops. The power control was tested with and without vehicle-to-grid (V2G) capabilities in different grid types, namely residential, commercial, and mixed grids. Moreover, the effect of different seasons and charger efficiencies was investigated. It was shown that grid characteristics such as EV parking times and building occupations can affect significantly the power control, e.g. the amount of imported and V2G power. Moreover, while V2G power is rarely used due to current V2G round-trip efficiency, future efficiency improvement can lead to a significant increase in V2G use. Finally, the seasonal effect had also a significant impact with Summer being characterized by higher exported and lower imported energy due to the high and prolonged PV power availability.

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This paper proposes a shared multi-stakeholder PV system for traction substations and nearby residential loads to reduce the need for storage, AC grid exchange, and curtailment. The residential stakeholders offer both the base electrical load and the solar panels installation space needed by the traction stakeholder, who brings the peak load and investments to the former. Two case studies were conducted for one year in the city of Arnhem, The cy=Netherlands, using comprehensive and verified simulation models: A high-traffic and a low-traffic substation. The results showed a positive, synergetic benefit in reducing the PV system's excess energy and size requirement for any type of traction substations connected to any number of households. In one detailed example, the multi-stakeholder system suggested in this paper is shown to reduce curtailment by up to 80% in moments of zero-traction load. Generally, the direct load coverage of a PV system is increased by as much as 7 absolute percentage points to the single-stakeholder system when looking at energy-neutral system sizes. This multi-stakeholders system offers then an increase in the techno-economic feasibility of PV system integration in urban loads.

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Low Carbon Technologies (LCTs), such as Photovoltaics (PVs), Electric Vehicles (EVs), and Heat Pumps (HPs), are expected to cause a huge electric load in future distribution grids. This paper investigates the grid impact in terms of over-loading and nodal voltage deviations in different distribution grids due to increasing LCT penetrations. The major objectives are the identification of the most severe LCT, grid impact issue, seasonal effect, and vulnerable distributional area, considering the physical models of the LCTs. It is concluded that Winter is the most hazardous for the future grid impact, characterized by nearly 3 times higher over-loading and 2.5 times higher voltage deviations during high HP penetrations, while suburban areas are the most vulnerable. Moreover, while HPs seem to have, in general, a greater impact compared to EVs, EVs cause more prolonged violations. While this work follows a bottom-up approach, using detailed physical models, aggregated national data has also been acquired, which is often used by top-down approaches. Different grid impact issues have been compared for the two approaches in terms of magnitude and duration. While bottom-up approaches generate more pessimistic results regarding the magnitude of the violations, results about the duration of the violations can be contradictory.

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An important aspect of the energy transition is the expected grid impact due to the abrupt increase of distributed electric generation and electric load demand. A part of this impact is going to be inflicted by the electrification of heating with heat pumps (HPs). Therefore, it is essential that the future power consumption of electric heating is estimated. This work develops a power estimation model without the use of heating demand data, needing only weather data and building heat pump specifications. Moreover, it is characterized as a risk-averse estimation since it uses no optimal control and utilizes the heat pump output capacity curves giving simultaneous priority to the customers' thermal comfort. Finally, it also estimates the power savings of electric heating due to future buildings' new insulation and energy label norms, revealing their importance.

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Smart-Charging of Electric Vehicles (EVs) is able to provide frequency regulation capacity services to the System Operator (SO) upon an automation generation control (AGC) signal. While the amount of available regulation capacity is of-fered in the Day-Ahead Market (DAM), there is high uncertainty on the actual amount of reserves that will be called in the Real-Time Market (RTM). This work focuses on aiding EV smart-charging to offer a consistent and reasonable amount of regulation capacity, taking into account the impact of potential future instantaneous called regulation reserves while also maintaining simplicity. The work also analyzes the results of different charger types with different characteristics and shows that they play an important role on the regulation provision. Finally, it has been shown that even though the regulation income is inevitably reduced (up to 66%), the Energy Management System (EMS) can still successfully charge the EV s and simultaneously provide regulation reserves with remuneration.@en