<p>Distribution grid companies and distribution system operators (DSOs) still mostly follow a traditional framework for grid planning. Such frameworks have so far served DSOs well in the economic assessment and cost-benefit analysis of passive measures, such as grid reinforcement. However, the development towards active distribution grids requires DSOs to also be able to assess an extended set of active measures. To this aim, this paper extends and implements a general planning framework for active distribution grids that builds upon the well-proven traditional framework. The methodology integrated in the framework includes: 1) decoupled models for i) operation with active measures and ii) optimal grid investment, and 2) methods for economic assessment considering active measures from both i) a DSO cost-benefit analysis perspective and ii) a willingness-to-pay perspective. In this paper, operational models are integrated for two examples of active measures, namely the use of fast-charging stations (FCS) and local energy communities (LEC). The methodology is demonstrated in a long-term grid planning case study for a realistic Norwegian medium voltage distribution system. For this case, grid planning with FCS as an active measure reduces the present value of grid investment costs by 70% compared with a passive grid planning strategy. The results also demonstrate how the methodology can be used in negotiating the price of active measures between the DSO and distribution system actors such as LEC and FCS operators.</p>
Modern society is to a larger and larger extent dependant on electric energy, and hence the reliance on and utilization of the electric grid is increasing steadily. At the same time the production and consumption patterns are changing from large centralized generation of electric power and pure consumers to distributed generation (DG) and more complex consumers. This transition causes higher stress on an aging infrastructure and major investments are required over the coming years to maintain a reliable supply of electric energy. Better monitoring solutions and predictive methods can increase the possible utilization of the existing grid and reduce the fault frequency. This paper presents some current challenges in the grid and a possible monitoring solution and fault prediction method. This is exemplified with statistics and field-measurements from the Norwegian power grid.
Electrification of mobility is paving the way in decreasing emissions from the transport sector; nevertheless, to achieve a more sustainable and inclusive transport system, effective and long-term planning of electric vehicles charging infrastructure will be crucial. Developing an infrastructure that supports the substitution of the internal combustion engine and societal needs is no easy feat; different modes of transport and networks require specific analyses to match the requirements of the users and the capabilities of the power grid. In order to outline best practices and guidelines for a cost-effective and holistic charging infrastructure planning process, the authors have evaluated all the aspects and factors along the charging infrastructure planning cycle, analysing different methodological approaches from scientific literature over the last few years. The review starts with target identification (including transport networks, modes of transport, charging technologies implemented, and candidate sites), second, the data acquisition process (detailing data types sources and data processing), and finally, modelling, allocation, and sizing methodologies. The investigation results in a decision support tool to plan high-power charging infrastructure for electric vehicles, taking into account the interests of all the stakeholders involved in the infrastructure investment and the mobility value chain (distributed system operators, final users, and service providers).
The transport sector is responsible for 20 % of the global CO2 emissions. By transitioning from internal-combustion engine to battery-electric vehicles, there is a big potential in reducing the emissions. The upcoming heavy-duty electric vehicles (HDEVs) are expected to have a charging power between 100-1600 kW. A transition to HDEVs can cause challenges to the power grid to deliver the charging power needed. In this paper, a methodology to model the load profile of a high-power charging station for HDEVs is proposed. Generated load profiles with different future shares of HDEVs are used to study the impact on the power grid in a representative area in Norway. The loading of the regional substation exceeds its rated capacity when the share of HDEV is 25%, and its thermal limit when the share is increased to 50%. Extending the mandatory breaks for the drivers, and a corresponding reduction of the charging power, shows promising results.
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