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Distribution systems operator (DSO's) are facing significant challenges in network planning due to the integration of distributed energy resources (DER), smart grid technologies, E-mobility, regulation and volatile market conditions. In the previous work, it was shown (a) how DSO's are able to optimise planning of network assets in the presence of...
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Citations
... The evolution of power systems introduces new challenges in terms of operation and planning, and current research is demonstrating how local services (provided by flexible demand/generation/storage) can compete with the conventional network reinforcement at any voltage level. In fact, literature [1]- [8] proposes many distribution network planning strategies aimed at determining the best trade-off between local flexibility and new lines/transformers. All of them are clearly showing how the current practices (based on manual procedures and worst-case scenarios analysis) are not leading to optimal solutions. ...
Modern planning techniques for distribution systems consider, in addition to the conventional grid reinforcement, the provision of power flexibility from local resources. This solution is demonstrated to be cost-effective in numerous cases. However, distribution resources might be required to provide services to transmission system too, and this aspect needs to be considered within the selection of the best distribution planning options. This paper investigates a distribution network planning strategy based on different trade-offs between "minimization of investment costs" and "maximization of distribution flexibility for transmission services", which is aimed at supporting a cooperative (but decoupled) planning for both distribution and transmission systems.
... As part of the research project "Agent.GridPlan" the functionality of the agent-based simulation SIMONA has been extended to interact with an existing automated genetic grid extension planning algorithm, that uses the results from SIMONA to propose grid extensions in case of a congestion. [4], [5] In the first part of the paper the overall concept of the developed coupled simulation framework and its functionality are outlined. Afterwards, the extensions and adjustments of the used simulation approaches are described in detail, subsequently followed by a small application example. ...
In recent years, the distribution grid planning process has faced the big challenge to integrate renewable energy sources in its planning methodology while preserving a secure and stable provision of electricity. With the currently observable efforts to electrify human mobility all around the world, another new challenge arises for the planning and operation of distribution grids. To address these challenges and to leverage the opportunities that are accompanied by them, new methods for the planning of distribution grids as well as planning decision-supportive approaches and algorithms are needed. The presented approach contributes to the described demands by means of a coupled approach, using both distribution grid time series as well as a genetic algorithm to support decision making in the planning process considering not only new assets for grid reinforcements and extensions but also smart-grid and operational opportunities.