Traditional power grid planning is based on passive measures such as grid reinforcement and using present value calculations to compare grid development plans. However, this approach does not accurately represent the real options value of using active measures such as demand-side flexibility for post-poning grid reinforcement through a ”wait-and-see” approach to manage the long-term uncertainty in load growth. However, the value of using active measures may come at the price of reducing the security margins in grid operation. This leads to an increased risk of operational challenges during operation, and this risk must be weighed against the value of using active measures. This paper presents a methodology for quantifying both the value and risk (or price) of real options related to grid development strategies using active measures, providing grid planners with more comprehensive information about the advantages and disadvantages. The methodology is demonstrated using an illustrative and simple case for a medium voltage reference distribution system, where flexibility from local energy communities is considered as an example of an active measure. The case study illustrates how some risk-taking is required to realize the value from using active measures.

Local energy communities are forming as a way for prosumers and consumers to invest in distributed renewable energy sources, community storage and share electricity. Meanwhile, several distribution grids have voltage problems at certain hours of the year. Local energy communities consisting of generation and storage units might be valuable flexible assets that the distribution system operator (DSO) can make use of. This article aims to study how a battery in an energy community can provide services to the distribution grid, by creating a linear optimisation model which includes power flow constraints and a battery degradation model. First, we investigate how the battery operation of an energy community impacts the voltage in the nearby buses. We find that when including the degradation model, the voltage limits are violated much less than when not including the degradation model. Next, we investigate how the battery operation differs when the energy community cooperates with an active DSO to share the battery use, and quantify how much the DSO should remunerate the energy community. We find that the energy community should get 15 \euro per year due to an increase in electricity and degradation costs, which equals an increase of 0.12%, compared to when the community is not providing a service. Finally, a sensitivity analysis is performed to determine which parameters are more important to consider. We find that voltage violations in the grid are sensitive to the battery replacement cost, electric vehicle charging peak and the average spot price, while the remuneration from the DSO is sensitive to the battery replacement cost. For small battery sizes and a low power-to-energy ratio, the community is not able to improve the voltage at all hours of the year.

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.