A smart distribution toolbox for distribution system planning

Paper 1623The distribution system planner should be able to coordinate smart grid solutions in order to find cost effective expansions plans. These plans should be able to deal with new added system uncertainties from renewable production and consumers while guaranteeing power quality and availability of supply. This paper proposes a structure for distribution systems planning oriented to help the planner in deciding how to make use of smart solutions for achieving the described task. Here, the concept of a system planning toolbox is introduced and supported with a review of relevant works implementing smart solutions. These are colligated in a way that the system planner can foresee what to expect with their combined implementation. Future developments in this subject should attempt to theorize a practical algorithm in an optimization and decision making context.postprin

Integrating lv network models and load-flow calculations into smart grid planning

Increasing energy prices and the greenhouse effect demand a more efficient supply of energy. More residents start to install their own energy generation sources such as photovoltaic cells. The introduction of distributed generation in the low-voltage network can have effects that were unexpected when the network was designed and could lead to a bad power quality. These developments ask for better insight in the effects of a planning for a fleet of households in a network. This paper presents the results of adding network models to planning strategies. Forward-backward load-flow calculations for a three phase low-voltage network are implemented to simulate the network. The results from load-flow calculations are used as feedback for demand side management. The results in this paper show that the implementation is both fast and accurate enough for integration purposes. Combining load-flow feedback and demand side management leads to improved worst-case voltage levels and cable usage whilst peakshaving optimization performance does not degrade significantly. These results indicate that load-flow calculations should be integrated with demand side management methodologies to evaluate whether networks support the effects of steering production and consumption. More sophisticated integration of network models are left for future work