To guarantee power supply with a required service reliability every time in an economical, ecological and resource saving way utilities have to schedule the energy allocation for the next day. In addition to forecasts of the demand this planning is based on forecasts of the non-schedulable supply by distributed plants using renewable energy resources. Although this portion is difficult to predict renewable energies gain more importance because of political guidelines and social trends in Germany. This prediction task is complicated further by the fact that in deregulated markets the system has to respond to changes in load demand fast and at low cost.
In many emerging countries, like on the Arabian Peninsula or China, new cities are planned and built from scratch in areas with no existing infrastructure. The load density is expected to become very high within the next 10 to 15 years. To handle such high load densities network structures for the distribution networks are required which are characterized by a very high flexibility and scalability. Based on the example of Dubai Waterfront planning steps for such networks are presented and explained.
With the expected charging characteristic of e-mobility a considerable load peak during the night is expected. Photovoltaic and small wind power systems will further increase the load fluctuations. The paper describes the application of a modified maximum rectangle algorithm to determine the optimal starting times for charging electric cars to realise a flat load curve. The load characteristic of electric cars is similar to night storage heating devices. This allows to use these currently widely spread devices as example for developing and testing methods for optimized load management in low and medium voltage networks. It is shown that the developed optimization algorithm finds solutions close to the global optimum even with a huge number of devices (≈15 000) with low requirements of calculation time (<1 min).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.