Intelligent energy management of electrical power systems with distributed feeding on the basis of forecasts of demand and generation

Abstract

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.

Distributed Intelligent Energy Management System for a Single-Phase High-Frequency AC Microgrid

“…So, the energy management has to perform energy scheduling a single day or multiple days ahead. An intelligent energy management system is thus required which enables short-term energy allocation scheduling at minimum costs based on power generation and load demand [7].…”

“…However, on the other hand, designing an efficient controller needs prediction of the generation with considerable accuracy [7]. Forecast of generation is not a very old topic and its relevance increases rapidly with more penetration of renewable energy sources in the power grid.…”

“…The forecast of generation is a challenging task for the Microgrid system as the sources connected are mainly the renewable energy sources where the capacity of generation varies largely with the external conditions like sunshine, temperature, etc. [7].…”

Intelligent Control of a Distributed Energy Generation System Based on Renewable Sources

“…One of the first papers was published in 2001 and concerns intelligent energy management considering energy sources like photovoltaic, wind and conventional power plants, and dealing with the optimization of the system using energetic, ecological and economical criteria [14]. One of the approaches used in the following years was the supervisory control, considering different structures for the distributed energy systems: stand-alone system, including wind and solar energy sources [15], or grid-connected system [16], also including wind and solar energy sources, where multiple supervisory control strategies are considered.…”

“…This paper deals with the hierarchical control of distributed systems for the generation and use of electrical energy based on renewable sources based on artificial intelligence techniques. The proposed structure of the control system distinguishes itself from the proposals in the literature [14][15][16][17][18][19][20][21][22] by the following features:…”