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Communication Dans Un Congrès Année : 1996

Development and Implementation of an Advanced Control System for Autonomous Power Systems Including Renewable Power Sources

Résumé

Autonomous power systems, usually in islands, represent a large potential for the installation of wind farms and photovoltaic plants, especially in the case that important wind and solar resources are available, due to the high cost of electricity production. However, in order to achieve a high level of integration of renewable energy plants, while maintaining a high level of security, an advanced control system must be available to help the power system operators. The objective of the European Community JOULE II Project No JOU2-CT92-0053 has been to develop such an advanced control system that has been installed on the Greek island of Lemnos. The developed control system is aimed to assist the operator of a medium-size autonomous power system by proposing optimal dispatching scenarios for the various power units, as well as various actions needed to avoid dangerous situations which might result from a poor prediction of load or weather conditions. The control system minimises the production costs through an on-line optimal scheduling of the power units which takes into account the technical constraints of the power units, as well as short-term forecasts of the load and the renewable resources. The power system security is certified by an on-line security assessment module, which supervises the scheduling of the power units and enables the power system to be capable of withstanding a number of perturbations caused by the renewable sources without exceeding acceptable limits of frequency variations. The control system is composed by the following five main modules, which are described in detail in this paper : • The economic dispatch module. This module is the basis of the real-time control system, and schedules the operation of the power system for the next time period (e.g. two hours, taking decisions each ten minutes) by taking into account forecasts for the expected load and renewable units power. • The short-term load and renewable power forecasting modules. The developed forecasting models are based on time-series analysis and have been built using past data from the island of Lemnos. The principal method used for load forecasting is the Winter method. A neural network based prediction model has been developed to perform the task of wind power forecasting. • The dynamic security assessment (DSA) module. This module is based on the Decision Trees methodology and its task is to evaluate if a given dispatch policy, suggested by the economic dispatch module for the upcoming minutes is dynamically secure. If the DSA module detects that the power system is insecure the dispatch module is asked to produce other solutions. • The security monitoring module. This module, based on the neural networks methodology, gives the operator the possibility for a real-time evaluation of the degree of dynamic security of the system under its current operating state and relative to a pre-specified severe disturbance that may occur. An advanced software having real time performance and a sophisticated man machine interface, has been developed. The various modules, that perform the control system functions have been integrated in the software and validated with real data obtained by the existing Data Acquisition system of Lemnos. The control system was installed in Lemnos in January 1995. The power system operators were trained and an on-line evaluation of the control system performance started. The up to day results are presented in the paper and show that the control system is able to represent correctly the power system behavior and to propose to the operators optimal actions resulting in the expected benefits.
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hal-04264832 , version 1 (30-10-2023)

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  • HAL Id : hal-04264832 , version 1

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Eric Nogaret, George Stavrakakis, Georges Kariniotakis, Michael Papadopoulos, Nikos Hatziargyriou, et al.. Development and Implementation of an Advanced Control System for Autonomous Power Systems Including Renewable Power Sources. 31st International Universities Power Engineering Conference - UPEC96, IEEE, Sep 1996, Heraklion, Greece. ⟨hal-04264832⟩
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