SmartGrid is the natural evolution for the control and optimization of electric grid operation, improving quality of service and reducing costs. The implementation of the SmartGrid means evolving the SCADA and DMS systems from systems that aid humans in the management of the power network to intelligent semiautonomous systems with a reduced human element. The introduction of Distributed Energy Resources (DER) and Demand Response (DR) are changing the character of the electrical network managed by the new systems. Consumers pass from clients to active agents, contributing interactively [1] to network management and thus Quality of Service (QoS). This paper indicates how the new systems must use selfdescribing equipment, standardised data models and protocols, must integrate with other corporate systems as both information vendors and purchasers, to achieve these while maintaining high data quality with acceptable costs of data capture and maintenance
This paper presents an innovative approach to outage detection and management using a big data stream processing system. The system, SINAPSE, enables customers to send power-related events in electricitypowered assets over the internet, correlates such events in space and time to detect grid outages, and provides realtime feedback to customers on known outages.
This is a joint paper between EDP Distribuição (Portuguese Distribution System Operator) and KEMA Consulting (Dutch based international consultant, specialized in energy), which describes the decision, development and expected benefits regarding EDP's Distribution Automation (DA) project. The DA project team felt the need to innovate in some aspects. Decisions are based on the balance of technical performance (outage minutes reduction) and economical performance (DA deployment total costs), related through the monetary value of Energy Not Delivered. The optimal number of DA devices and optimal locations are determined with two types of new tools. The first is a heuristic easy to use tool applied for most of the feeders. The second tool is based on genetic algorithms and dedicated reliability analysis (electrical and geographical computer model); it is used for rules extraction and validation of the first tool. Outcomes are also used to benchmark the results per feeder in order to achieve an investment portfolio based on relative marginal benefits. Validation for a pilot network shows that both tools yield consistent results. EDP intends to start a field pilot before the progressive roll-out.
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