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Inteligentne cyfrowe liczniki energii elektrycznej jako element systemu Smart Power Grids. Cz. 1

100%

Piotrowski P.

tom nr 6

72--75

Dwuczęściowy artykuł dotyczy wybranych aspektów inteligentnych liczników w systemie Smart Power Grids. Skupiono się w nim na charakterystyce Inteligentnych liczników, korzyściach i kosztach wprowadzania systemów inteligentnego opomiarowania. Przedstawiono aktualny stan wdrożeń systemów inteligentnego opomiarowania w Unii Europejskiej, w tym w Polsce. Omówiono wy-brane problemy bezpieczeństwa w systemach Smart Power Grids. Sformułowano ponadto końcowe uwagi i wnioski.

The two parts paper concerns the chosen aspects of smart meters in Smart Power Grids systems. It focuses on features of smart meters as well as the benefits and the costs of the smart metering systems implementation. The present situation of smart metering systems implementation in the European Union including Poland has been showed. Chosen aspects of safety problems have been discussed. The final conclusions and remarks have been formulated.

Cybersecurity Risk Analysis and Threat Assessment Within Smart Electrical Power Distribution Grids

99%

Czechowski R.

tom Nr 7

19--28

Development Of Electrical Power Systems And Their Integration With An Increasing Number Of Smart Automation Devices Compel To Undertake A New Approach To The Issue Of The System’s Security. Reliability Of An Electrical Power System And High Service Availability Are The Essential Characteristics Of Efficient Strategic Electricity Customers, I.E.: Large Industrial Facilities, Railway Transport, Medical Service Providers And Life-Saving Institutions. The Time Of Manual Or Automatic System Recovery After A Failure, Which Increases Its Security, Is Not Without Significance, Either. The Article Discusses The Issues Of Risk Assessment And Management, Including The Overall Process Of Analysis And Assessment Of Threat Probability In Electrical Power Systems.

Security policy and good practice for implementation of smart grid solutions

71%

Czechowski R.

tom R. 92, nr 3

177--181

Smart Grid jest koncepcją i zarazem sposobem na złagodzenie braków infrastrukturalnych oraz przeciwdziałania skutkom rosnącego popytu na energię elektryczną. Jednym ze sposobów zapewniających wzrost efektywności zarządzania elektroenergetycznego jest wykorzystanie najnowszych rozwiązań komunikacyjnych. Rozwiązania takie zapewniają mniejsze zużycie energii, wyrównanie krzywej dobowego obciążenia, zmniejszenie strat dzięki automatycznego bilansowania energii i większe bezpieczeństwo transferu.

Smart Grid is both a concept and a way to mitigate infrastructural deficiencies and counteract the effects of the growing demand for electrical energy. One of the ways ensuring an increase in power grid’s management efficiency is utilization of the latest communication solutions. Such solutions ensure reduced energy consumption and leveling cur ve of daily load, decreased losses and – thanks to automated energy balancing – increased transfer security.

Towards fully decentralized multi-objective energy scheduling

57%

Bremer J. , Lehnhoff S.

2019

tom Vol. 18

193--201

Future demand for managing a huge number of individually operating small and often volatile energy resources within the smart grid is preponderantly answered by involving decentralized orchestration methods for planning and scheduling. Many planning and scheduling problems are of a multi-objective nature. For the single-objective case - e.g. predictive scheduling with the goal of jointly resembling a wanted target schedule - fully decentralized algorithms with self-organizing agents exist. We extend this paradigm towards fully decentralized agent-based multi-objective scheduling for energy resources e.g. in virtual power plants for which special local constraint-handling techniques are needed. We integrate algorithmic elements from the well-known S-metric selection evolutionary multi-objective algorithm into a gossiping-based combinatorial optimization heuristic that works with agents for the single-objective case and derive a number of challenges that have to be solved for fully decentralized multi-objective optimization. We present a first solution approach based on the combinatorial optimization heuristics for agents and demonstrate viability and applicability in several simulation scenarios.