An Analytical Method for Supply-Demand Situation Awareness of Power Systems Based on Classification of Action Levels to Balance Supply and Demand

Author(s):  
Ryuya Tanabe ◽  
Akihiko Yokoyama
Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3970
Author(s):  
Marie-Louise Arlt ◽  
David P. Chassin ◽  
L. Lynne Kiesling

Transactive energy systems (TS) use automated device bidding to access (residential) demand flexibility and coordinate supply and demand on the distribution system level through market processes. In this work, we present TESS, a modularized platform for the implementation of TS, which enables the deployment of adjusted market mechanisms, economic bidding, and the potential entry of third parties. TESS thereby opens up current integrated closed-system TS, allows for the better adaptation of TS to power systems with high shares of renewable energies, and lays the foundations for a smart grid with a variety of stakeholders. Furthermore, despite positive experiences in various pilot projects, one hurdle in introducing TS is their integration with existing tariff structures and (legal) requirements. In this paper, we therefore describe TESS as we have modified it for a field implementation within the service territory of Holy Cross Energy in Colorado. Importantly, our specification addresses challenges of implementing TS in existing electric retail systems, for instance, the design of bidding strategies when a (non-transactive) tariff system is already in place. We conclude with a general discussion of the challenges associated with “brownfield” implementation of TS, such as incentive problems of baseline approaches or long-term efficiency.


2019 ◽  
Vol 2 (S1) ◽  
Author(s):  
Friederike Wenderoth ◽  
Elisabeth Drayer ◽  
Robert Schmoll ◽  
Michael Niedermeier ◽  
Martin Braun

Abstract Historically, the power distribution grid was a passive system with limited control capabilities. Due to its increasing digitalization, this paradigm has shifted: the passive architecture of the power system itself, which includes cables, lines, and transformers, is extended by a communication infrastructure to become an active distribution grid. This transformation to an active system results from control capabilities that combine the communication and the physical components of the grid. It aims at optimizing, securing, enhancing, or facilitating the power system operation. The combination of power system, communication, and control capabilities is also referred to as a “smart grid”. A multitude of different architectures exist to realize such integrated systems. They are often labeled with descriptive terms such as “distributed,” “decentralized,” “local,” or “central." However, the actual meaning of these terms varies considerably within the research community.This paper illustrates the conflicting uses of prominent classification terms for the description of smart grid architectures. One source of this inconsistency is that the development of such interconnected systems is not only in the hands of classic power engineering but requires input from neighboring research disciplines such as control theory and automation, information and telecommunication technology, and electronics. This impedes a clear classification of smart grid solutions. Furthermore, this paper proposes a set of well-defined operation architectures specialized for use in power systems. Based on these architectures, this paper defines clear classifiers for the assessment of smart grid solutions. This allows the structural classification and comparison between different smart grid solutions and promotes a mutual understanding between the research disciplines. This paper presents revised parts of Chapters 4.2 and 5.2 of the dissertation of Drayer (Resilient Operation of Distribution Grids with Distributed-Hierarchical Architecture. Energy Management and Power System Operation, vol. 6, 2018).


2014 ◽  
Vol 643 ◽  
pp. 99-104
Author(s):  
Jin Yang ◽  
Yun Jie Li ◽  
Qin Li

In this paper, the process of the developments and changes of the network intrusion behaviors were analyzed. An improved epidemic spreading model was proposed to study the mechanisms of aggressive behaviors spreading, to predict the future course of an outbreak and to evaluate strategies to control a network epidemic. Based on Artificial Immune Systems, the concepts and formal definitions of immune cells were given. And in this paper, the forecasting algorithm based on Markov chain theory was proposed to improve the precision of network risk forecasting. The data of the Memory cells were analyzed directly and kinds of state-spaces were formed, which can be used to predict the risk of network situation by analyzing the cells status and the classification of optimal state. Experimental results show that the proposed model has the features of real-time processing for network situation awareness.


2015 ◽  
Vol 43 (19) ◽  
pp. 2178-2188 ◽  
Author(s):  
Ana Claudia Barros ◽  
Mauro S. Tonelli-Neto ◽  
José Guilherme Magalini Santos Decanini ◽  
Carlos Roberto Minussi

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