Simulation of Curative Congestion Management in Large-Scale Transmission Grids

Author(s):  
Andre Hoffrichter ◽  
Katharina Kollenda ◽  
Maximilian Schneider ◽  
Ralf Puffer
Author(s):  
Zhengfu Liu ◽  
Qifu Lu ◽  
Xiangyu Kong ◽  
Hongxing Wang ◽  
Chao Sheng ◽  
...  

Author(s):  
Bo Chen ◽  
Harry H. Cheng ◽  
Joe Palen

Agent technology is rapidly emerging as one of the powerful technologies for the development of large-scale distributed systems to deal with the uncertainty in a dynamic environment. The domain of traffic and transportation systems is well suited for an agent-based approach because systems are usually geographically distributed in dynamic changing environments. Our literature survey shows that the techniques and methods resulted from the field of agent and multi-agent systems have been applied to many aspects of traffic and transportation systems, including modeling and simulation, dynamic routing and congestion management, intelligent traffic management, and urban traffic signal control. This paper examines agent-based approach and its applications in roadway traffic and transportation systems, and discusses several future research directions towards successful deployment of agent technology in traffic and transportation systems.


Author(s):  
Majid Moazzami ◽  
Hossein Shahinzadeh ◽  
Gevork B. Gharehpetian ◽  
Abolfazl Shafiei

Congestion management is one of the important issues in the deregulated power systems. There are several methods to eliminate congestion. Utilizing FACTS devices is an appropriate option for large-scale and quick control of flows of transmission lines. FACTS devices such as Thyristor Controlled Series Capacitor (TCSC) can help to mitigate the transmitting flow of power in the congested lines, which leads to an increase in the network loading ability as well as reduction of both losses and production costs. Due to the considerably high price of FACTS devices, it is important to determine their optimum location on the network. Accordingly, in this paper, the Antlion optimization algorithm (ALO) has been employed to conduct a congestion management analysis to determine the optimal location for the installation of TCSC, which is simulated on an IEEE 14-bus test system subject to satisfy the constraints of the market environment.


2021 ◽  
Vol 238 ◽  
pp. 05005
Author(s):  
Alvaro Gonzalez-Castellanos ◽  
Priyanko Guha Thakurta ◽  
Aldo Bischi

Congestion caused in the electrical network due to renewable generation can be effectively managed by integrating electric and thermal infrastructures, the latter being represented by large scale District Heating (DH) networks, often fed by large combined heat and power (CHP) plants. The CHP plants could further improve the profit margin of district heating multi-utilities by selling electricity in the power market by adjusting the ratio between generated heat and power. The latter is possible only for certain CHP plants, which allow decoupling the two commodities generation, namely the ones provided by two independent variables (degrees-of-freedom) or by integrating them with thermal energy storage and Power-to-Heat (P2H) units. CHP units can, therefore, help in the congestion management of the electricity network. A detailed mixed-integer linear programming (MILP) optimization model is introduced for solving the network-constrained unit commitment of integrated electric and thermal infrastructures. The developed model contains a detailed characterization of the useful effects of CHP units, i.e., heat and power, as a function of one and two independent variables. A lossless DC flow approximation models the electricity transmission network. The district heating model includes the use of gas boilers, electric boilers, and thermal energy storage. The conducted studies on IEEE 24 bus system highlight the importance of a comprehensive analysis of multi-energy systems to harness the flexibility derived from the joint operation of electric and heat sectors and managing congestion in the electrical network.


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