On Load–Frequency Regulation With Time Delays: Design and Real-Time Implementation

2009 ◽  
Vol 24 (1) ◽  
pp. 292-300 ◽  
Author(s):  
H. Bevrani ◽  
T. Hiyama
Keyword(s):  
Real Time ◽  
Time Delays ◽  
Frequency Regulation ◽  
Load Frequency

Real-time adjustment of load frequency control based on controllable energy of electric vehicles

2019 ◽  
Vol 42 (1) ◽  
pp. 42-54 ◽  
Author(s):  
Qian Zhang ◽  
Yan Li ◽  
Chen Li ◽  
Chun-yan Li
Keyword(s):  
Real Time ◽  
Electric Vehicles ◽  
Time Allocation ◽  
State Transition ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Frequency Regulation ◽  
Dynamic Changes ◽  
Load Frequency ◽  
Electric Car

The time-varying characteristics of electric vehicle (EV) controllable energy and the rationality of frequency regulation (FR) demand power allocation have significant influences on participating in system FR. Combined with the state transition characteristics of EVs, the calculation models of real-time controllable quantities and real-time controllable energy of EVs are established. Then, considering the dynamic changes of EVs’ controllable energy, the system FR strategy with real-time adjusting scheme of FR coefficients is put forward. Finally, based on the unit participation time contribution, the selecting strategy for individual EVs to participate in FR is proposed. The simulation results show that based on the calculation of EVs’ real-time controllable energy, the proposed load frequency control model with real-time allocation of FR demand power suppresses the frequency deviation effectively, and the private electric car is found to have the most potential for the FR system.

scholarly journals Exponential Stability for Multi-Area Power Systems with Time Delays Under Load Frequency Controller Failures

2016 ◽  
Vol 19 (2) ◽  
pp. 787-791 ◽  
Author(s):  
Xu Li ◽  
Rui Wang ◽  
Shu-Nan Wu ◽  
Georgi M. Dimirovski
Keyword(s):  
Power Systems ◽  
Exponential Stability ◽  
Time Delays ◽  
Load Frequency ◽  
Frequency Controller

scholarly journals Co-Optimizing Battery Storage for Energy Arbitrage and Frequency Regulation in Real-Time Markets Using Deep Reinforcement Learning

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8365
Author(s):  
Yushen Miao ◽  
Tianyi Chen ◽  
Shengrong Bu ◽  
Hao Liang ◽  
Zhu Han
Keyword(s):  
Real Time ◽  
Critical Role ◽  
Frequency Regulation ◽  
Power Networks ◽  
Physical Constraints ◽  
Policy Gradient ◽  
Markov Decision ◽  
Battery Energy Storage Systems ◽  
Complex Decision Making ◽  
Battery Energy

Battery energy storage systems (BESSs) play a critical role in eliminating uncertainties associated with renewable energy generation, to maintain stability and improve flexibility of power networks. In this paper, a BESS is used to provide energy arbitrage (EA) and frequency regulation (FR) services simultaneously to maximize its total revenue within the physical constraints. The EA and FR actions are taken at different timescales. The multitimescale problem is formulated as two nested Markov decision process (MDP) submodels. The problem is a complex decision-making problem with enormous high-dimensional data and uncertainty (e.g., the price of the electricity). Therefore, a novel co-optimization scheme is proposed to handle the multitimescale problem, and also coordinate EA and FR services. A triplet deep deterministic policy gradient with exploration noise decay (TDD–ND) approach is used to obtain the optimal policy at each timescale. Simulations are conducted with real-time electricity prices and regulation signals data from the American PJM regulation market. The simulation results show that the proposed approach performs better than other studied policies in literature.

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