Vector Measurement based Virtual Inertia Emulation Technique for Real-Time Transient Frequency Regulation in Microgrids

2020 ◽  
pp. 1-1
Author(s):  
Pritam Bhowmik ◽  
Pravat Rout ◽  
Josep GE M Guerrero ◽  
Abdullah M Abusorrah
Keyword(s):  
Real Time ◽  
Frequency Regulation ◽  
Vector Measurement ◽  
Virtual Inertia

A comprehensive comparison of Virtual Synchronous Generators with focus on virtual inertia and frequency regulation

2021 ◽  
Vol 201 ◽  
pp. 107516
Author(s):  
Vincenzo Mallemaci ◽  
Fabio Mandrile ◽  
Sandro Rubino ◽  
Andrea Mazza ◽  
Enrico Carpaneto ◽  
...  
Keyword(s):  
Frequency Regulation ◽  
Synchronous Generators ◽  
Comprehensive Comparison ◽  
Virtual Inertia

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.

scholarly journals Research on Real-time Intelligent Load Control Technology among Giant Hydropower Station Group under High-intensity Peak-load and Frequency Regulation Demand

2018 ◽  
Vol 246 ◽  
pp. 01107
Author(s):  
Wei Luo ◽  
Qingxiang Zhong ◽  
Faying Gu
Keyword(s):  
Real Time ◽  
High Intensity ◽  
Power Grid ◽  
Peak Load ◽  
Load Control ◽  
Water Volume ◽  
Frequency Regulation ◽  
Control Technology ◽  
Cascade Hydropower Stations ◽  
Hydropower Stations

The paper conducts an in-depth study on the real-time dispatching involved in joint operation among giant cascade hydropower stations with high-intensity peak-load and frequency regulation demand, and proposes anintelligent load control technology for cascade hydropower stations in the coordination mode of station and power grid. Aiming to water level safety control of runoff power stations and rapid response to load regulation requirements of the power grid, taking 10 types of constraints such as output, water volume and flow rate into consideration, a model cluster is established through the layered control principle to realize real-time intelligent load allocation and economic operation among Pubugou, Shenxigou and Zhentouba stations. Dadu River has become the first large-scale river basin in China to realize “one-key dispatch” of multiple stations, and has achieved good demonstration effect.

A Novel Approach of Battery Energy Storage for Improving Value of Wind Power in Deregulated Markets

2013 ◽  
Vol 14 (3) ◽  
pp. 255-264 ◽  
Author(s):  
Y Minh Nguyen ◽  
Yong Tae Yoon
Keyword(s):  
Energy Storage ◽  
Real Time ◽  
Wind Power ◽  
Frequency Control ◽  
Minimum Cost ◽  
Wind Generation ◽  
Frequency Regulation ◽  
Battery Energy Storage ◽  
Novel Approach ◽  
Battery Energy

Abstract Wind power producers face many regulation costs in deregulated environment, which remarkably lowers the value of wind power in comparison with the conventional sources. One of these costs is associated with the real-time variation of power output and being paid in frequency control market according to the variation band. In this regard, this paper presents a new approach to the scheduling and operation of battery energy storage installed in wind generation system. This approach depends on the statistic data of wind generation and the prediction of frequency control market prices to determine the optimal charging and discharging of batteries in real-time, which ultimately gives the minimum cost of frequency regulation for wind power producers. The optimization problem is formulated as the trade-off between the decrease in regulation payment and the increase in the cost of using battery energy storage. The approach is illustrated in the case study and the results of simulation show its effectiveness.

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