scholarly journals Deep Forest Reinforcement Learning for Preventive Strategy Considering Automatic Generation Control in Large-Scale Interconnected Power Systems

2018 ◽  
Vol 8 (11) ◽  
pp. 2185 ◽  
Author(s):  
Linfei Yin ◽  
Lulin Zhao ◽  
Tao Yu ◽  
Xiaoshun Zhang
Keyword(s):  
Reinforcement Learning ◽  
Power Systems ◽  
Power System ◽  
Large Scale ◽  
Automatic Generation ◽  
Preventive Strategy ◽  
Emergency Situations ◽  
Interconnected Power Systems ◽  
Deep Forest ◽  
Normal States

To reduce occurrences of emergency situations in large-scale interconnected power systems with large continuous disturbances, a preventive strategy for the automatic generation control (AGC) of power systems is proposed. To mitigate the curse of dimensionality that arises in conventional reinforcement learning algorithms, deep forest is applied to reinforcement learning. Therefore, deep forest reinforcement learning (DFRL) as a preventive strategy for AGC is proposed in this paper. The DFRL method consists of deep forest and multiple subsidiary reinforcement learning. The deep forest component of the DFRL is applied to predict the next systemic state of a power system, including emergency states and normal states. The multiple subsidiary reinforcement learning component, which includes reinforcement learning for emergency states and reinforcement learning for normal states, is applied to learn the features of the power system. The performance of the DFRL algorithm was compared to that of 10 other conventional AGC algorithms on a two-area load frequency control power system, a three-area power system, and the China Southern Power Grid. The DFRL method achieved the highest control performance. With this new method, both the occurrences of emergency situations and the curse of dimensionality can be simultaneously reduced.

Applications of Reinforcement Learning and Bayesian Networks Algorithms to the Load-Frequency Control Problem

2014 ◽  
pp. 677-710
Author(s):  
Fatemeh Daneshfar
Keyword(s):  
Reinforcement Learning ◽  
Power Systems ◽  
Power System ◽  
Bayesian Networks ◽  
Model Building ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Load Frequency ◽  
Interconnected Power Systems ◽  
Power System Engineering

Load-Frequency Control (LFC) is an essential auxiliary service to keep the electrical system reliability at a suitable level. In addition to the regulating area frequency, the LFC system should control the net interchange power with neighboring areas at scheduled values. Therefore, a desirable LFC performance is achieved by effective adjusting of generation to minimize frequency deviation and regulate tie-line power flows. Nowadays such an LFC design is becoming much more complicated and significant due to the complexity of interconnected power systems. However, most of the LFC designs are based on conventional Proportional-Integral (PI) controllers that are tuned online by trial-and-error approaches. These conventional LFC designs are usually suitable for working at specific operating points and are not more efficient for modern and distributed power systems. These problems apply to design of intelligent LFC schemes that are more adaptive and flexible than conventional ones. The present chapter addresses the frequency regulation using Reinforcement Learning (RL) and Bayesian Networks (BNs) approaches for interconnected power systems. RL and BNs are computational learning based solutions which can adapt with environment conditions. They are a kind of Machine Learning (ML) techniques which have many applications in power system engineering. The main advantages of these intelligent-based solutions for the LFC design can be simplicity and intuitive model building that is closely based on the physical power system topology, easy incorporation of uncertainty, and dependent to the frequency response model and also to the power system parameter values.

scholarly journals Wind power integration into the automatic generation control of power systems with large-scale wind power

2014 ◽  
Vol 2014 (10) ◽  
pp. 538-545 ◽  
Author(s):  
Abdul Basit ◽  
Anca Daniela Hansen ◽  
Mufit Altin ◽  
Poul Sørensen ◽  
Mette Gamst
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Large Scale ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Wind Power Integration ◽  
Generation Control

scholarly journals A Novel Methodology for Adaptive Coordination of Multiple Controllers in Electrical Grids

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1474
Author(s):  
Ruben Tapia-Olvera ◽  
Francisco Beltran-Carbajal ◽  
Antonio Valderrabano-Gonzalez ◽  
Omar Aguilar-Mejia
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electric Power ◽  
Large Scale ◽  
Short Circuit ◽  
Dynamic Performance ◽  
Low Frequency ◽  
Electric Power System ◽  
Design Stage ◽  
Positive Interaction

This proposal is aimed to overcome the problem that arises when diverse regulation devices and controlling strategies are involved in electric power systems regulation design. When new devices are included in electric power system after the topology and regulation goals were defined, a new design stage is generally needed to obtain the desired outputs. Moreover, if the initial design is based on a linearized model around an equilibrium point, the new conditions might degrade the whole performance of the system. Our proposal demonstrates that the power system performance can be guaranteed with one design stage when an adequate adaptive scheme is updating some critic controllers’ gains. For large-scale power systems, this feature is illustrated with the use of time domain simulations, showing the dynamic behavior of the significant variables. The transient response is enhanced in terms of maximum overshoot and settling time. This is demonstrated using the deviation between the behavior of some important variables with StatCom, but without or with PSS. A B-Spline neural networks algorithm is used to define the best controllers’ gains to efficiently attenuate low frequency oscillations when a short circuit event is presented. This strategy avoids the parameters and power system model dependency; only a dataset of typical variable measurements is required to achieve the expected behavior. The inclusion of PSS and StatCom with positive interaction, enhances the dynamic performance of the system while illustrating the ability of the strategy in adding different controllers in only one design stage.

scholarly journals The Flexible Operation of Coal Power and Its Renewable Integration Potential in China

2019 ◽  
Vol 11 (16) ◽  
pp. 4424 ◽  
Author(s):  
Chunning Na ◽  
Huan Pan ◽  
Yuhong Zhu ◽  
Jiahai Yuan ◽  
Lixia Ding ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Power System ◽  
Large Scale ◽  
Renewable Integration ◽  
Flexible Resources ◽  
Feasible Option ◽  
Coal Power ◽  
Simulation Results ◽  
Flexible Operation

At present time, China’s power systems face significant challenges in integrating large-scale renewable energy and reducing the curtailed renewable energy. In order to avoid the curtailment of renewable energy, the power systems need significant flexibility requirements in China. In regions where coal is still heavily relied upon for generating electricity, the flexible operations of coal power units will be the most feasible option to face these challenges. The study first focused on the reasons why the flexible operation of existing coal power units would potentially promote the integration of renewable energy in China and then reviewed the impacts on the performance levels of the units. A simple flexibility operation model was constructed to estimate the integration potential with the existing coal power units under several different scenarios. This study’s simulation results revealed that the existing retrofitted coal power units could provide flexibility in the promotion of the integration of renewable energy in a certain extent. However, the integration potential increment of 20% of the rated power for the coal power units was found to be lower than that of 30% of the rated power. Therefore, by considering the performance impacts of the coal power units with low performances in load operations, it was considered to not be economical for those units to operate at lower than 30% of the rated power. It was believed that once the capacity share of the renewable energy had achieved a continuously growing trend, the existing coal power units would fail to meet the flexibility requirements. Therefore, it was recommended in this study that other flexible resources should be deployed in the power systems for the purpose of reducing the curtailment of renewable energy. Furthermore, based on this study’s obtained evidence, in order to realize a power system with high proportions of renewable energy, China should strive to establish a power system with adequate flexible resources in the future.

Decentralized H ∞ control for damping power system oscillations

2012 ◽  
Vol 2 (1) ◽  
Author(s):  
Guo-Jie Li ◽  
Tek Lie
Keyword(s):  
Power Systems ◽  
Power System ◽  
Large Scale ◽  
Digital Simulation ◽  
Design Procedure ◽  
Disturbance Attenuation ◽  
System Stability ◽  
Frequency Noise ◽  
Stability Robustness ◽  
Norm Bound

AbstractInter-area oscillations are serious problems to large-scale power systems. A decentralized H ∞ generator excitation controller of a power system is proposed to damp the inter-area oscillations and to enhance power system stability. The design procedure for a linear composite system is presented in terms of positive semi-definite solutions to modified algebraic inequalities. The resulting controller guarantees closed-loop stability, robustness and an H ∞-norm bound on disturbance attenuation even under uncertainties such as high frequency noise. The control is decentralized in the sense that the control of each generator depends on local information only. The effectiveness of the H ∞ controller is demonstrated through digital simulation studies on a two-machine power system.

scholarly journals Evaluating the Potential Contribution of District Heating to the Flexibility of the Future Italian Power System

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 584
Author(s):  
Chiara Magni ◽  
Sylvain Quoilin ◽  
Alessia Arteconi
Keyword(s):  
Power Systems ◽  
Power System ◽  
Large Scale ◽  
District Heating ◽  
Energy System ◽  
Heat Pumps ◽  
Electricity Sector ◽  
Potential Contribution ◽  
The Future ◽  
Promising Solution

Flexibility is crucial to enable the penetration of high shares of renewables in the power system while ensuring the security and affordability of the electricity dispatch. In this regard, heat–electricity sector coupling technologies are considered a promising solution for the integration of flexible devices such as thermal storage units and heat pumps. The deployment of these devices would also enable the decarbonization of the heating sector, responsible for around half of the energy consumption in the EU, of which 75% is currently supplied by fossil fuels. This paper investigates in which measure the diffusion of district heating (DH) coupled with thermal energy storage (TES) units can contribute to the overall system flexibility and to the provision of operating reserves for energy systems with high renewable penetration. The deployment of two different DH supply technologies, namely combined heat and power units (CHP) and large-scale heat pumps (P2HT), is modeled and compared in terms of performance. The case study analyzed is the future Italian energy system, which is simulated through the unit commitment and optimal dispatch model Dispa-SET. Results show that DH coupled with heat pumps and CHP units could enable both costs and emissions related to the heat–electricity sector to be reduced by up to 50%. DH systems also proved to be a promising solution to grant the flexibility and resilience of power systems with high shares of renewables by significantly reducing the curtailment of renewables and cost-optimally providing up to 15% of the total upward reserve requirements.

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