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An Interactive Operating Demand Response Approach for Hybrid Power Systems Integrating Renewable Energy Sources

Protection and control of Modern Power Systems 2024年第3期9卷 174-194页

作者： Abhishek Saxena Ravi Shankar IEEE the Department of Electrical Engineering National Institute of Technology PatnaIndia

The increased deployment of renewable energy in existing power networks has jeopardized rotational inertia,resulting in system degradation and *** address the issue,this paper proposes a demand response strategy for ensuring the future reliability of the electrical power *** addition,a modified fuzzy logic control topology-based two-degree-of-freedom(fractional order proportional integral)-tilt derivative controller is designed to regulate the frequency within a demand response framework of a hybrid two-area deregulated power *** test system includes thermal power plants,renewable energy sources(such as wind,parabolic trough solar thermal plant,biogas),and electric vehicle *** adaptively tune the controller’s coefficients,a quasi-opposition-based harris hawks optimization(QOHHO)algorithm is *** effectiveness of this algorithm is compared to other optimization algorithms,and the stability of the system is *** results demonstrate that the designed control algorithm significantly enhances system frequency stability in various scenarios,including uncertainties,physical constraints,and high penetration of renewables,compared to existing ***,an experimental assessment through OPAL-RT is conducted to verify the practicality of the proposed strategy,considering source and load intermittencies.

关键词： area control error demand response energy storage vertically integrated utility

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Integral Performance Criteria Based Analysis of Load Frequency control in Bilateral Based Market

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Circuits and Systems 2016年第6期7卷 1021-1032页

作者： P. Anitha P. Subburaj Department of Electrical Engineering UVOCCE Thoothukudi India Department of Electrical Engineering NEC Kovilpatti India

Performance index based analysis is made to examine and highlight the effective application of Particle Swarm Optimization (PSO) to optimize the Proportional Integral gains for Load Frequency control (LFC) in a restructured power system that operates under Bilateral based policy scheme. Various Integral Performance Criteria measures are taken as fitness function in PSO and are compared using overshoot, settling time and frequency and tie-line power deviation following a step load perturbation (SLP). The motivation for using different fitness technique in PSO is to show the behavior of the controller for a wide range of system parameters and load changes. error based analysis with parametric uncertainties and load changes are tested on a two-area restructured power system. The results of the proposed PSO based controller show the better performance compared to the classical Ziegler-Nichols (Z-N) tuned PI and Fuzzy Rule based PI controller.

关键词： Load Frequency control Particle Swarm Optimization Bilateral Market area control error Fuzzy Rule Based PI controller Parametric Uncertainties

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Load Frequency control of Interconnected Microgrid Enhanced by Deep Reinforcement Learning SAC-PID

Load Frequency Control of Interconnected Microgrid Enhanced ...

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第43届中国控制会议

作者： Zheng Liu Lijun Zhu Bolin Li Xuhui Wang School of Artificial Intelligence and Automation Huazhong University of Science and Technology

In recent years, the incorporation of sustainable energy resources such as wind power has had a significant impact on the stability of microgrids. In this context, our research introduces a proficient method for load frequency regulation utilizing deep reinforcement learning(DRL). Firstly, a two-area interconnected microgrid frequency control model is constructed, including wind power generation, reheat steam turbines, generators and loads. Secondly, the proposed method uses a soft actor critic(SAC)with a double Q-network to tailor the parameters of the proportional integral derivative(PID) controller, to train a DRL agent to obtain optimal controller parameters for this two-area interconnection, and we used the area control error(ACE) as the controller's input to reduce fluctuations in both grid frequency and interconnection line power flows. Furthermore, we designed a reward function via the square of the ACE to obtain the best-suited parameters for the controller. Finally, the trained controllers are tested under step load disturbance and random load disturbance, verifying that the designed SAC-PID controller provides improved frequency control performance for microgrids compared with the classical PID controller and the PID controller optimized through the particle swarm optimization(PSO) algorithm.

关键词： Microgrid Load Frequency control Deep Reinforcement Learning PID controller Soft Actor-Critic Algorithm area control error

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