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Frequency control of isolated power systems with high penetration of wind power is a challenging task for system operators. The difficulty results from the limited frequency response capability of thermal power units to keep up with the fluctuations of wind power. This paper develops a field verification architecture to leverage aluminum smelting loads (ASLs) to participate in primary frequency control. A new method is proposed to coordinate ASLs with thermal power units to quickly stabilize the isolated power system with significant wind power fluctuations or curtailments. Moreover, a closed-loop control system for the ASLs controller is developed and tested on a real-world isolated power system in Inner Mongolia, China. Hardware-in-the-loop simulations, as well as field tests, are conducted under various scenarios of wind power fluctuations or curtailments to verify the proposed architecture for frequency control. The highly consistent simulation results and field tests demonstrate the good frequency control capability of the ASL. The regulated power from the ASL is demonstrated to be able to reach 6% of its rated power within 4 s. Working jointly with thermal power units, the ASL helps maintain the stable operation of the isolated power system, significantly improving the frequency response characteristic. [ABSTRACT FROM AUTHOR]

This paper proposes a systematic approach to coordinately design probabilistically-robust wide-area power system stabilizers (WPSSs) for suppressing inter-area oscillations of power systems incorporating wind power. Specifically, the operating point of the system varies stochastically due to wind power integration and each operating point corresponds to a wind power generation scenario in the steady state. Thus, the WPSSs tuned by solving a delicately formulated optimization problem can maximize the occurrence probability of scenarios where the inter-area modes possess the acceptable damping ratios, and strictly constrain their unfavorable impacts. Multiple contingencies are also directly considered. In addition, several advanced techniques are tactfully employed for accurate and efficient evaluation of occurrence probability (objective function) during the optimization so as to ensure the proposed tuning method can deal with the highly nonlinear relationships between the system eigenvalues and the steady-state power outputs of wind farms; a customized differential evolution algorithm is proposed as well to efficiently solve the formulated optimization problem. Simulations and comparisons conducted on two classic test systems with proper modifications show the effectiveness and efficiency of the proposed control design method. [ABSTRACT FROM PUBLISHER]

• A novel tri-level optimization model is proposed for distribution-level market clearing. • The Stackelberg game model between the distribution network operator and each charging station is formulated. • A method of integrating KKT conditions with the decentralized iterative approach is developed to solve the tri-level model. • The effectiveness and performance of the proposed method are verified in standard systems. With the increasing penetration of distributed renewable energy sources in distribution networks, a large number of independent market entities such as load serving entities will participate in the distribution-level market, which provides a platform for transparent energy transactions among them. This paper proposes a novel tri-level optimization model for distribution system operator market clearing, fully considering the strategic participation of electrical vehicles and the interactions with the transmission system operator in the market environment. The upper-level model addresses the bidding strategy problem of charging stations and the randomness of renewable energy sources, the middle-level model performs the distribution-level market clearing, and the lower-level model focuses on the joint optimization of power and reserve for transmission network. Furthermore, the Stackelberg game model between distribution system operator and each charging station is converted into a mathematical program with equilibrium constraints formulation, and a decentralized approach based on analytical target cascading algorithm is developed to realize the decoupling of distribution and transmission network. The simulation results show that the proposed distribution-level market clearing method can alleviate the congestion in transmission network and enhance the economic benefits of load serving entities in distribution network. [ABSTRACT FROM AUTHOR]

• New concept of controller load damping factor of power systems using voltage regulators. • Implementation method for a series-type controlled load damping factor controller. • Examination of controlled load damping controller implemented in RTDS. As sustainable natural sources such as wind and solar are increasingly integrated into power grids, conventional fossil fuel-based generating units will be gradually replaced, resulting in enormous pressure on frequency regulation of the novel power systems. This paper proposes a method for implementing a cascaded load-damping factor controller based on the controlled load-damping factor controller. Series-type voltage regulators, namely, solid-state transformers or dynamic voltage restorers, can regulate the voltage of the 10 kV feeder within the allowed range. Therefore real-time control of composite load power is realized, which significantly improves the primary frequency regulation capability of novel power systems with renewable energy generation(REG). The effect of actuator regulation time constant is considered, The impact of dynamic loads on the primary frequency regulation of the controller, designed based on a static load model, is analyzed, The effectiveness of the controller on the primary frequency regulation under different renewable energy penetration rates is discussed, The effectiveness of the controller in smoothing short-term power fluctuations of REG is examined. Finally, the effectiveness of the series-connected controlled load-damping factor controller in primary frequency regulation is verified on the RTDS simulation experimental platform. The proposed control system is characterized by a simple structure, easy implementation, and convenient maintenance, which can realize the coordination and unification of reactive-voltage and active-frequency control of the novel power system in the 110 kV customer substation and is beneficial to practical application in engineering. [ABSTRACT FROM AUTHOR]

Addressing renewable energy (RE) curtailment in power systems necessitates a comprehensive strategy leveraging peak regulation resources from both the power and load sides. On the power side, deep peak shaving of thermal power plants can mitigate surplus electricity during periods of high RE production. On the load side, energy-intensive industrial loads, characterized by large capacity and rapid adjustability, can respond effectively to energy deficits when RE is low. To enhance the peak regulation capacity for optimal RE accommodation, this paper proposes a collaborative optimization method combining electrolytic aluminum load (EAL) regulation with thermal power deep peak shaving (DPS). The study is initiated by developing a sophisticated peak regulation model for the electrolytic aluminum load (EAL), considering production characteristics, cost features, and safety constraints. Subsequently, a collaborative optimization model is formulated, integrating EAL regulation with thermal power deep peak shaving (DPS), aiming to minimize societal peak regulation costs (PRC). Applying this model to a practical regional grid in Yunnan Province reveals substantial reductions in RE curtailment rates, effective minimization of total social PRC, and enhanced operational economics of thermal power DPR under varying wind power scenarios. Notably, the proposed approach requires only minor adjustments to the EAL, ensuring production safety is maintained. This research provides valuable insights for the seamless integration of EAL into grid peak regulation services. • A refined peak regulation model of the electrolytic aluminum load (EAL) is established. • The segmented cost model of the EAL is constructed. • Collaborative optimization integrating EAL regulation and thermal power deep peak shaving. • The effectiveness of collaborative optimization under various RE scenarios is proved. • The influence of EAL regulation space on the social peak regulation effect is discussed. [ABSTRACT FROM AUTHOR]

• A novel algorithm is proposed to detect ramp events in databases with different resolutions. • The proposed algorithm is able to deal with bad data points which previous methods cannot handle. • The detecting efficiency and accuracy is greatly improved by the proposed algorithm. • The proposed algorithm can be employed to provide accurate information about system flexibility for ancillary services. The flexibility of the power system gets more attention of power system operators due to the high penetration of renewable energy sources. This leads to the need of the ramp detection. Based on the detection results of ramp events (REs) in historical and forecast databases, the assessment of flexibility requirements in the power system can be significantly improved. Thus the system operator is able to procure minimum ancillary services and design flexible ramping products. Furthermore, the accuracy of the ramp forecasting can be increased. In the mean time, the rapid development of measuring facilities in the power system, such as the WAMS and the SCADA system, requires a robust detecting method to detect ramp events in the databases with different data properties and resolutions of the power system. This paper proposes a Parameter and Resolution Adaptive Algorithm (PRAA) to identify REs fast and accurately. A fast search method that can process raw databases with tens of millions of data points in seconds is proposed to merge adjacent REs with the same ramp direction. The bad data processing method is directly integrated into the proposed algorithm. A post-processing method is developed to increase the accuracy and robustness of the proposed algorithm. The raw wind power data sets from Bonneville Power Authority (BPA) and a real-world power system in China are utilized to validate the performance of the proposed PRAA. [ABSTRACT FROM AUTHOR]

As the increasing penetration of renewable energy sources in distribution network, the tie-line power fluctuation caused by intermittent renewable energy produces a detrimental impact on security and reliability of the main grid. Therefore, maximization of renewable energy utilization as well as stabilization of tie-line power fluctuation are both required in the distribution network, to ease the power regulation burden of main grid. Remarkably, the development of integrated energy systems makes it possible to transfer the fluctuation in power network to other larger inertial systems. This paper proposes a coordinated operation strategy for the gas-electricity integrated distribution system, considering AC power flow in the power network and the gas hydraulic calculation in gas network. In addition, based on the nonlinear multi-energy coupling external characteristics modeling of CCHP system, the power fluctuation of renewable energy sources is transferred to gas distribution network and cooling or heating system by coordinated operation of Multi-CCHPs. Moreover, a two-stage optimization algorithm is proposed to solve the corresponding mixed integer nonlinear programming (MINLP) problem. The simulations conducted on 33-node power distribution network and 24-node gas network show that the proposed method can effectively smooth the tie-line power fluctuation in variety case. [ABSTRACT FROM AUTHOR]