Transient stability emergency control combining open-loop and closed-loop techniques

The prevalence of Line‐Commutated Converter (LCC) HVDC makes the coupling and interaction phenomenon between AC system and DC system of particular complicated. There are significant challenges to determine control strategy using state‐of‐the‐art approaches especially when discrete events (e.g. switching and state resetting) happen frequently due to successive commutation failures (CFs). An enhanced transient stability emergency control (TSEC) for AC/DC grids based on the optimal control is presented to maintain the transient stability and mitigate the successive CFs caused by AC faults. In the proposed TSEC method, an extinction advance angle constraint is added to the TSEC model to mitigate the successive CFs. The emergency power control of LCC‐HVDC is employed as an additional control measure to reduce generator‐tripping and load‐shedding amount. The direct sequential approach is adopted to obtain the optimal solution of TSEC to improve the calculation efficiency. In the direct sequential approach, the modified adjoint sensitivity analysis (MASA) with the consideration of adjoint jump conditions is utilized to increase the gradient calculation accuracy. The effectiveness of the control strategies and the accuracy of the sensitivity calculation are verified on two test systems.

This paper proposes a safe reinforcement learning (RL)-based transient stability emergency control (TSEC) method for islanded microgrids. RL requires extensive interaction with the environment to learn control strategies, hence, a data-driven approach is used as a substitute for time-consuming time-domain simulation calculations. Deep sigma point processes (DSPP), which is a Gaussian process model, is utilized to predict the normal distribution of transient stability of microgrids and to construct a transient stability chance constraint. Reward-constrained policy optimization (RCPO) can simultaneously achieve objective prediction, policy learning, and constraint cost coefficient update across multiple timescales. RCPO interacts with the DSPP-based microgrid environment through a multi-process parallel manner, greatly increasing the training speed. Case studies on a real islanded microgrid demonstrate that the proposed method can efficiently and quickly obtain the optimal emergency control strategy while adhering to all hard constraints.

Online transient stability assessment and preventive control are important measures to prevent power system blackouts. Based on the deep cross network (DCN), an online assessment and preventive control method for power system transient stability is proposed. The deep cross network is developed to estimate the critical clearing time (CCT) of the credible fault contingencies. Based on the deep cross network model, the sensitivity of the active power of the generator set to the fault critical clearing time is calculated and then the DCN model-embedded transient stability constrained optimal power flow (TSCOPF) model is proposed to compute the preventive generation re-dispatch strategy. This TSCOPF model is computed by successive linear programming assisted by the DCN. The simulation results of the IEEE 39-bus test system show that this method can give early warning to the operation mode with instability risk and generate preventive control strategies, which can effectively improve the safety level of power grid operation.

Pile oscillator techniques are powerful methods to measure small reactivity worth of isotopes of interest for nuclear data improvement. This kind of experiment has long been implemented in the Minerve experimental reactor, operated by CEA Cadarache, Saint-Paul-les-Durance, France. A hybrid technique mixing reactivity worth and flux variations surrounding the oscillator is presented here. It was made possible after developing high-sensitivity miniature fission chambers introduced next to the irradiation channel. A test campaign, called MAESTRO-SL, took place in 2015. Its objective was to assess the feasibility of the hybrid method and investigate the separation of mixed neutron effects, such as fission and capture or scattering and capture. The experimental results are presented and discussed in this paper, which focus on comparing two measurement setups, one using a power control system (closed-loop technique) and another one in which reactor power is free to drift (open-loop technique). First, it is demonstrated that the open loop is equivalent to the closed loop, and both techniques bring similar results. It is shown that measuring the flux change around oscillated samples provides valuable information on partial neutron cross sections. Second, uncertainty management and methods’ reproducibility are discussed. As expected, both techniques can achieve similar performances. In this paper, uncertainty as low as 0.007 pcm for samples’ reactivity worth and $1.2 \times 10^{-4}$ for local flux change were achieved.

Automatic Learning Approaches for On-Line Transient Stability Preventive Control of the Hydro-Quebec System: Part I. Decision tree approaches

This paper presents the theoretical background and analytical methods developed for BC Hydro's on-line transient stability assessment (TSA) module. It concentrates on the preprocessing modeling, stability analysis/margin calculation and post processing techniques, the architecture, hardware and implementation are presented in a companion paper. BC Hydro's TSA has been tested with thousands of cases using a large scale detailed basecase derived for on-line analysis, sample tests are presented in this paper.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Areas discussed are power system modeling, state estimation, structure decomposition, state forecasting, clustering and security measure development. A detailed dynamic model of a multi-machine power system has been developed. A process state estimator was developed to estimate the long-term dynamic behavior of the power system. The algorithm is identical to the extended Kalman filter but has a modified process noise driving term. A two-stage structure estimation technique was proposed for identifying the power system network configuration. Two approaches to structure decomposition were investigated. A time-scale decomposition of the system equations, based on a singular perturbation approach, was evaluated using a detailed model of a generating system. Spatial decomposition was examined by applying an optimal network decomposition technique to a 39-bus test system. Stochastic approximation based approaches to estimator simplification were examined. Explicit expressions were obtained for the evolution of the first and second moments of the system state. Research into security measures proceeded in three directions. The first area involves viewing the security assessment problem as a hyperplane crossing problem for a stochastic process. The second approach examined the stability of an unforced linear system where the system coefficients are subject to future jumps. The third area of research has led to the formulation of a security measure suitable for on-line assessment of transient stability.

peer reviewed

With the development of science and technology, the cost of offshore wind power development and transmission has gradually decreased, making offshore wind power technology a research hotspot. The installed capacity has been increasing year by year. China has abundant offshore wind energy resources, which are much richer than those on land and are available for exploitation. Offshore wind speeds are stable and do not produce harmful substances. Therefore, studying the transient voltage stability of offshore wind power grid-connected systems to improve the utilization efficiency of offshore wind power and protect the ecological environment is critical. After large-scale wind power is connected to the grid, ensuring the stability of the system's transient voltage becomes crucial. This paper aims to deeply study the transient voltage stability of offshore wind farm grid-connected systems, providing theoretical support for the subsequent design and operation of offshore wind farms. A simulation model of a typical power system integrated with offshore wind farms was established using PSAT. Relevant transient voltage stability indices were calculated, and the impact of varying wind speeds on the transient voltage stability of the grid-connected system was investigated. Static Var Compensators (SVC) and Static Synchronous Compensators (STATCOM) were installed for comparative analysis. The results demonstrate that excessively low wind speeds degrade the system's transient stability, and the installation of SVC provides superior improvement in transient voltage stability compared to STATCOM.

This chapter, on practical nonlinear control design, includes a variety of open-loop and closed-loop control design techniques that not only do not avoid the nonlinearities of the model but sometimes utilize the nonlinearities as part of a successful control strategy. The chapter includes many MATLAB Simulink examples. One of the chapter purposes is to serve as a MATLAB Simulink tutorial. Nonlinearities in the process model are often the “heart and soul” of the process model. We tried to demonstrate it with many real-life examples—aircraft motion models, missile guidance, physiological models, and more. In all these examples, the nonlinearities play a central role. Dynamic simulations, if done carefully and systematically, can compensate for the lack of full control design experience and training. A simulator in the loop that performs multiple runs of a slow enough process can provide meaningful control insight that can be put into action in real time. Sliding mode control and Lyapunov Design are powerful control design techniques in their own right. These control design methods particularly shine in the presence of modeling uncertainties and poorly modeled disturbance signals. One may even apply these methods to linear process in order to obtain superior performance at certain circumstances. Due to time and space constraints, several subjects regrettably ended up being omitted from this chapter (awaiting possibly future editions of this book). These subjects include Model Linearization by means of MATLAB and Simulink and PID Control Auto-Tuning.

Convolutional neural network-based power system transient stability assessment and instability mode prediction

This paper presents a new candidate method for on-line transient security assessment and enhancement based on Pattern Recognition techniques. Transient state variables are used as primary features and the classifier is obtained in two phases, through the combination of an optimum discriminant transformation together with a probabilistic procedure. The proposed security functions can be further refined by means of a second level classifier based on an optimal discriminant plane and using a weighted K nearest neighbour rule. Finally it is shown that this method provides also an efficient and simple tool for on-line preventive control. Extensive results obtained for several contingencies in the CIGRE test system are presented and discussed.

In this paper, we introduce two novel closed-loop current control techniques for rotor alignment in a phase axis direction in PMSM drives. This alignment procedure is used both in sensor and sensorless PMSM drives to correctly implement vector control strategies. The two novel closed-loop current control techniques employ PI and sliding-mode controllers. The design formulae, based on the mathematical model of the motor, are derived for all controller parameters. Using closed-loop schemes it is possible to develop the maximum torque during rotor alignment, and reduce alignment error. To avoid large alignment errors, due to static friction torque, when the initial rotor position is close to the chosen phase axis direction we propose a new procedure based on a double-alignment in two consecutive phase axis directions. Experimental results demonstrate that using closed-loop current control together with double-alignment procedure the alignment error is minimized and independent of the initial rotor position.

Utilizing the Laplace transform to derive the quadrupole model for both the direct and inverse problems, the temperature regulation of thin plate sides was examined.The polynomial expansions about poles and zeros are used to approximate the resultant hyperbolic functions.For multilayer plates, the open-loop and closed-loop control techniques were developed.The benefits and drawbacks of this method are demonstrated by simulation results for a two-layer plate.With this method, one may use the opposite side's temperature to regulate the temperature of one side of the plate in real time.

A semiactive magnetorheological fluid―elastomeric device has been assembled and evaluated in control experiments to demonstrate its utility to compensate for measured changes as a helicopter lag damper. The baseline used in this study was lag damper (snubber) for a hingeless helicopter rotor that employs both elastomers and fluids: that is, a fluid―elastomeric damper. This damper was disassembled and modified to include two internal magnetorheological control valves, and the existing hydraulic fluid was replaced with magnetorheological fluid. Hence, the resulting prototype damper is a retrofit design that can easily be installed in a test rotor in future evaluations. The magnetorheological fluid―elastomeric damper was subject to extensive performance characterization at displacement amplitudes ranging from 0.8 to 3.4 mm, temperatures ranging from 20 to 55°C, and control currents up to 2.0 A. Using this database and a hydromechanical model of the damper, control systems were designed to track a reference damping profile, which is a function of amplitude only, in the presence of measured amplitude and temperature variations at the rotor lag frequency (3.8 Hz). Both open-loop (interpolating lookup table) and closed-loop (proportional-integral and gain scheduling) techniques were employed in simulations and experiments. The results demonstrated that all of the control schemes were effective, although a minimum tracking error was achieved with the closed-loop systems. Comparing the two closed-loop systems, the gain-scheduling controller provided a faster response overall, but the improvement was marginal.