Implementing Load‐Side Operating Energy Reserves to Improve System Frequency Control Amid the Expansion of Distributed Generation

Due to the increasing penetration of wind power, operating characteristic of wind turbines may cause great concerns to frequency stability of the power system with large-scale wind power integration. Wind power plant participation in frequency regulation and the coordination with stored energy of the power system will be a trend in the future. However, the traditional wind turbines may not have the capability of frequency regulation. The issue of how wind power plants can participate in frequency regulation becomes research hotspot in recent years. Currently, most of frequency control methods of wind turbines are designed to have a new control loop from the existing control modules, such as speed control, droop control and pitch angle control. Theses novel control methods could realize the frequency support in some cases. However, these single-functional control loops have some drawbacks and could not solve the issues of frequency control effectively. For instance, the speed control could only work under the rated wind speed and the pitch control may not have fast-speed response ability to support the frequency control when the system frequency starts to fall. In this paper, a comprehensive review is presented regarding the latest studies about the multi-controller method of variable speed wind turbines in order to solve the problems of primary and secondary frequency control.

The frequency control of an islanded microgrid is consisted of primary frequency control (PFC) and secondary frequency control (SFC). This paper proposes a novel cooperative application of Battery Energy Storage System (BESS), Photovoltaic (PV) systems and LED lighting loads (LEDLLs) to quickly intercept frequency deviation in the stage of PFC. The slow responding distributed generators handle SFC by restoring the frequency to its nominal value. For participation in PFC, in the case of power shortage, LEDLLs decrease their power consumption, and in the case of power surplus, the PVs decrease their power generation. While PVs and LEDLLs are participating in PFC with their maximum capability, the BESS frequency controller is tuned to inject/absorb enough power in both cases to keep the frequency within safe limits. In this paper for battery sizing, instead of using its nominal power, a modified overloading capability to fast discharge/charge is used to reduce the required battery size for PFC that also prevents damaging it during fast discharge/charge for PFC. The proposed approach is evaluated on the CIGRE low voltage microgrid using MATLAB/Simulink software. Simulation results show that besides the overloading characteristics, the cooperative utilization of BESS, PVs and LEDLLs also reduce the battery size.

This paper proposes a simulation model of Virtual Power Plants (VPP) and analysis the impact of the proposed model in frequency control. This paper, also, analyses the impact of reduced inertia on the hydro power plants stability. The simulations were done considering an increased share of renewable energy sources (RES) in electrical power production and a reduction of system inertia. The simulations were performed in Matlab/Simulink on the Kundur two-area frequency model which contains both primary and secondary frequency control levels. The simulation time was considered equal to 900 seconds, equivalent to 15 minutes, this being a reference value for secondary frequency control. The virtual power plant is composed of hydro power plants, renewable sources and energy storage systems and is controlled by a hybrid controller meaning that the VPP can contribute to both primary and secondary frequency control.

Microgrids rely on both primary and secondary frequency control techniques to maintain system stability. Secondary frequency control effectively minimizes frequency fluctuations by adjusting the active power reference in each power inverter, but requires complex and costly interequipment communication. In this paper, we propose a distributed secondary frequency control strategy for microgrids containing multiple virtual synchronous generator (VSG) units based on a new maximum power loading factor (MPLF) concept. The MPLF algorithm facilitates power sharing by dynamically identifying the maximum VSG loading factor at each time instance, and then using this value as a unified reference signal for all the VSGs in the microgrid. The active power reference for each VSG will be adjusted based on the unified reference signal, subsequently the secondary frequency control can be realized. The proposed strategy does not require high-bandwidth communication since the MPLF data are transmitted among the VSGs using low-bandwidth communication. We also develop small-signal models for the control architecture to analyze the influence of major proportional–integral control parameters and communication latency. The MPLF control strategy is implemented using custom digital signal processor controllers, and experimentally validated using hardware in loop simulations. Finally, the new control paradigm demonstrates significant tolerance for communication delay or failure, which we purposely introduced in our investigation.

Energy storage systems (ESSs) have been applied in power systems for a long time. It participates in the grid frequency control at two levels, the primary frequency control and the secondary frequency control. In this paper, a control strategy that integrates one synchronous generator (SG) and ESS as one single generation unit named flexible generator (FG) is proposed, allowing ESS to participate in primary frequency control. The main trick is that the proposed control strategy not only adopts SG's frequency as the ESS control input but also feeds back FG's total output power to control the ESS. FGs have more substantial damping and stability than SGs. The proposed control strategy has a superior performance compared to traditional PID control and fuzzy control strategies of ESSs. The flexible control parameters are determined by the linear quadratic regulator (LQR) with disturbance suppression. The ESS's capacity is discussed and determined. Simulation results of the New England 39-bus system verify the advantages of FGs both in load changes and faults. The HIL experiment results also illustrate the applicability and effectiveness of the flexible control.

The existing passive methods for islanding detection are mainly based on the detection of voltage and frequency deviation after islanding, using protections such as voltage vector shift (VVS) and rate of change of frequency (ROCOF). Although there are reported issues with these passive methods such as inherent non-detection zones and nuisance trips, utilities prefer the passive methods due to the low cost and simplicity of deployment. In this paper, one composite passive islanding detection method is presented. It tracks the voltage phase angle, the system frequency, and ROCOF every power cycle. If three phase voltage vectors shift in the same direction and the rotated angle values are balanced, the calculation of the accumulated phase angle drift (PAD) will be initiated. This calculation continues until the ROCOF measurement is below the ROCOF setting threshold. If the accumulated phase angle drift reaches the set angle threshold, the condition for islanding is claimed. The performance of this composite method is verified under different scenarios based on Matlab Simscape multidomain physical systems and practical waveforms recorded from sites. Although there are still non-detection zones, this composite PAD solution has better sensitivity than existing VVS and ROCOF methods and is stable under external system faults.

The extensive development of renewable energies in power systems causes several problems due to intermittent output power generation. To tackle the challenge, demand response contribution to ancillary service is currently well recognized under the smart grid infrastructure. The application of the heat pump water heater (HPWH) as a controllable load in primary frequency control is well presented in the literature; however, the motivation of this paper is to use HPWHs for secondary frequency control. To this end, a model predictive control (MPC) method for a two-area power system incorporating HPWHs to contribute to secondary frequency control is proposed in this paper. A detailed model of HPWH is employed as a controllable load to control the power consumption during water heating. The MPC method predicts the future control signals using a quadratic programming-based optimization. It uses the system model, past inputs and outputs, as well as system control signals to predict the next signals. The effective performance of the proposed method for the two-area power system with HPWH is demonstrated for different scenarios of load changes, intermittent renewable power generation and parameter variations as the sensitivity analysis.

In an autonomous micro grid or a power system with high renewable power penetration, the intermittency of renewable energy resources becomes major concern of system operation. Dynamic process of frequency response and control due to unit failures and resource variation may have significant impacts on system operational reliability because the outputs of committed conventional generators have to be frequently adjusted for frequency recovery. This paper proposes a technique to investigate system operational reliability from the aspect of frequency variation and control. The time durations of primary and secondary frequency controls are considered in the proposed technique. Frequency related reliability indices are defined. The IEEE-RTS is used to illustrate the applications of the proposed method.

Real-time validation of RoCoF – Enhancing advanced coordinated control strategy for voltage unbalance mitigation implementing demand side management

Fast and accurate estimation of active power imbalance during frequency contingency events is crucial for effective power system monitoring and frequency control. Conventional power imbalance estimation methods are typically based on the swing equation, where both system inertia and the Rate of Change of Frequency (RoCoF) are required for the calculation. However, accurate real-time system inertia level is often unavailable, and measuring RoCoF reliably remains challenging. As a result, the conventional methods are not effective, particularly with the increasing penetration of renewables, where system uncertainties have increased with power quality degraded. This paper explores the feasibility of applying a data-driven approach to address the aforementioned challenges, where the Extreme Gradient Boosting (XGBoost) algorithm is used to train a model that only requires frequency and system operating conditions as inputs for accurate estimation of power imbalance. Through appropriate training, the proposed method does not require the accurate system inertia data and avoids the need for RoCoF measurement. Case studies are presented, which demonstrate that the proposed approach can achieve a highly satisfactory accuracy, providing an effective solution for estimating the power imbalance size during contingency events.

This paper presents the implementation of the Grid-Forming (GFM) control technique in renewable energy source inverters to synchronize with the grid and provide frequency support. Specifically, the GFM Droop Control technique, based on the Power–Frequency relationship, is employed. The proposed model was developed and validated in the Matlab-Simulink environment. By using electromagnetic transient (EMT) simulations, we were able to precisely monitor and analyze voltage and current waveforms, thereby confirming the approach’s effectiveness in enhancing grid stability and power quality. The implementation of the GFM control technique in islanded mode demonstrated high system frequency stability. In response to sudden load changes up to 5 MW (equivalent to over 30% of the total load), a maximum frequency deviation of 0.04 Hz and a maximum Rate of Change of Frequency (RoCoF) of 4 Hz/s were observed. The system ensured the frequency’s return to its nominal value of 60 Hz, thanks to the virtual inertia and frequency regulation provided by the GFM. The total harmonic distortion (THD) of current and voltage in steady-state operation consistently remained below 1%, thus complying with IEEE 1547 standards. In tests with the GFM interconnected to the grid, the droop+LPF control provided dynamic support to the external system, effectively mitigating both frequency deviations and RoCoF. The GFM contributes to the grid’s frequency stability by providing virtual inertia. The power quality at the point of common coupling (PCC) was excellent, as the voltage distortion was maintained below 0.5%, confirming that the injection of harmonic currents does not violate established limits.

In this paper, we propose a multiagent based distributed algorithm for enhanced frequency response in large-scale multiarea power systems. Control nodes associated with these areas preemptively agree on their relative contributions in supporting the frequency response in a completely distributed manner. Consequently, in case of system contingencies, each area knows the total change in generation required to facilitate faster frequency restoration during primary frequency control. Within an area, local controllers associated with generators execute a distributed power agreement via sparse information exchange to achieve this required change in generation. As a result of these coordinated control actions, frequency deviation from the nominal remains minimal, thereby reducing the dependency on secondary frequency control. Inspired from graph theoretic techniques in networked controls, the proposed architecture requires nodes with minimalistic computation and communication capabilities, thereby increasing its applicability. Simulations performed on a large test case demonstrate the efficacy of the proposed algorithm in improving the transient performance of the frequency response.

Due to the shortage and environmental pollution of fossil fuel sources, conventional generating units are substituted with renewable energy sources. Thus, the total inertia decreases while the rate of change of frequency (ROCOF) increases, affecting the system frequency and stability. In this paper, a supplementary control, washout filter, is added to the primary frequency control of a doubly-fed induction generator (DFIG)-based wind turbine for better frequency regulation. In order to achieve the best performance (lowest frequency deviation with keeping the system stable), a new optimization technique called Mayfly Algorithm (MA) is used to find the optimum values of the washout filter’s parameters. Compared with the traditional method, a great improvement has been presented in the system frequency response under different load perturbations. Also, the results show that the washout filter’s parameters have an adverse impact on the frequency response and system stability if they aren’t determined accurately. MATLAB/SIMULINK program is used to test the performance of the improved method under different scenarios.

Droop control, inertia control, and PD control are three typical frequency response (FR) strategies of grid-tied inverters interfaced renewable energy sources (RES) to restrain the power system frequency indicators, i.e., frequency deviation ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta \omega $ </tex-math></inline-formula> ) and the rate of change of frequency (RoCoF). Due to the highly limited inverter capacity, the FR performance in power systems with high RES penetration should be optimized. To this end, this paper first analyzes the impact of high-penetration renewable energy injection on power system frequency stability, and derives the system frequency expressions in the absence of an FR scheme, and in the presence of droop/inertia/PD controls that are representative for various virtual synchronous generator-based FR schemes. Under the same constraint of available FR capacity, control parameter ranges of these FR schemes are obtained, and their optimal conditions for restraining the maxima of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta \omega $ </tex-math></inline-formula> and RoCoF are identified and compared analytically. Comparison conclusions are finally proved by the provided experiment and simulation results.

Low inertia, nonlinearity and a high level of uncertainty (varying topologies and operating conditions) pose challenges to microgrid (MG) systemwide operation. This paper proposes an online adaptive Koopman operator optimal control (AKOOC) method for MG secondary voltage and frequency control. Unlike typical data-driven methods that are data-hungry and lack guaranteed stability, the proposed AKOOC requires no warm-up training yet with guaranteed bounded-input-bounded-output (BIBO) stability and even asymptotical stability under some mild conditions. The proposed AKOOC is developed based on an ensemble Koopman state space modeling with full basis functions that combines both linear and nonlinear bases without the need of event detection or switching. An iterative learning method is also developed to exploit model parameters, ensuring the effectiveness and the adaptiveness of the designed control. Simulation studies in the 4-bus (with detailed inner-loop control) MG system and the 34-bus MG system showed improved modeling accuracy and control, verifying the effectiveness of the proposed method subject to various changes of operating conditions even with time delay, measurement noise, and missing measurements.