Distributed Consensus‐Based Optimization of Multiple Load Aggregators for Secondary Frequency Control

Hierarchical control model of AGC is adopted by regional power grid of China, which is divided into two levels, namely, one regional dispatching center (RD) and several provincial dispatching centers (PD). The RD and each PD have their own control assessment objectives, however, the load, RD and PD AGC units are located in the different PD control areas. Hence the cross-regulation uncoordinated control of RD and PD AGC units is not only affects the control performance standard (CPS) of the PD but also directly impacts the adjustment cost of AGC units of them. Aiming at this problem, a dynamic coordination optimization model of regional and provincial AGC unit control for the interconnected power system (DCOMAGCUC) is proposed in this paper to improve the effect and adjustment performance of AGC strategy. In this control strategy, the minimum AGC ancillary service cost is considered as objective function, the power balances function of the tie line between different province power girds and the ultra-high voltage (UHV) line are considered as equality constraints, the CPS1 and CPS2 of each PD control area, the UHV line between the different regional power grids and other unit's constraints are considered as inequality constraints, and the adjustment instruction and the adjustment rate of all AGC units of RD and PD are considered as control variables, and the tie line power deviation as well as frequency deviation as dependent variables. The model of DCOMAGCUC is a complex nonlinear optimization problem with continuous and discrete variables. Then, an immunity evolutionary programming algorithm is adopted to solve the DCOMAGCUC. The experiment results and comparisons are obtained by DCOMAGCUC and the traditional PI control strategy, which indicated that the proposed DCOMAGCUC can enhance the effect and performance of AGC

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.

Secondary frequency control strategy for BESS considering their degree of participation

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.

This paper presents a neural network approach intended to aid electricity consumers or power system planner in the task of classification of harmonic load types using the measurements (data samples) collected from one of the power station in Malaysia. In order to allow the classification of the type of harmonic loads, harmonic currents order produced by aggregate harmonic loads and the level of emission are modelled using the Multi-Layer Extreme Learning Machine with autoencoder (hereinafter denoted as ML-ELM-AE). The feasibility of ML-ELM-AE on the classification of the Harmonic empirical data set will be probed, for when the classification results of the Harmonic load types become available, it can come in handy to power system analyst or engineers for analysis in later stage. They can use it to determine the harmonic distortion patterns and to characterize the harmonic currents at network buses. Depending on whether the aggregate load is residential, commercial, or industrial, the load characteristics in terms of its harmonic contents are likely to be different. The achieved results demonstrate the effectiveness of the investigated technique in dealing with the real world power system application of harmonic load type classification, that can be useful in providing good indication to the power system or distribution network planner.

The hierarchical control strategy enables seamless integration of power electronics-based distributed generators (DGs) into microgrids (MGs). This work presents a distributed coordinated secondary voltage and frequency control strategy of islanded MGs, utilizing distributed model predictive control (DMPC) approach. The Proposed approach is entirely distributed in nature, with plug and play features and requires minimal communication network with information exchange between immediate neighbors. This technique facilitates efficient information exchange and obviates the need for centralized control. Droop control is the primary controller for all the DGs, which leads to the deviations in DG voltage and operating frequency from standard nominal values. Secondary control enables the restoration of DG voltage and frequency to their nominal values. Input–output feedback linearization (IOFL) is used to transform nonlinear dynamics of inverter-interfaced DGs into first-order linear dynamics between input and output. Compared to some published works, the single-integrator dynamics eliminates the need to compute the derivative of the output voltage. Furthermore, DMPC has been used for all DG units as secondary controller, to achieve voltage and frequency regulation. This approach takes advantage of distributed architecture with optimal control actions and enhances reliability and flexibility of MG operations. Moreover, the proposed approach ensures that voltage and frequency of overall system are restored to its reference value while maintaining accuracy in real power sharing. Effectiveness of proposed control scheme is validated with simulations conducted on islanded MG test system using MATLAB/Simulink toolbox.

Distributed secondary frequency control in microgrids: Robustness and steady-state performance in the presence of clock drifts

This paper focuses on the development of a fast aggregate electricity load model under steady-state and dynamic conditions. An important requirement of such a load model is that it should be robust, analytically sound, and conceptually clear. Besides, the model can be easily incorporated into existing programs of power system analysis. By using quasi-linear approximation made on the dynamic components of power demands, the general model is described in the paper by a combination of a linear system and a non-linear function. From the general model, the step response of the load is derived. The model is then reduced into a discrete one based on the step response. Successive applications of such a discrete model provide a good approximation of load dynamics. To evaluate parameters of the proposed discrete load model, an identification algorithm is developed to read data from a sliding sample window of bus voltages and load responses. By comparing the identification results with the detailed simulation of a test system, the proposed fast model is shown to provide good representation of the consumer load response under static and dynamic conditions. Furthermore, aggregate load characteristics have been taken into account in the voltage control of a study power system to demonstrate the importance of aggregate load modelling with respect to suppressing transients, reducing control errors and preventing reverse actions in voltage regulation.

The progression of modern computing technologies assists the development of cyber-physical systems, which are transforming the legacy electrical power systems into smarter ones. The informationalization of the grid poses potential vulnerabilities concerning cyberattacks. With dynamic variations over time, cyberattacks can cause significant impacts on the secondary frequency control with various attack scenarios. In this article, by divulging the characteristics of dynamic attacks, the stability and dynamic responses of secondary frequency control systems are analyzed. The complete attack models considering dynamic load altering attack and dynamic false data injection attack are both derived first. Then the system stability is evaluated with different attack models through mathematical analysis. Eventually, the simulation studies against two benchmark power system models validate the evaluation results.

The paper develops a co-ordinated control scheme based on linear programming (LP) for the secondary control in a power system where it is required to restore system security in relation to voltages and power flows, and, simultaneously, minimize the network loss, following a system disturbance or contingency. The secondary control scheme proposed is more general than the classical secondary voltage control where only voltages are considered. The scheme automatically adjusts the reference settings of the power system controllers to achieve the objectives specified in the secondary control. The algorithm is derived on the basis of the linearized power system model the parameters of which are determined online using the information obtained from the phasor measurement units and/or state estimation. The LP-based scheme is suitable for online application in secondary control. Representative results based on a test power system with FACTS devices and subject to disturbance/contingency are included in the paper.

Lyapunov-based distributed secondary frequency and voltage control for distributed energy resources in islanded microgrids with expected dynamic performance improvement

ABSTRACTEskom, South Africa's national power utility, is transitioning from centralised, large‐scale electricity coal generation to a more distributed, small‐scale inverter‐based renewable generation to reduce greenhouse gas emissions. This shift poses operational challenges, particularly in maintaining power system frequency stability, which relies on real‐time balancing of supply and demand. Traditionally, frequency stability has depended on accurate load forecasts, sufficient generation capacity, and energy reserves from large generators to handle disturbances. However, as the number of large generators decreases, energy reserves will also reduce, potentially compromising frequency stability. This paper introduces the concept of integrating small‐scale distributed generators to enhance both primary and secondary frequency control. By actively monitoring and managing these inverter‐based generators, while accounting for phase balancing and network congestion, the proposed system seeks to improve grid stability, minimise reliance on large generators, and mitigate the risk of secondary frequency drops within an unmanaged inverter‐based network (i.e. the high rate of change of frequency (RoCoF) may lead to inverter trips).

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.

Optimized robust control for improving frequency response of delay dependent AC microgrid with uncertainties

This paper discusses the impact of discrete secondary controllers on the dynamic response of power systems. The idea of the paper originates from the observation that there is a range of values, from few tens of seconds to few minutes, of the execution cycles of conventional automatic generation control (AGC) that leads to a limit cycle. Below and above this range the system is stable. This is certainly not a problem in practice as the AGC updates the power set points of generating units every few seconds. However, this phenomenon has interesting consequences if one considers real-time electricity markets with short dispatch periods (i.e., 5 minutes) as these markets can be modeled as a sort of AGC. The paper first provides a formal analogy between conventional AGC and real-time electricity markets. Then it shows that the discretization-driven instability exists if the system includes a real-time electricity market modeled as secondary frequency controller. Finally, the paper discusses the impact of the combined effect of high wind generation shares and discrete secondary controllers on power system dynamics.