Proposed Frequency Control Strategy Research Articles

Frequency Coordination Control Strategy for Large-Scale Wind Power Transmission Systems Based on Hybrid DC Transmission Technology with Deep Q Network Assistance

Wind power is currently the most mature representative of sustainable energy generation technology, which has been developed and utilized on a large scale worldwide. The random and fluctuating nature of wind power output poses a threat to the secure and stable operation of the system. Consequently, the transmission of wind power has garnered considerable attention as a crucial factor in mitigating the challenges associated with wind power integration. In this paper, an artificial-intelligence-aided frequency coordination control strategy applicable to wind power transmission systems based on hybrid DC transmission technology is proposed. The line commutated converter (LCC) station at the sending end implements the strategy of auxiliary frequency control (AFC) and automatic generation control (AGC) to cooperate with each other in order to assist the system frequency regulation. The AFC controller is designed based on the variable forgetting factor recursive least squares (VFF-RLS) algorithm for system identification. First, the VFF-RLS algorithm is used to identify the open-loop transfer function of the system. Then, the AFC controller is designed based on the root locus method to achieve precise control of the system frequency. The DC line power modulation quantity is introduced in the AGC to automatically track the active power fluctuation and frequency deviation of the system. The AGC utilizes the classical proportional-integral (PI) control. By selecting the integrated time absolute error (ITAE) performance index to construct the reward function, and using a deep Q-network (DQN) for controller parameter optimization, it achieves improved regulation performance for the AGC. The voltage source converter (VSC) station at the receiving end implements an adaptive DC voltage droop control (ADC)strategy. Finally, the effectiveness and robustness of the proposed frequency control strategy are verified through simulation experiments.

Frequency control by BESS for smooth Island transition of a hydro‐powered microgrid

AbstractThis paper develops a frequency control strategy for a battery energy storage system to facilitate the smooth island transition of a hydro‐powered microgrid during unplanned grid outages. The proposed frequency control strategy uses a PI‐based droop controller, where the tuning of the controller accounts for the limitations in the power response of a hydro generator and the required frequency quality of the microgrid. The effectiveness of the frequency control strategy is verified in Simulink using phasor simulations, and it is further validated in laboratory tests. The results demonstrate that the proposed PI‐based droop and its tuning strategy fulfill the desired frequency quality requirement of the hydro‐powered microgrid without over‐dimensioning the size of the storage capacity as compared to the traditional proportional droop controller.

Frequency control strategy for sending-end of hybrid cascaded UHVDC system with large-scale wind power access

For the frequency overrun problem caused by the high proportion of wind power in the sending grid of hybrid UHVDC transmission system, the coordinated frequency control strategy of wind power and hybrid UHVDC system in the sending system is proposed. Firstly, the additional frequency control strategy considering primary frequency control and inertia characteristics is introduced in the wind turbines and the line commuted converter (LCC) station respectively, and the virtual inertia control strategy is introduced in the modular multilevel converter (MMC) station. Secondly, the action rules and control strategy of wind power and hybrid UHVDC system coordination involved in the power grid are designed. At the same time, the mechanism of frequency control strategy is analyzed​ based on the frequency response model of wind power and UHVDC integrated system. Finally, the simulation results indicate that the proposed frequency control strategy can enhance the inertia and primary frequency capability of the AC system at the sending end, and effectively improve the frequency stability problem of the AC system under different operating conditions.

Convex Neural Networks Based Reinforcement Learning for Load Frequency Control under Denial of Service Attacks

With the increase in the complexity and informatization of power grids, new challenges, such as access to a large number of distributed energy sources and cyber attacks on power grid control systems, are brought to load-frequency control. As load-frequency control methods, both aggregated distributed energy sources (ADES) and artificial intelligence techniques provide flexible solution strategies to mitigate the frequency deviation of power grids. This paper proposes a load-frequency control strategy of ADES-based reinforcement learning under the consideration of reducing the impact of denial of service (DoS) attacks. Reinforcement learning is used to evaluate the pros and cons of the proposed frequency control strategy. The entire evaluation process is realized by the approximation of convex neural networks. Convex neural networks are used to convert the nonlinear optimization problems of reinforcement learning for long-term performance into the corresponding convex optimization problems. Thus, the local optimum is avoided, the optimization process of the strategy utility function is accelerated, and the response ability of controllers is improved. The stability of power grids and the convergence of convex neural networks under the proposed frequency control strategy are studied by constructing Lyapunov functions to obtain the sufficient conditions for the steady states of ADES and the weight convergence of actor–critic networks. The article uses the IEEE14, IEEE57, and IEEE118 bus testing systems to verify the proposed strategy. Our experimental results confirm that the proposed frequency control strategy can effectively reduce the frequency deviation of power grids under DoS attacks.

Double stage controller optimization for load frequency stabilization in hybrid wind-ocean wave energy based maritime microgrid system

The momentum towards reduction of greenhouse gas emissions by reduced use of conventional source in marine power networks as well as significant development of renewable energy resources (RRs) have been the motivating factors for inclusion RRs in hybrid maritime microgrid system (HMμGS) and investigation of consequent frequent control mechanism. This article presents an approach of load frequency control in an independent HMμGS consisting of wind driven generation (WDG), Archimedes wave power generation (AWPG), marine biodiesel generator (MBG), solid-oxide fuel cell (SOFC) energy units, heat pump (HP) and freezer (FZR). The stability of the HMμGS model have been evaluated through the rigorous tests considering non-availability of renewable resources, concurrent random generation of AWPG, load demand, real recorded data of WDG. Comparative performance of several controllers such as PID, PID with filter (PIDN) and PI-(1 + PD) controller are presented with their parameters optimized using genetic algorithmic technique (GA), particle swarm technique (PSO), firefly algorithmic technique (FA), cultural algorithmic technique (CA) and the recent metaheuristic grasshopper algorithmic technique (GOA). The proposed frequency control strategy of HMμGS model is benchmarked by comparative statistical assessment and decision indicators. Finally, sensitivity assessment of GOA tuned PI-(1 + PD) controller under uncertain parametric variations such as; variation of WDG gain, droop factor (R), inertia constant (M) and loading without reoptimizing the optimal base condition values is conducted as an evidence of the sturdiness of the proposed frequency control strategy. The analysis of the results shows that the proposed GOA optimized PI-(1 + PD) control strategy perform much better than other control schemes.

A frequency control strategy of electric vehicles in microgrid using virtual synchronous generator control

In recent years, with the increase in energy resource penetration into power systems, more technical requirements regarding the frequency control capability of renewable energy have become required. Plug-in electrical vehicles (PEVs) have become increasingly commercialized, and vehicle-to-grid technology has received extensive attention. This paper proposes a novel frequency control strategy for EVs to participate in the primary and secondary frequency regulations of microgrids. Virtual inertia and virtual damping are introduced using a virtual synchronous generator through AC/DC control. Thus, the charging/discharging device has the characteristics of inertia and damping, which are similar to those of a synchronous generator. According to the droop characteristic of an EV’s charging frequency, the designed auxiliary frequency regulation method can be used to calculate the power adjustment to change the reference value of the EV’s charging/discharging power, allowing the EV to participate in the frequency regulation of a microgrid. The models and connected microgrid were established using MATLAB/Simulink software, and the proposed control strategy was tested. The proposed frequency control strategy can provide virtual inertia, damping, and frequency support; improve the dynamic stability; and realize an effective frequency regulation when the microgrid works in an independent operational mode.

Frequency control strategy of multi‐area hybrid power system based on frequency division and sliding mode algorithm

For renewable energy penetration, a frequency control strategy is proposed to assure the multi-area hybrid power system stable operation. The load frequency control (LFC) and the battery energy storage system (BESS) are used together to design the frequency control strategy. Furthermore, in order to improve the control accuracy and reduce the battery capacity, the area control error and active power disturbance are divided into low-frequency components and high-frequency components. Therefore, LFC is designed by using sliding mode algorithm for the low-frequency deviation and BESS is adjusted by using the designed disturbance observer for the high-frequency disturbance. Finally, the effectiveness of the proposed frequency control strategy is proved by the real-time digital simulator which can optimise the frequency quality and reduces the capacity of the BESS.

Performance of industrial melting pots in the provision of dynamic frequency response in the Great Britain power system

As a result of the increasing integration of Renewable Energy Source (RES), maintenance of the balance between supply and demand in the power system is more challenging because of RES’s intermittency and uncontrollability. The smart control of demand is able to contribute to the balance by providing the grid frequency response. This paper uses the industrial Melting Pot (MP) loads as an example. A thermodynamic model depicting the physical characteristics of MPs was firstly developed based on field measurements carried out by Open Energi. A distributed control was applied to each MP which dynamically changes the aggregated power consumption of MPs in proportion to changes in grid frequency while maintaining the primary heating function of each MP. An aggregation of individual MP models equipped with the control was integrated with the Great Britain (GB) power system models. Case studies verified that the aggregated MPs are able to provide frequency response to the power system. The response from MPs is similar but faster than the conventional generators and therefore contributes to the reduction of carbon emissions by replacing the spinning reserve capacity of fossil-fuel generators. Through the reviews of the present balancing services in the GB power system, with the proposed frequency control strategy, the Firm Frequency Response service is most beneficial at present for demand aggregators to tender for. All studies have been conducted in partnership between Cardiff University, Open Energi London – Demand Aggregator, and National Grid – System Operator in GB to ensure the quality and compliance of results.

Frequency Control Strategy of Hybrid Energy Storage System for Microgrid Based on Frequency Hysteretic Loop

Abstract In this paper, a frequency control strategy of hybrid energy storage system (HESS) for autonomous microgrid (AMG) based on a frequency hysteretic loop is proposed. The control strategy is composed of two modes. Mode I coordinates the relationship between the frequency control precision and the battery charge/discharge cycles. Mode II coordinates the charge/discharge priorities of battery and supercapacitor to achieve the optimal control of different energy storage systems. Finally, a test system is established to verify the effectiveness of the proposed frequency hysteretic loop based control strategy of HESS. The proposed frequency control strategy can make significant contribution to the stable operation of MG and promote the utilization level of renewable energy resources.