Search

This paper proposes a virtual inertia control strategy for wind farms based on auto disturbance rejection controller with artificial bee colony (ABC) algorithm. First, based on the system frequency dynamic response equation, an active disturbance rejection controller is designed according to the non‐linear feedback control law and the extended state observer to improve the anti‐interference capability of the virtual inertia control system. Second, in order to solve the problem of difficulty in tuning the parameters of the active disturbance rejection control (ADRC), an ABC algorithm based on nectar collection behaviour was proposed to iteratively optimize the parameters of ADRC. Finally, the proposed control method is effectively verified based on Matlab/Simulink. The simulation results show that compared with traditional algorithms, the proposed ABC‐ADRC can effectively control the rotor speed to adjust the frequency of the power grid system, achieve power sharing and adaptive noise elimination, reduce the complexity of parameter settings, not only improve anti‐interference ability, but also enhance the robustness of the system. [ABSTRACT FROM AUTHOR]

In a high proportion of new energy grids or a 100% new energy source of power grid, the dynamic performance of PMSG under fault conditions is very important. However, the current small signal model lacks detailed and deep analysis of a permanent‐magnet synchronous generator (PMSG)‐based wind power generation under LVRT control. Here, a small signal model of a PMSG under pre‐fault, fault and after fault failure recovery stages are established. This paper employs linear analyses to characterize the dynamic performance of a PMSG‐based wind power generation system under LVRT control and practical generator characteristics. In particular, the conflict between frequency regulation and LVRT is discussed based on the constructed model. On this basis, the impact of dc‐link bandwidth on the system performance during failure recovery stage is discussed, and the active damping method is analysed to improve the performance of PMSG during failure and failure recovery stages. Finally, time‐domain simulations are utilized to verify the analyses and models discussed. The research results in this paper are helpful to promote and improve the performance of PMSG during LVRT conditions. [ABSTRACT FROM AUTHOR]

Economic operation and reliable supply‐demand balance are problems of paramount importance in power grids with a massive share of intermittent renewable energy sources (RESs) of great interest. This paper sought an optimal coordinated generation scheduling for day‐ahead power system operation considering RESs and energy storage units. Renewable power generation, particularly, wind and photovoltaic are uncontrollable, whereas can be predicted using forecasting models. Within the proposed framework, a hyperparameter‐optimized long short‐term memory (LSTM) regression model is employed to forecast the day‐ahead weather from the historical time‐series weather data. Eventually, an empirical formula is used to estimate the power conversion from the day‐ahead weather forecasts for a selected PV module and wind turbine. The objective of the scheduling framework is to keep a delicate supply‐demand balance at the lowest possible cost of generation while maintaining the prevailing generation and system constraints. A variance measure uncertainty handling‐based grey wolf optimizer (GWO) technique is used to find the optimal day‐ahead generation schedules and dispatches under RESs forecast uncertainty. The proposed generation scheduling framework is examined on the IEEE 6 and 30‐bus systems. In the studied scenarios, the coordinated operation of generators can decrease the total day‐ahead operating cost for the modified IEEE 6‐bus system by 2.57% compared to supplying electricity generation with conventional generators alone. Likewise, the total operating cost from the coordinated operation of all generation portfolios was reduced by 6.93% from the operating cost of generation during base case simulation (supply only from dispatchable thermal units) on the modified IEEE 30‐bus system. Moreover, the case studies show that coordinated generation scheduling can mitigate the RESs power variability problem, provide secure supply‐demand operation, and minimize the operating cost of electricity generation. [ABSTRACT FROM AUTHOR]

With the fast development of cyber‐physical power systems, coordinated cyber‐physical attacks have become one of the main threats to the security of modern power grid. Considering that it is difficult for attackers to obtain full information of the entire power grid, the coordinated cyber‐physical attack problem for partitioned power grid is studied in this paper, and a tri‐level defender‐attacker‐dispatcher optimization model with consideration of wind power uncertainty in a specific coordinated cyber‐physical attack mode is proposed. The Karush‐Kuhn‐Tucker (KKT) condition and an improved implicit enumeration algorithm are applied to obtain the solution of the complicated optimization problem effectively. In addition, two risk assessment indices pertinent to the physical lines and load measurements are proposed according to the obtained total amount of optimized load shedding and coordinated attack‐defense strategy under valid attack‐defense scenarios. Taking a partitioned IEEE 39‐bus test system as example, the risks of physical transmission lines and load measurements in different areas under attacks are elaborately studied, and the impact of wind power uncertainty on attack‐defense strategies is discussed as well. Numerical simulation results illustrate the effectiveness of the proposed optimization model and risk assessment indices, and some significant conclusions are drawn. [ABSTRACT FROM AUTHOR]

The power characteristics of offshore wind power will change the regional power flow distribution and affect the regional voltage. Here, the direct‐drive wind turbine generator controlled by unity power factor is selected as the research object, and the influence of change of wind power on voltage at the grid connection point is analyzed from the simple integration model. Based on the two critical states of the external equivalent power of the grid connection point, an analytical expression of the output of wind power in the corresponding state is obtained, and the relationship among the critical state outputs, the output of wind power and the parameters at the grid connection point is drawn, hence the related influence laws is analyzed. The influence of change of wind power on voltage and regional reactive power and the reactance distribution of transmission lines near the grid connection point is considered to analyze the influence of offshore wind power on the vicinity region of grid connection point. The rationality of the conclusion is verified by study the cases of the integration of offshore wind power into Guangdong power grid, and some suggestions are put forward for the planning of offshore wind power integration. [ABSTRACT FROM AUTHOR]

Utilizing energy storage systems equipped with virtual/synthetic inertia control has emerged as one of the solutions to solve low inertia issues in power systems with massive penetration of renewables. However, while the aspect regarding the control of the synthetic inertia control has been widely investigated, the optimal placement of synthetic inertia control is rarely investigated. Therefore, the optimal placement of energy storage system with synthetic inertia control based on swarm‐based mean‐variance mapping optimization is proposed. The performance of the proposed method is tested by considering several cases, both single and multiple contingencies. By utilizing the proposed method, the optimal placement of energy storage system equipped with synthetic inertia control could be obtained, in which the resulting frequency response is better compared to randomly placed ones. The proposed method could also be applied by considering multiple contingencies in different locations. Furthermore, the resulting fitness values for different independent optimization repetitions for various study cases are consistent, leading to the efficacy to be applied in the actual power system planning. [ABSTRACT FROM AUTHOR]

With the large‐scale integration of renewable energy into power systems, the strong correlation of wind power output as an important feature will inevitably bring huge impact on power grid planning and operation. However, due to the proliferation of planning and operation scenarios, the traditional power grid planning method can no longer guarantee the operation flexibility and stability under the fluctuation of new energy. In this work, a bi‐level transmission and generation expansion planning (TGEP) model considering the correlation of wind power based on mixed integer linear programming (MILP) is proposed. Firstly, a variable‐structure point diagnosis method is proposed to improve the fitting accuracy of the correlation. Secondly, a scenario reduction method considering the correlation, joint probability distribution and geometric characteristics is proposed, which effectively provides a more matching operating scenarios basis for planning. Thirdly, a multi‐scenario bi‐level TGEP model is proposed. The upper‐level investment decision model aims at the economical goal, while the lower‐level multi‐scenario coordinated optimization operation model aims to minimize the weighted operation index. The impact of the correlation on the results of TGEP is examined and verified in case study. [ABSTRACT FROM AUTHOR]

Large‐scale day‐ahead wind power forecasting (WPF) for wind farm clusters (WFCs) can enable dispatching agencies to formulate scientifically sound power generation plans and enhance the robustness of power grids. Most available WPF methods for WFCs only involve mathematical models and rarely consider spatial correlation factors. This necessitates further improvements to forecasting systems. In this study, to increase the day‐ahead WPF accuracy for WFCs, fractal transform theory is introduced to optimize the process of WPF for WFCs through spatial upscaling and establish a day‐ahead WPF model for WFCs based on an improved spatial upscaling method. First, a WFC is partitioned into subclusters. Then, using fractal transform theory, an affine relation is established between the local output of each subcluster and the overall output of the WFC. Finally, a day‐ahead power forecast is produced for the WFC through spatial upscaling of the forecast for the subcluster with the highest grey relational grade with the output of the WFC. The applicability of the proposed forecasting model is examined using historical measured data for a large WFC in north‐eastern China. The case study results show that the proposed forecasting model outperforms the summation method and the statistical upscaling method in terms of forecasting accuracy. [ABSTRACT FROM AUTHOR]

Rapid expansion and integration of wind energy is restrained due to transmission capacity constraints and conventional generation technologies limited operational flexibility in today's power systems. Energy storage is an attractive option to integrate and utilise more renewable energy without major and timely upgrade of existing transmission infrastructure. Moreover, it can be considered as a means for differing the reinforcement plans. The evaluation of energy storage deployment projects is a challenging task due to severe uncertainty of wind power generation. In this study, a robust techno-economic framework is proposed for energy storage evaluation based on information gap decision theory for handling wind generation uncertainty. The total social cost of the system including conventional generators' fuel and pollution cost and wind power curtailment cost is optimised considering generators operational constraints and transmission system capacity limitations based on the DC model of the power grid. The effect of storage devices on system performance is evaluated taking into account wind power uncertainty. The proposed method is conducted on the modified IEEE reliability test system and the modified IEEE-118-bus test system to assess its applicability and performance in mid-term robust evaluation of energy storage implementation plans. [ABSTRACT FROM AUTHOR]

As a result of the increasing penetration of renewables in power systems, wind farms (WFs) have to satisfy the low-voltage ride-through (LVRT) requirement to stay connected to the power grid under fault conditions. This study proposes a novel method that uses the static synchronous compensator (STATCOM) to improve the LVRT capability of WFs during grid faults. The proposed method is based on the Taguchi method which involves orthogonal experiments. The allocation (locations and sizes) and fuzzy control gains of STATCOM are determined by the analysis of mean (ANOM) technique as part of the Taguchi method to achieve a robust design that is insensitive to variations of operating conditions and faults. The optimal STATCOM that is obtained by the proposed method is validated in both a single WF-infinite bus power system and the IEEE 39-bus power system. The simulation results show that the proposed method can enhance the LVRT capability of WFs. [ABSTRACT FROM AUTHOR]

The low and variable inertia due to the integration of large-scale wind generation poses severe challenges to the frequency control of the power grid. In this study, a novel model predictive control (MPC)-based load frequency controller (LFC), which can adapt to the changes in system inertia, is proposed to improve the frequency control effect. First, the inertia estimation scheme based on measurements is designed. Then, the state-space model, which is the key that determines the control effect of MPC, is corrected in time based on the estimated inertia. The proposed method in this study can avoid the problem of MPC-based LFC failure caused by inaccurate model parameters. The performance of the proposed strategy is demonstrated in two scenarios, i.e. wind power fluctuation and load multi-step, using a two-area interconnected power system with time-variant inertia. [ABSTRACT FROM AUTHOR]

As the deployment of wind and solar energy increases in the USA, energy storage (ES) will play an important role in future electric power grids to help manage the variability from high penetration levels of renewable generation, ES can provide promising power/energy demand to coordinate with renewables generation, as a virtual power plant (VPP). There is an industry need for the capability in power system studies to model ternary pumped storage hydropower (T-PSH), a pumped storage technology that offers increased system benefits. This study presents a comprehensive vendor-neutral dynamic model of T-PSH in GE's commercial software positive sequence load flow. A new governor model is developed with detailed gate valve modelling and a shared-penstock function. Specifically, this model is designed to simulate the seamless transition among three operation modes: generation mode, pumping mode, and hydraulic short-circuit mode. The developed T-PSH model has been tested and validated on a 10-bus test system. A comparison study of T-PSH to conventional pumped storage hydropower has also been conducted on the Western interconnection system. [ABSTRACT FROM AUTHOR]

Wind and solar have major share among the growing renewable penetration, due to their extensive availability and improved technologies. Both wind and solar generation are highly uncertain and intermittent as compared to system load. The increased number of such uncertain and intermittent variables necessitates complex multivariate operational strategies for system operation. A compilation of different uncertain and intermittent variables such as load, wind and solar generation, to a single uncertain variable called net load, reduces system operational planning complexity. Net load is the difference between total load and renewable generation. Thus, conventional generation units have to be scheduled for net load. Prior knowledge about net load can help optimum operational planning such as generation scheduling and power system flexibility estimations. There have been significant advancement in load and renewable generation forecasting over the last decades. Still, there is little attention towards net load forecasting (NLF). This study proposes a novel NLF model using Gumbel copula based joint probability distribution for load, wind and solar generation forecasting error aggregation. Gumbel copula covers all extreme forecasting errors due to max-stable property. Proposed model uses modified Grey index models for forecasting. Results show that proposed model has strong potential in very short-term NLF. [ABSTRACT FROM AUTHOR]

This study develops a new multi-stage (dynamic) approach for the co-planning of power and gas systems to deal with variable renewable energy resources (VREs). The model is formulated using a stochastic programming framework to accurately capture the unfolding of both short and long-term uncertainties faced by power and gas systems. The effects of high renewable energy penetration and renewable energy uncertainty in both systems are assessed while determining the optimal investment and operation decisions in several stages of the planning horizon. To prove the benefits of the proposed approach, the authors compare the results of the authors' framework with other methods used in the literature. The effectiveness of the framework is validated on a realistic case of Queensland, Australia, in which both networks are driven to capture the link between these systems and to accommodate the state's unique features of renewable availability. The results demonstrate that their dynamic approach provides more robust outcomes compared to other methods as it allows adapting the expansion plans to unexpected changes in the future. The analysis also shows that a transition towards renewable energy presents a higher cost, different investment strategies, and lower gas-fired consumption compared to the terminal renewable target. [ABSTRACT FROM AUTHOR]

Multi-terminal dc (MTDC) grids are expected to be built and experience rapid expansion in the near future as they have emerged as a competitive solution for transmitting offshore wind generation and overlaying their ac counterpart. The concept of inertia sharing for the control and operation of MTDC grids, which can be achieved by the proposed unified reference controller. The control objectives of the MTDC grids voltage source converter (VSC) stations are no longer limited to the stabilisation of MTDC grid, instead, the requirements of ac side are also met. The interaction dynamics between the ac and dc grid is analysed to illustrate the proposed concept. In addition, the voltage source converter stations can work in different operation modes based on the proposed unified control structure, and can switch among the operation modes smoothly following the secondary control commands. Simulation results exhibit the merits and satisfactory performance of the proposed control strategy for stable MTDC grid operation. [ABSTRACT FROM AUTHOR]

In recent years, the energy storage system (ESS) has been demonstrated to be involved in many aspects of the integration of wind power. For ESS application, ESS allocation of the installation location, power rating, and energy rating is the first concern. Different from previous studies, this study emphasises the significance of the ESS operation in the study of ESS allocation. A bi-level-programming-based model is proposed to take the interaction of allocation and operation into consideration at the same time, with the external level optimising allocation and the internal level optimising operation. The complexity assessment and solution algorithm of the model is also discussed. Next, a genetic numerical algorithm is proposed to solve the bi-level model. The authors' results were tested on a modified IEEE 39 bus system and a provincial regional power system to verify both the flexibility and applicability of the proposed model and algorithm. This model is useful for various types of ESS and provides a foundation for ESS application. [ABSTRACT FROM AUTHOR]