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Highlights • A security-constrained co-planning of power lines and energy storage is proposed. • The corrective control with multi-energy storages and generator units is studied. • The large-scale formulation is solved using Benders decomposition algorithm. • Case studies on the real-world power system in Gansu, China are conducted. Abstract This paper presents a security-constrained co-planning of transmission line expansion and energy storage with high penetration of wind power. The energy storage can not only improve the accommodation of renewable generation but also help to mitigate the emergency overflow under the post-contingency state. Also, the adjustment capabilities of the wind farms are considered, and the risk of excessive wind curtailment under the post-contingency state is assessed quantitatively. The coordinated multistage corrective control strategy for the battery storage, the pumped storage, thermal generators, and wind farms is studied. The mixed-integer linear programming problem based on the proposed corrective control strategy has been formulated. The Benders decomposition algorithm is introduced to divide the co-planning problem into one master problem and two sub-problems. In the master problem, the system is operating under normal conditions, so the security constraints are not considered. It minimizes the sum of the investment cost of newly built facilities and the operational cost. In the sub-problems, the corrective control during different post-contingency stages is formulated, minimizing the risk costs under fault conditions. The two-step technique is developed to generate the Benders cuts from the mixed-integer linear programming sub-problems, and return to the master problem. The real-world power system in Gansu, China is studied to validate the applicability and scalability of the proposed model and solution technique. The results denote that the co-planning model with security constraints is profitable in the real power system, with savings of 25% for the newly built transmission lines and a 5.5% reduction in total cost. [ABSTRACT FROM AUTHOR]

The construction of the uncertainty set is a key aspect of robust unit commitment (RUC) for the power systems with wind power integrated. The existing uncertainty sets based on the convex hull of historical data are limited to the specific shape of the historical data set or with high computational burden. In this letter, we propose the partition-combine method to build the minimal uncertainty set with the irregularly-distributed historical data. The partition of the box set is used to reduce the size of the uncertainty so that the set can properly adapt the data provided and is no longer limited to a specific shape. The combination of non-empty subsets is used to formulate the model of uncertainty set instead of the extreme points. The scale of uncertainty variables is reduced with quick identification of inner subsets which contain no extreme points. The simulation results validated the enhanced performances of the proposed method from both the conservativeness and computational burden perspectives. [ABSTRACT FROM AUTHOR]

This paper presents an open‐access Matlab/Simulink‐based power system simulation toolbox (MatPSST) for research and education. In MatPSST, dynamic modeling is implemented by Simulink. Only the initialization process is coded in Matlab. This structure makes full use of Simulink, enabling users to fully use the rich solvers and built‐in toolboxes in Matlab/Simulink, such as small‐signal analysis, without additional programming. The interaction with real‐time platforms like RTLAB and dSPACE in MatPSST is convenient through the Simulink interface. In addition, MatPSST provides a uniform interface and flexible framework for user‐defined functions. Users do not need to consider the interaction between models and dynamic solvers when implementing state‐of‐the‐art user‐defined models. To avoid the heavy work (replicate units and change parameters) in modeling detailed wind farm or photovoltaic station with hundreds of renewable generation units, the idea of the vector‐variable‐based model is proposed with MatPSST. Case studies introduce some selected application examples of MatPSST in research and education and demonstrate its accuracy by the comparisons with Simscape and PSAT. The cases reveal the advantages of MatPSST in promoting power system research and education. [ABSTRACT FROM AUTHOR]

With increasing wind farm scale, dynamic modeling and simulating the low-voltage ride-through (LVRT) process of wind farms are time- and source-consuming. Thus, a dynamic equivalent model of a wind farm considering the LVRT process is necessary and vital for power system analysis. However, the crowbar status of each doubly-fed induction generator (DFIG), voltage, and wind speed differences among will influence the LVRT process and equivalent results. To consider these three factors comprehensively and eliminate the error, this paper proposes a three-stage dynamic equivalent modeling approach, using accurate crowbar identification and voltage differences among DFIGs. Stage I: DFIGs are divided by crowbar status. A new accurate crowbar identification method is proposed to consider the interference from other DFIGs, using the experimental two-machine system and several dynamic simulations to correct fault voltage. Stage II: The often-overlooked voltage differences are considered, and DFIGs are divided into different clusters for accurate fault dynamics. Stage III: To eliminate errors resulting from wind speed differences, the DFIG active power reference is corrected based on the analytical function of the wind farm LVRT process. The proposed model can accurately identify crowbar status and consider the voltage and wind speed differences without detailed model simulation results, improving the accuracy. Case studies are undertaken on a wind farm with fifty DFIGs. Simulation results indicated that the proposed model can match the detailed model under different wind scenarios and fault voltages, and it also increases simulation efficiency, which is suitable for studying the effect of LVRT on power systems. [Display omitted] • A three-stage dynamic equivalent method is proposed to model the wind farm. • Fault voltage is corrected to identify crowbar status given DFIGs' mutual impact. • Voltage differences among wind turbines are considered to reduce equivalent error. • The simulation results demonstrate the effectiveness of proposed equivalent method. • The proposed model can capture the LVRT process of large-scale wind farm. [ABSTRACT FROM AUTHOR]

This paper proposes a general optimal design method of probabilistic robust damping controllers (PRDCs) to suppress multiband oscillations in the power system integrated with wind farm. The proposed optimal design method consists of the following two steps. In the first step, owing to the high efficiency of the probabilistic collocation method (PCM), it is adopted to investigate the probabilistic small signal stability analysis (PSSSA) of power system integrated with wind farm. In the second step, a novel adaptive compass search (ACS) with an adaptive sequence of exploration directions is proposed to enhance the global searching ability through the previous searching results, and the proposed ACS is used to obtain the parameters of the PRDCs via solving an optimization problem based on the results of PSSSA obtained from the first step. Case studies are conducted on 16-machine 68-bus system to verify the accuracy and computational efficiency of the PCM. Moreover, simulation studies are also conducted to verify the advantages of the control performances of ACS in the design of damping controllers compared with that of the traditional residue method, particle swarm optimization (PSO), grey wolf optimizer (GWO), and teaching learning-based optimization (TLBO), respectively. Finally, the effectiveness of the proposed method is validated by the time-domain simulation. • Probabilistic robust damping controllers is proposed to suppress oscillations. • Probabilistic small signal stability analysis of power system with wind is studied. • Probabilistic collocation method is employed to improve analysis efficiency. • Adaptive compass search is proposed to obtain parameters of the damping controller. • Simulation results verify the effectiveness of the proposed damping controller. [ABSTRACT FROM AUTHOR]

Different from conventional power plants, a wind farm usually consists of hundreds of wind generators and collector systems with arbitrary topology. The numerous devices increase modeling efforts and computational burden. This paper proposes a vector-variable based method for dynamic modeling of the large-scale wind farm considering collector system dynamics. Using the vector variables, the modeling method converts the complex wind farm containing many components to a model consisting of two typical submodules, the wind generator module and the collector system module. These submodules can establish any number of wind generators and any topology of the collection systems considering dynamics freely, with good scalability. The correctness and high simulation efficiency of the established model are validated by the electromagnetic model. Furthermore, a detailed wind farm containing twenty-five wind generators is built via the proposed method. Compared with the aggregation model, the results show that the established model can reflect the wind farm stability accurately. Also, by comparing with the model neglecting the collector system dynamics, the results reveal the relative error caused by neglecting the collector system dynamics can lead to misjudgment of instability mode when analyzing the sub-synchronous modes. [Display omitted] • Based on vector variables, two typical modules can model whole wind farm in detail. • The model has better scalability and higher efficiency than electromagnetic model. • The model can reveal dynamics of wind farm more precise than aggregation model. • Neglecting collector network dynamics will cause misjudgement of instability mode. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-level coordinated control (MLCC) scheme for symmetrical bipolar modular multilevel converter based high voltage direct current (MMC-HVDC) integrated offshore wind farms. MLCC makes full use of the energy control capability of MMCs to effectively suppress DC overcurrent triggered by submarine cable breakage. This MLCC scheme consists of four control levels. The first level is for the offshore fault pole MMC. Once a DC submarine cable is broken, the fault pole MMC of the offshore converter station passively absorbs power from wind farms using the storage capacity of internal sub-module capacitors. This buys time for the rest of the control to start. The second level is for the onshore non-faulty pole MMC, which can actively raise the DC voltage to suppress DC overcurrent. The third level is for offshore non-fault pole MMC, which balances the power delivered to the DC system in real-time based on the power received from wind farms. The fourth level is for offshore wind farms, which reduce power to restore the non-fault pole submarine cable transmission power and current to the allowed state. The correctness and effectiveness of the proposed MLCC in different scenarios are verified using the PSCAD/EMTDC. [Display omitted] • The fault characteristics of the symmetrical bipolar MMC-HVDC are analyzed. • A sub-module capacitor energy control scheme of offshore MMC is designed. • A multi-level coordinated control (MLCC) is proposed to suppress DC overcurrent. • MLCC can combine safety and economy at the same time. [ABSTRACT FROM AUTHOR]

• Wide-area power oscillation damper (WPOD) is used to damp interarea oscillation. • Networked predictive control-based WPOD is proposed for DFIG-based wind farm. • The data transmission and packet dropouts of WAMS are modeled in detail. • The proposed WPOD can compensate the time delay and data dropout actively. • Case studies are conducted to verify the effectiveness of the proposed WPOD. Data dropouts and time delays introduced in communication network would degrade the damping performance of the wide-area power oscillation dampers (WPODs) or may even cause instability of the closed-loop system. This paper establishes a data transmission model in the network control system (NCS) and proposes a networked predictive control (NPC) based WPOD of doubly-fed induction generator (DFIG)-based wind farm to damp inter-area oscillations in a large-scale interconnected power system. The major advantage of the proposed WPOD is that it can actively compensate packet dropouts and communication delays involved in wide-area control channels. Additionally, online model identification is employed to handle the parameter uncertainties and operating condition variations of the power system. Case studies are undertaken on the 16-machine 68-bus power system. Simulation results show that the proposed WPOD can provide better damping performances than those of the conventional WPOD over a wide range of operating conditions and different communication delays and packet dropouts. [ABSTRACT FROM AUTHOR]