High Renewable Penetrated Power Systems Research Articles

Coordinated restoration of inverter‐based power sources and synchronous generators for the high renewable penetrated power system considering the dynamic frequency regulation capability

AbstractExtensive inverter‐based power sources (IPS) impose significant challenges on the restoration of high renewable penetrated power systems (HRPPS). To enhance HRPPS resilience, the proper utilization of IPSs must be implemented. Combining frequency dynamics of IPSs and synchronous generators, this paper proposes a coordinated restoration method for multi‐type power sources after a major blackout. First, interactions between synchronous generators and IPSs are systematically analyzed. Based on this, output characteristics and constraints of IPSs in the power sources restoration process are quantified. Second, the dynamic frequency regulation capability (DFRC) of restored systems is quantified based on a unified transfer function structure model. Then the maximum power disturbance that restored systems can bear is derived based on DFRC indices including the maximum frequency deviation and the rate of change of frequency. Third, considering interactions between power sources and the DFRC of restored systems, a coordinated restoration optimization model of multi‐type power sources is proposed. Finally, case studies based on a modified IEEE 39‐bus system are simulated to verify the applicability and superiority of the proposed method. Meanwhile, results show that the proposed method for quantifying DFRC is more suitable for HRPPSs than traditional inertia‐based methods.

Voltage Stability Constrained Operation Optimization: An Ensemble Sparse Oblique Regression Tree Method

Voltage stability remains a main challenge for high renewable penetrated power systems. In future power systems, the dispatch needs to consider the voltage stability margin. However, considering static and transient voltage stability is challenging because a complex relationship exists between voltage stability and operation state variables. This paper proposes an ensemble sparse oblique regression tree method for voltage stability constrained operation optimization. First, we train multiple oblique regression trees on voltage stability simulation datasets. The trained trees are then grouped into ensemble using a boosting method to extract accurate and understandable voltage stability rules. Finally, the rules are embedded as mixed-integer linear programming constraints in a linear optimal power flow model. Validation on the IEEE-14 case shows the interpretability and efficiency of the proposed algorithm. Case studies on the Qinghai power grid and IEEE-118 further show that the proposed strategy can effectively improve the voltage stability margin of optimized operation states.

Communication Resources Allocation for Time Delay Reduction of Frequency Regulation Service in High Renewable Penetrated Power System

Communication Resources Allocation for Time Delay Reduction of Frequency Regulation Service in High Renewable Penetrated Power System

Data-Driven Security and Stability Rule in High Renewable Penetrated Power System Operation

Power systems around the world are experiencing an energy revolution that substitutes fossil fuels with renewable energy. Such a transition poses two significant challenges: highly variable generators that add short-term and long-term difficulties for supply–demand balance, and a high proportion of convertor-based devices that may jeopardize power system security and stability. At the same time, machine learning techniques provide more opportunities to study the complex power system security and stability problems. This article summarizes the machine learning framework to embed security rules into power system operation optimization under high renewable energy penetration. First, we explore how high penetration renewable energy impacts power system security and stability. Then, we review how the complex security and stability boundary of power systems is modeled using various machine learning techniques. Finally, we show how the machine learning model is transformed into optimization constraints that can be embedded into the power system operation model. The framework is substantiated through case studies of practical power systems.

Guest Editorial Toward Reliability Enhancement and Smarter Sensing for Emerging Interacting Dynamics in High Renewable Penetrated Power System

This Special Issue of the IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS) is dedicated to provide a bridge among multidisciplines to enhance the reliability and sensing throughout the fundamental theory and practical design in high renewable penetrated power systems.

Grey System Theory Based Net Load Forecasting for High Renewable Penetrated Power Systems

Net-load is the imbalance between aggregated load and renewable generation. System operations like economic dispatch necessitate accurate forecasting of net-load. There has been significant progress in load and renewable generation forecasting, however, little research focus has been there on Net-Load Forecasting (NLF). Therefore, this paper proposes three Direct Grey index net-load forecasting models (DGM (1, 1), DGM (1, 2) and DGM (1, 3)) using Grey System Theory (GST). GST based models are suitable for accurate and fast very short-term (five minutes ahead) forecasting due to their momentum transfer behavior. Proposed NLF models are implemented for the Bonneville Power Administration (BPA) balancing area. Forecasts obtained from proposed models are compared with actual net load data and forecasts obtained from reference Artificial Neural Network (ANN) model. Comparison with actual net load shows that proposed models have strong potential for very short-term NLF. At very short time frames, net load shows a very high correlation with previous time steps data. Proposed models utilize such characteristics for forecasting, compared to continuous error reduction procedure in ANN. Continuous error reduction in a very short time frame can lead to under/overestimation of ANN weights and that lowers the forecasting accuracy. Proposed NLF models, especially DGM (1, 3) show superior performance over ANN.

A Fast-Algorithmic Probabilistic Evaluation on Regional Rate of Change of Frequency (RoCoF) for Operational Planning of High Renewable Penetrated Power Systems

The high rate of change of frequency (RoCoF) issue incurred by the integration of renewable energy sources (RESs) into a modern power system significantly threatens the grid security, and thus needs to be carefully examined in the operational planning. However, severe fluctuation of regional frequency responses concerned by system operators could be concealed by the conventional assessment based on aggregated system frequency response. Moreover, the occurrence probability of a high RoCoF issue is actually a very vital factor during the system planner’s decision-making. Therefore, a fast-algorithmic evaluation method is proposed to determine the probabilistic distribution of regional RoCoF for the operational planning of a RES penetrated power system. First, an analytical sensitivity (AS) that quantifies the relationship between the regional RoCoF and the stochastic output of the RES is derived based on the generator and network information. Then a linear sensitivity-based analytical method (LSM) is established to calculate the regional RoCoF and the corresponding probabilistic distribution, which takes much less computational time when comparing with the scenario-based simulation (SBS) and involves much less complicated calculation procedure when comparing with the cumulant-based method (CBM). The effectiveness and efficiency of the proposed method are verified in a modified 16-machine 5-area IEEE benchmark system by numerical SBS and analytical CBM.

Developing of Quaternary Pumped Storage Hydropower for Dynamic Studies

Quaternary pumped storage hydropower (Q-PSH) technology, as one of the new advanced-PSH technology, has been developed by taking advantage of Conventional-PSH (C-PSH) and Adjustable Speed-PSH (AS-PSH). By combining adjustable-speed pump unit and conventional hydropower turbine unit in the quaternary configuration, Q-PSH has the more competitive capability of providing fast power support in the future high renewable penetrated power system. Acting as energy storage (ES), Q-PSH provides promising power supply to deal with the uncertainty and variability from renewable energy generation. This paper focuses on the dynamic modeling of Q-PSH technology employing full-converter machine and the impact of Q-PSH on the frequency response in a system. The detailed model of Q-PSH is developed and implemented in the IEEE 14-bus system based on GE Positive Sequence Load Flow (PSLF) platform, which captures the dynamic of multiple operation modes, especially hydraulic short-circuit (HSC) operation mode. Several cases are set up to reveal the advantages of Q-PSH technology when power electronic based renewable energy generation is deployed in the system. Sensitivity studies of the controller in pump governor show the impact of parameters in pump response performance. The comparison case illustrates the impact of frequency response provided by the Q-PSH in the system.

A Modified DSC-Based Grid Synchronization Method for a High Renewable Penetrated Power System Under Distorted Voltage Conditions

With the increasing penetration of renewable energy, a weak grid with declining inertia and distorted voltage conditions becomes a significant problem for wind and solar energy integration. Grid frequency is prone to deviate from its nominal value. Grid voltages become more easily polluted by unbalanced and harmonic components. Grid synchronization technique, as a significant method used in wind and solar energy grid-connected converters, can easily become ineffective. As probably the most widespread grid synchronization technique, phase-locked loop (PLL) is required to detect the grid frequency and phase rapidly and precisely even under such undesired conditions. While the amount of filtering techniques can remove disturbances, they also deteriorate the dynamic performance of PLL, which may not meet the standard requirements of grid codes. The objective of this paper is to propose an effective PLL to tackle this challenge. The proposed PLL is based on quasi-type-1 PLL (QT1-PLL), which provides a good filtering capability by using a moving average filter (MAF). To accelerate the transient behavior when disturbance occurs, a modified delay signal cancellation (DSC) operator is proposed and incorporated into the filtering stage of QT1-PLL. By using modified DSCs and MAFs in a cascaded way, the settling time of the proposed method is reduced to around one cycle of grid fundamental frequency without degrading any disturbance rejection capability. To verify the performance, several test cases, which usually happen in high renewable penetrated power systems, are carried out to demonstrate the effectiveness of the proposed PLL.

Operation of a High Renewable Penetrated Power System With CSP Plants: A Look-Ahead Stochastic Unit Commitment Model

The integration of variable renewable energy (VRE) generation, i.e., wind power and solar photovoltaic, brings significant uncertainty for the power system operation. Different with VRE techniques, concentrating solar power (CSP) is an appealing renewable generation technology due to its dispatch ability through the use of thermal energy storage and is thus expected to play a significant role in high renewable energy penetrated power systems. In this paper, we propose a look-ahead stochastic unit commitment model to operate power systems with CSP under high renewable energy penetration. It has a three-stage structure. The first stage optimizes the operational decisions in a day-ahead framework based on forecasts; the second stage minimizes the expected generation cost for possible realizations in the real time; and the third stage accounts for look-ahead operation in future operating days. This paper has a dual purpose: first, exploring how CSP plants operate in high renewable penetrated power systems; and second, analyzing the benefits of CSP in accommodating VRE generation. A case study on a modified IEEE RTS-79 system with actual solar and wind power data is provided to validate the proposed method.

Flexible Frequency Operation Strategy of Power System With High Renewable Penetration

Growth of renewable penetration will increase the requirement for flexible resources. It may be a simple solution to build more flexible resources, but it is too expensive. Recently, the new construction of power plant or transmission line has faced opposition by the resistance of the local residents. Depending on the needs, new methodologies are required in order to gain the flexibility of the power grids. This paper proposes the flexible frequency operation strategy with significant renewable penetration to achieve the flexibility of the power grids. Flexible frequency operation provides customized frequency through BTB HVDC, and the overall system is operated with relaxed frequency regulation. By reducing the need and role of the frequency ancillary service reserve, an operator does not need to secure additional governor response reserve for renewable energy. In order to model frequency dynamic of high renewable penetrated power system, the swing equation is modified in this paper. The case studies using MATLAB show effectiveness of flexible frequency operation strategy.