Showing papers on "Electric power system published in 2019"

Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network

Abstract: As the power system is facing a transition toward a more intelligent, flexible, and interactive system with higher penetration of renewable energy generation, load forecasting, especially short-term load forecasting for individual electric customers plays an increasingly essential role in the future grid planning and operation. Other than aggregated residential load in a large scale, forecasting an electric load of a single energy user is fairly challenging due to the high volatility and uncertainty involved. In this paper, we propose a long short-term memory (LSTM) recurrent neural network-based framework, which is the latest and one of the most popular techniques of deep learning, to tackle this tricky issue. The proposed framework is tested on a publicly available set of real residential smart meter data, of which the performance is comprehensively compared to various benchmarks including the state-of-the-arts in the field of load forecasting. As a result, the proposed LSTM approach outperforms the other listed rival algorithms in the task of short-term load forecasting for individual residential households.

Harmonic Stability in Power Electronic-Based Power Systems: Concept, Modeling, and Analysis

Abstract: The large-scale integration of power electronic-based systems poses new challenges to the stability and power quality of modern power grids. The wide timescale and frequency-coupling dynamics of electronic power converters tend to bring in harmonic instability in the form of resonances or abnormal harmonics in a wide frequency range. This paper provides a systematic analysis of harmonic stability in the future power-electronic-based power systems. The basic concept and phenomena of harmonic stability are elaborated first. It is pointed out that the harmonic stability is a breed of small-signal stability problems, featuring the waveform distortions at the frequencies above and below the fundamental frequency of the system. The linearized models of converters and system analysis methods are then discussed. It reveals that the linearized models of ac–dc converters can be generalized to the harmonic transfer function, which is mathematically derived from linear time-periodic system theory. Lastly, future challenges on the system modeling and analysis of harmonic stability in large-scale power electronic based power grids are summarized.

Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work

Abstract: This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

Abstract: Industrial cyber-physical systems (CPSs) are large-scale, geographically dispersed, and life-critical systems, in which lots of sensors and actuators are embedded and networked together to facilitate real-time monitoring and closed-loop control. Their intrinsic features in geographic space and resources put forward to urgent requirements of reliability and scalability for designed filtering or control schemes. This paper presents a review of the state-of-the-art of distributed filtering and control of industrial CPSs described by differential dynamics models. Special attention is paid to sensor networks, manipulators, and power systems. For real-time monitoring, some typical Kalman-based distributed algorithms are summarized and their performances on calculation burden and communication burden, as well as scalability, are discussed in depth. Then, the characteristics of non-Kalman cases are further disclosed in light of constructed filter structures. Furthermore, the latest development is surveyed for distributed cooperative control of mobile manipulators and distributed model predictive control in industrial automation systems. By resorting to droop characteristics, representative distributed control strategies classified by controller structures are systematically summarized for power systems with the requirements of power sharing and voltage and frequency regulation. In addition, distributed security control of industrial CPSs is reviewed when cyber-attacks are taken into consideration. Finally, some challenges are raised to guide the future research.

On-Line Building Energy Optimization Using Deep Reinforcement Learning

Abstract: Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the future power systems and to help customers transition from a passive to an active role. In this paper, we explore for the first time in the smart grid context the benefits of using deep reinforcement learning, a hybrid type of methods that combines reinforcement learning with deep learning, to perform on-line optimization of schedules for building energy management systems. The learning procedure was explored using two methods, Deep Q-learning and deep policy gradient, both of which have been extended to perform multiple actions simultaneously. The proposed approach was validated on the large-scale Pecan Street Inc. database. This highly dimensional database includes information about photovoltaic power generation, electric vehicles and buildings appliances. Moreover, these on-line energy scheduling strategies could be used to provide real-time feedback to consumers to encourage more efficient use of electricity.

Internet of Things-Aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Abstract: Traditional power grids are being transformed into smart grids (SGs) to address the issues in the existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability, and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution, and utilization systems. SGs employ various devices for the monitoring, analysis, and control of the grid, deployed at power plants, distribution centers, and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation, and the tracking of such devices. This is achieved with the help of the Internet of Things (IoT). The IoT helps SG systems to support various network functions throughout the generation, transmission, distribution, and consumption of energy by incorporating the IoT devices (such as sensors, actuators, and smart meters), as well as by providing the connectivity, automation, and tracking for such devices. In this paper, we provide a comprehensive survey on the IoT-aided SG systems, which includes the existing architectures, applications, and prototypes of the IoT-aided SG systems. This survey also highlights the open issues, challenges, and future research directions for the IoT-aided SG systems.

A new prediction model of battery and wind-solar output in hybrid power system

Abstract: In this paper short term power forecast of wind and solar power is proposed to evaluate the available output power of each production component. In this model, lead acid batteries used in proposed hybrid power system based on wind-solar power system. So, before the predicting of power output, a simple mathematical approach to simulate the lead–acid battery behaviors in stand-alone hybrid wind-solar power generation systems will be introduced. Then, the proposed forecast problem will be evaluated which is taken as constraint status through state of charge (SOC) of the batteries. The proposed forecast model includes a feature selection filter and hybrid forecast engine based on neural network (NN) and an intelligent evolutionary algorithm. This method not only could maintain the SOC of batteries in suitable range, but also could decrease the on-or-off switching number of wind turbines and PV modules. Effectiveness of the proposed method has been applied over real world engineering data. Obtained numerical analysis, demonstrate the validity of proposed method.

Distributed Blockchain-Based Data Protection Framework for Modern Power Systems Against Cyber Attacks

Abstract: The cyber security of modern power systems has drawn increasing attention in both academia and industry. Many detection and defense methods for cyber-attacks have therefore been proposed to enhance robustness of modern power systems. In this paper, we propose a new, distributed blockchain-based protection framework to enhance the self-defensive capability of modern power systems against cyber-attacks. We present a comprehensive discussion on how blockchain technology can be used to enhance the robustness and security of the power grid, by using meters as nodes in a distributed network which encapsulates meter measurements as blocks. Effectiveness of the proposed protection framework is demonstrated via simulation experiments on the IEEE-118 benchmark system.

Optimisation of demand response in electric power systems, a review

Abstract: Demand response programs offer efficient solutions for many power system problems, such as high generation cost, high demand’s peak to average ratio, high emissions, reliability issues and congestion in generation, transmission and distribution systems. Their main function is to assist power systems during peak demand hours and also during contingencies. They are a subcategory of the family of demand side management (DSM) strategies. DR programs are classified into two broad categories; price-based DR programs and incentive-based DR programs. In order to exploit their full potential, DR programs must be implemented optimally. Such a problem, which here is referred to as “DR optimisation problem”, is a hot research topic and has been frequently researched in the literature. This paper aims to review different research works on DR optimisation problems. Based on the conducted review, some directions for future research are proposed.

Event-Triggered $H_\infty$ Load Frequency Control for Multiarea Power Systems Under Hybrid Cyber Attacks

Abstract: This paper investigates the problem of event-triggered ${H_\infty }$ load frequency control (LFC) for multiarea power systems under hybrid cyber attacks, including denial-of-service (DoS) attacks and deception attacks. An event-triggered transmission scheme is developed under the DoS attacks to lighten the load of network bandwidth while preserving a satisfactory system performance. Then, a new switched system model accounting for the simultaneous presence of DoS attacks and stochastic deception attacks is established with respect to the LFC for multiarea power system. On the basis of the new model, sufficient conditions ensuring multiarea power system exponentially mean-square stable with prescribed ${H_\infty }$ performance are obtained by using Lyapunov stability theory. Furthermore, criteria for simultaneously designing the weighting matrix in event-triggered scheme and the controller gain matrix are derived by utilizing the linear matrix inequality technique. Finally, a three-area power system is simulated to demonstrate the usefulness of the approaches proposed in this paper.

On the Inertia of Future More-Electronics Power Systems

Abstract: Inertia plays a vital role in maintaining the frequency stability of power systems. However, the increase of power electronics-based renewable generation can dramatically reduce the inertia levels of modern power systems. This issue has already challenged the control and stability of small-scale power systems. It will soon be faced by larger power systems as the trend of large-scale renewable integration continues. In view of the urgent demand for addressing the inertia concern, this paper presents a comprehensive review of inertia enhancement methods covering both proven techniques and emerging ones and also studies the effect of inertia on frequency control. Among those proven techniques, the inertia emulation by wind turbines has successfully demonstrated its effectiveness and will receive widespread adoptions. For the emerging techniques, the virtual inertia generated by the dc-link capacitors of power converters has a great potential due to its low cost. The same concept of inertia emulation can also be applied to ultracapacitors. In addition, batteries will serve as an alternative inertia supplier, and the relevant technical challenges as well as the solutions are discussed in this paper. In future power systems where most of the generators and loads are connected via power electronics, virtual synchronous machines will gradually take over the responsibility of inertia support. In general, it is concluded that advances in semiconductors and control promise to make power electronics an enabling technology for inertia control in future power systems.

Comparative Review of Energy Storage Systems, Their Roles, and Impacts on Future Power Systems

Abstract: It is an exciting time for power systems as there are many ground-breaking changes happening simultaneously. There is a global concensus in increasing the share of renewable energy-based generation in the overall mix, transitioning to a more environmental-friendly transportation with electric vehicles as well as liberalizing the electricity markets, much to the distaste of traditional utility companies. All of these changes are against the status quo and introduce new paradigms in the way the power systems operate. The generation penetrates distribution networks, renewables introduce intermittency, and liberalized markets need more competitive operation with the existing assets. All of these challenges require using some sort of storage device to develop viable power system operation solutions. There are different types of storage systems with different costs, operation characteristics, and potential applications. Understanding these is vital for the future design of power systems whether it be for short-term transient operation or long-term generation planning. In this paper, the state-of-the-art storage systems and their characteristics are thoroughly reviewed along with the cutting edge research prototypes. Based on their architectures, capacities, and operation characteristics, the potential application fields are identified. Finally, the research fields that are related to energy storage systems are studied with their impacts on the future of power systems.

A Review of Power System Flexibility With High Penetration of Renewables

Abstract: The notion of secure operation of power systems, with its present semantic, dates back to the last decade. Since then, tremendous research effort has investigated secure operation of the power system. Nevertheless, operators are still faced with security issues, with even larger uncertainty, however, caused by the integration of renewable energy sources (RES). The system's ability to cope with the volatility of RES and load becomes a critical issue in power system operation. This paper surveys the literature on the concepts of power system flexibility, indices of flexibility, and implementation of the concept of flexibility in power system security. The paper proceeds to review the origin of the reserve problem, the meaning of reserve, its technical classification and related economical aspects. The paper highlights the effect of renewables on these aspects, and suggests new research directions.

A Survey of Relaxations and Approximations of the Power Flow Equations

Abstract: The power flow equations model the relationship between voltage phasors and power injections at nodes (buses) in an electric power system and are fundamental in their analysis and operation. A wealth of literature exists on these equations, many providing different representations of them. This monograph provides the first comprehensive survey of representations in the context of optimization. To achieve this the power flow representations surveyed are categorized as either relaxations or approximations. The techniques described in here form the basis of running an optimally efficient modern day power system. A Survey of Relaxations and Approximations of the Power Flow Equations is a must-read for all students and researchers working on the cutting edge of electric power systems.

Power systems with high renewable energy sources: A review of inertia and frequency control strategies over time

Abstract: Traditionally, inertia in power systems has been determined by considering all the rotating masses directly connected to the grid. During the last decade, the integration of renewable energy sources, mainly photovoltaic installations and wind power plants, has led to a significant dynamic characteristic change in power systems. This change is mainly due to the fact that most renewables have power electronics at the grid interface. The overall impact on stability and reliability analysis of power systems is very significant. The power systems become more dynamic and require a new set of strategies modifying traditional generation control algorithms. Indeed, renewable generation units are decoupled from the grid by electronic converters, decreasing the overall inertia of the grid. ‘Hidden inertia’, ‘synthetic inertia’ or ‘virtual inertia’ are terms currently used to represent artificial inertia created by converter control of the renewable sources. Alternative spinning reserves are then needed in the new power system with high penetration renewables, where the lack of rotating masses directly connected to the grid must be emulated to maintain an acceptable power system reliability. This paper reviews the inertia concept in terms of values and their evolution in the last decades, as well as the damping factor values. A comparison of the rotational grid inertia for traditional and current averaged generation mix scenarios is also carried out. In addition, an extensive discussion on wind and photovoltaic power plants and their contributions to inertia in terms of frequency control strategies is included in the paper.

A survey on control issues in renewable energy integration and microgrid

Abstract: This paper describes the usefulness of renewable energy throughout the world to generate power. Renewable energy adds a remarkable scope in power system. Renewable energy sources act as the prime mover of a microgrid. The Microgrid is a small network of power system with distributed generation (DG) units connected in parallel. The integration challenges of renewable energy sources and the control of microgrid are described in this paper. The varied nature of DG system produces voltage and frequency deviation. The unknown nature of the load produces un-modeled dynamics. This un-modeled dynamic introduces measurable effects on the performance of the microgrid. This paper investigates the performance of the microgrid against different scenarios. The voltage of the microgrid is controlled by using different controllers and their results are also investigated. The performance of controllers is investigated using MATLAB/Simulink SimPowerSystems.

Placement and Implementation of Grid-Forming and Grid-Following Virtual Inertia and Fast Frequency Response

Abstract: The electric power system is witnessing a shift in the technology of generation. Conventional thermal generation based on synchronous machines is gradually being replaced by power electronics interfaced renewable generation. This new mode of generation, however, lacks the natural inertia and governor damping, which are quintessential features of synchronous machines. The loss of these features results in increasing frequency excursions and, ultimately, system instability. Among the numerous studies on mitigating these undesirable effects, the main approach involves virtual inertia (VI) emulation to mimic the behavior of synchronous machines. In this paper, explicit models of grid-following and grid-forming VI devices are developed for inertia emulation and fast frequency response in low-inertia systems. An optimization problem is formulated to optimize the parameters and location of these devices in a power system to increase its resilience. Finally, a case study based on a high-fidelity model of the South-East Australian system is used to illustrate the effectiveness of such devices.

Grid-Forming Inverters: Are They the Key for High Renewable Penetration?

Abstract: In regions such as hawai'i, south australia, Tasmania, Texas, and Ireland, power systems are commonly experiencing instantaneous penetration levels of inverter-based power sources (IBPSs) such as wind, solar photovoltaics (PV), and battery storage in excess of 50n60% relative to system demands.

A Model Combining Convolutional Neural Network and LightGBM Algorithm for Ultra-Short-Term Wind Power Forecasting

Abstract: The volatility and uncertainty of wind power often affect the quality of electric energy, the security of the power grid, the stability of the power system, and the fluctuation of the power market. In this case, the research on wind power forecasting is of great significance for ensuring the better development of wind power grids and the higher quality of electric energy. Therefore, a lot of new forecasting methods have been put forward. In this paper, a new forecasting model based on a convolution neural network and LightGBM is constructed. The procedure is shown as follows. First, we construct new feature sets by analyzing the characteristics of the raw data on the time series from the wind field and adjacent wind field. Second, the convolutional neural network (CNN) is proposed to extract information from input data, and the network parameters are adjusted by comparing the actual results. Third, in consideration of the limitations of the single-convolution model in predicting wind power, we innovatively integrated the LightGBM classification algorithm at the model to improve the forecasting accuracy and robustness. Finally, compared with the existing support vector machines, LightGBM, and CNN, the fusion model has better performance in accuracy and efficiency.

Transient Angle Stability of Virtual Synchronous Generators Using Lyapunov’s Direct Method

Abstract: With an increasing number of distributed energy resources integrated into the power system, inverters need to take on the corresponding responsibility for the security and stability of the system. Virtual synchronous generators (VSGs) are proposed to mimic dynamic characteristics of traditional rotational synchronous generators (RSGs) to compensate for the loss of inertia and reserve capacity. Similar to RSGs, VSGs will experience transient angle instability under certain conditions, which likely threatens the system security. In this paper, transient angle stability of a VSG is investigated by Lyapunov’s direct method. The deteriorative effect of reactive power control loop on transient angle stability is first analyzed and then voltage variation is incorporated into an approximate Lyapunov’s direct method. In this method, the inverter internal voltage is treated as a parameter rather than a state variable. Moreover, the influence of different parameters on transient angle stability is studied. Finally, an enhanced control strategy is presented to improve the transient angle stability by adjusting the reference power. Numerical simulation results are presented to validate the effectiveness of the proposed method and the enhanced control.

Review on the optimal placement, sizing and control of an energy storage system in the distribution network

Abstract: Energy storage system (ESS) has developed as an important element in enhancing the performance of the power system especially after the involvement of renewable energy based generation in the system. However, there are a few challenges to employ ESS in distribution network, one of which is to ensure the best location and capacity so as to take the full advantage of installing ESS in the grid. In this paper, an extensive literature review on optimal allocation and control of ESS is performed. Besides, different technologies and the benefits of the ESS are discussed. Some case studies of ESS application in different part of the world are also presented. Finally, this paper emphasizes the future improvement of ESS control and performance to solve more complicated problems originated from the participation of renewable energy generation in the power system.

From demand response to integrated demand response: review and prospect of research and application

Abstract: In the traditional power system demand response, customers respond to electricity price or incentive and change their original power consumption pattern accordingly to gain additional benefits. With the development of multi-energy systems (MES) in which electricity, heat, natural gas and other forms of energy are coupled with each other, all types of energy customers are able to participate in demand response, leading to the concept of integrated demand response (IDR). In IDR, energy consumers can response not only by reducing energy consumption or opting for off-peak energy consumption but also by changing the type of the consumed energy. Taking the traditional demand response in power system as a starting point, the studies of the fundamental theory, framework design and potential estimation of demand response in power system are reviewed, and the practical cases and software development of demand response are introduced. Finally, the current theoretical research and application of IDR are assessed.

Impact of distributed generation on protection and voltage regulation of distribution systems: A review

Abstract: During recent decades with the power system restructuring process, centralized energy sources are being replaced with decentralized ones. This phenomenon has resulted in a novel concept in electric power systems, particularly in distribution systems, known as Distributed Generation (DG). On one hand, utilizing DG is important for secure power generation and reducing power losses. On the other hand, widespread use of such technologies introduces new challenges to power systems such as their optimal location, protection devices' settings, voltage regulation, and Power Quality (PQ) issues. Another key point which needs to be considered relates to specific DG technologies based on Renewable Energy Sources (RESs), such as wind and solar, due to their uncertain power generation. In this regard, this paper provides a comprehensive review of different types of DG and investigates the newly emerging challenges arising in the presence of DG in electrical grids.