Construction of Automatic Scheduling and Visualization System for Power Grid Space Operation Based on Reinforcement Learning Algorithm

Electric power has become an essential part of daily life: we plug our electronic devices in, switch our lights on, and expect to have power. As the availability of power is usually taken for granted in modern societies, we mostly feel annoyed at its absence and perceive the importance of power during outages which have severe effects on the public order. Blackouts have had disastrous consequences for many countries and they continue to occur frequently. Such examples demonstrate the necessity for careful analysis and planning of power grids, to ultimately increase the reliability of power grids. The power grids have evolved due to economic, environmental and human-caused factors. In addition to the contingency analysis, nowadays, the operation and planning of power grids are facing many other challenges (such as demand growth, targeted attacks, cascading failures, and renewable energy integration). Thus, many questions arise, including: which buses (nodes) to connect with a new line (link)? What are the impacts of malicious attacks on power grids? How may an initial failure result in a cascade of failures? How to prepare for the integration of renewable energy? Answering such questions requires developing new concepts and tools for analysing and planning of power grids. Power grids are one of the largest and the most complex man-made systems on earth. The complex nature of power grids and its underlying structure make it possible to analyse power grids relying on network science. The applications of network science on power grids have shown the promising potential to capture the interdependencies between components and to understand the collective emergent behaviour of complex power grids. This thesis is motivated by the increasing need of reliable power grids and the merits of network science on the investigation of power grids. In this context, relying on network science, we model and analyse the power grid and its near-future challenges in terms of line removals/additions, malicious attacks, cascading failures, and renewable integration.

With the UHV (Ultra High Voltage) power grid construction and the interconnection of regional power grids, the scale of power grids in China is increasing rapidly. At the same time, significant uncertainty and variability is being introduced into power grid operation with the integration of large-scale renewable energy in power systems. All of these pose an enormous challenge to the operation control of power systems in China. For a long time, online static security analysis, as an important part of EMS (Energy Management System), has been an effective tool for power grid operation. However, it is increasingly difficult for traditional static security analysis in serial computing mode to be online applied in bulk power grids in China. A new practical parallel approach for online static security analysis is put forward in this paper. A multithread parallelism is introduced into contingency screening, detailed contingency evaluation and decision support for reducing the execution time. By employing the multithread technology, the hardware resources of multi-processor/multi-core computer can be fully used and the program can be speeded up effectively. The performance of the parallel static security analysis is demonstrated by tests on two large-scale power systems. The test results show that the proposed method can be online applied in real bulk power grids.

To systematically analyze the impact of the DC frequency limit controller (FLC) configuration scheme on the frequency characteristics of asynchronous interconnected power grids with renewable energy integration, a comprehensive frequency analysis model for three-area asynchronous interconnected power grids including the FLC is proposed. The model is based on the SFR model considering renewable energy integration and includes a simplified model of the DC FLC. A rigorous validation of the rationality and stability of the model is achieved through detailed mathematical calculations and pole-zero analysis. Taking the local power grids as an example, the established model is used to study the difference between single- and double-sided configuration of the DC FLC, the relationship between the increase in the renewable energy penetration rate and the frequency characteristics of each regional power grid, and the influence of DC FLC configuration on the maximum acceptance ratio of renewable energy. Through data comparison and theoretical analysis, the influence of FLC configuration on the frequency characteristics of each region of the asynchronous power grid under renewable energy integration is obtained. The results show that the configuration of a bilateral FLC on the DC line has more advantages in alleviating the complementary power disturbance at both ends and obvious limitations on the non-complementary power disturbance at both ends. Compared with the configuration of the bilateral FLC, the configuration of a unilateral FLC on the weak grid has a larger proportion of renewable energy acceptance. When the DC FLC power transmission capacity is sufficient, the weak grid and the adjacent two asynchronous grid DC tie lines are configured with a single-sided FLC, and the weak grid is theoretically connected to the renewable energy penetration rate of up to 100%.

Affected by the north of the Jianghuai cyclone on November 17,2020, a rare rain and snow freezing weather occurred in Jilin Province, which is the largest and widest range of rainstorm, snowstorm, freezing rain and gale disaster weather since its own meteorological records. This paper provides a reference and basis for future power grid planning, design and operation, and maintenance of disaster prevention and mitigation by analyzing the causes of this weathering process and its impact on power grid operation.

Power grid anomaly detection is a basic task of the power system, and the evaluation results are of great significance for the power grid to find out the potential dangers of operation as soon as possible and take timely measures to prevent them from happening. In recent years, with the rapid development of green energy and high technology, the power grid is developing towards the smart grid. A large number of measurement devices are deployed in the power grid, and the power grid operation data is collected, transmitted and analyzed in real time. The data-driven power big data analysis approach emerges as the times require. In this paper, a data-driven approach is proposed. It constructs a high-dimensional random matrix based on power system operating data, uses the sliding window method and the random matrix single-ring theorem to continuously analyze the high-dimensional matrix, and introduces the mean spectral radius (MSR) as a specific evaluation index to realize the power grid operation situation assessment. The simulation data test results of IEEE 39 bus system verifies the feasibility and correctness of the approach for evaluating the operation situation of the power grid. This developed approach can identify abnormal conditions at the early stage of system failure, and has great guiding significance for fault inspection of power grids.

Generative artificial intelligence (AI) has captured into the mainstream, demonstrating capabilities that once belonged solely to the realm of human cognition. From defeating world champions in complex games to generating human-quality text and images, Generative AI has proven its potential to revolutionize countless industries. The electric power grid is no exception. Generative AI's ability to process vast amounts of data rapidly, assist decision support and identify patterns could significantly enhance power grid operations. For example, Generative AI could improve state estimation where measurements are not available or integrate renewable energy sources more efficiently with probabilistic forecasting. The key contributions of this whitepaper are outlined below: (1) Comprehensive overview of Generative AI's applications in power grid operations: It highlights the opportunities in areas such as forecasting, state estimation, and demonstrating the potential for enhancing efficiency, reliability, and resilience. (2) Expanding Generative AI's impact through synergies with emerging technologies: The paper introduce NREL developed eGridGPT and explores how AI orchestration, multi-agent systems, and Digital Twins can collaborate to optimize grid operations, addressing the complexities of a decarbonized and electrified future. (3) In-depth analysis of challenges in implementing Generative AI: This includes considerations like data availability and quality, model validation, certification, and ethical concerns, ensuring responsible AI deployment. (4) Emphasizing human-AI collaboration: The whitepaper underscores the importance of trustworthy, transparency, and explainability in AI systems to promote seamless interaction between human operators and AI, ultimately improving decision-making. (5) Exploring future research and development: It identifies critical areas for further advancement to fully realize Generative AI's potential in power grid operations. This whitepaper serves as a valuable resource for researchers, practitioners, and policymakers looking to harness Generative AI for a more reliable, stable, and cost-effective power grid.

When the power grid is disturbed to a certain degree, it may be extremely deteriorated. At this time, corresponding control measures need to be taken to eliminate or reduce the risks. For an unsafe normal state, the system can be restored to a safe state through preventive control. This paper proposes a risk-based power grid operational control strategy by using the optimal power flow method to solve the problem of power grid operational control based on risk parameters with the goal of minimizing the power grid operating risks. Under the condition of satisfying steady-state operational constraints, by adjusting the control measures that can be used in the system, such as active power generation, the safe operational state of the system with the least operational risk is realized. To avoid the poor effectiveness of alternating current power flow of large power grid, linearized power flow model is employed. Simulation results using an IEEE 118-node system and East China Power Grid system. The proposed operational control strategy can achieve the effect of eliminating or reducing operating risks, which provide effective decision-making for the dispatch operators to deal with risks.

The now ubiquitous use of information technology poses a crucial challenge to the cyber security of power grid operations, one that has aroused serious concerns from both industry and academia. The state-of-the-art research either focuses on the vulnerability assessment of particular types of components or concentrates on the prevention and mitigation of cyber attacks from the power grid’s perspective. Complete causal chains connecting component vulnerabilities to cyber attacks causing malicious system-wide effects are unclear, which hinders cyber-attack prevention and the consolidation of affected components. To bridge this research gap, this survey aims to study two issues that need further investigation. On one hand, the causal relationship between power grid component vulnerabilities and resulting cyber attacks has not been thoroughly explored. On the other hand, the evolvement of cyber attacks, from initial attempt to resulting serious consequences has not been resolved. To study these two issues, we first analyze various stakeholders and associated information flows in diverse applications in power grid operation. Second, we summarize the root cause of cyber attacks in the vulnerability of communication protocols. Third, a multi-stage model is proposed to describe the cyber vulnerabilities, which reveals potential attacks and their evolvement on power grid components at each stage, assesses the associated impact on the entire power grid, and elucidates possible countermeasures. With the above efforts, this survey establishes a complete causal chain from component-wise vulnerability to system-wide impact assessment for enhancing cyber security, and potential research directions for enhancing power grid cyber security are identified.

Due to the weak support of renewable energy power generation equipment, the voltage support capacity after connecting to the power grid is difficult to meet the needs of safe operation of the power grid. Especially when large-scale renewable energy units, DC transmission and other power equipment are connected to the power system, the problem of transient overvoltage has become the main factor restricting the transmission of renewable energy. By configuring the condenser, the power grid voltage support strength can be effectively improved and the output limit of renewable energy can be improved. However, in the actual production and operation of power grid, there is not only a lack of quantitative analysis and research on improving the transmission capacity of renewable energy, but also a lack of technical and economic analysis methods for the configuration of condenser. Therefore, based on the quantitative evaluation of MRSCR on the power grid voltage support strength, through the joint calculation of PSD-BPA software and production simulation model, this study quantitatively analyzes the impact on the renewable energy consumption capacity after the distributed dimmer is connected to the system, and quantitatively evaluates the technical economy of configuring the dimmer in the renewable energy collection station by constructing the technical economy model of the dimmer. The results show that the condenser can not only improve the transmission capacity of renewable energy, but also have good economic benefits.

The renewable energy sources such as wind power and solar energy are widely connected to the current power network. The proportion of the renewable resources to the entire energy sources in the power grid is increasing. Since wind power and solar energy are intermittent, which have more uncertain factors, power grid operation is being impacted by generation of the renewable energy sources. Especially in the area of power balance and dispatch. Severe power imbalance, which causes the huge frequency deviation, will lead to the stability of power system. Therefore, it is very important to deal with the uncertainties of renewable energy. The existing deterministic approaches are not sufficient to deal with the uncertain factors. This paper analyzes the effect of renewable energy uncertainties in power grid operation based on the fuzzy theory and probabilistic methods. The steady-state security analysis is taken as an example to handle renewable energy uncertainty in power grid operation.

Wind turbines are increasingly connected to the bulk power grid through electronic devices. Compared with the dynamic characteristics of traditional power system, transient characteristics are dramatically changed. Recognizing the transient characteristics of large-scale wind power connected to the bulk power grid and proposing practical and feasible transient control strategies for wind turbines are important to the safe and stable operation of current power grid. This paper focuses on the interactive characteristics of double-fed induction generator (DFIG) coupled to the power grid of receiving-end. A DFIG-based wind farm can be reduced to a single DFIG wind turbine by simplifying it, transient dynamics of the wind turbine, such as output fault current characteristics, under different fault levels of power grid are analyzed. Moreover, according to the fault ride through (FRT) standard of wind farms, FRT control strategies of DFIG wind turbines under different fault levels of power grid are presented to form a coordinated fault ride-through control scheme. Finally, a case study was conducted with MATLAB/Simulink. The simulation results verified the effectiveness and feasibility of the interactive characteristics analysis and the proposed FRT control scheme of DIFG-based wind farms connected to the receiving power grid.

Hurricane Sandy and other recent extreme weather events, which have caused significant service interruptions including power outages, have revealed that our power grid is not sufficiently planned and operated to be resilient to large-scale events. Power grid resilience is a generic term that covers many aspects of power grid planning and operation. A resilient power grid should be capable of executing preventive measures, mitigating the impact of extreme events, responding optimally by automated control procedures, reducing the time needed to restore service to consumers, and potentially leading to significant economic savings. In addition, due to the growing usage of information and communication technologies (ICT), power grids are being increasingly exposed to cyber attacks. The recent blackout in Ukraine serves as a good example to illustrate the severe consequence that cyber attacks on the power grid can entail. Extensive reports and media coverage indicate the urgency to improve our power grid resilience. Maintaining resilience of the power grid is crucial to our nation’s energy security and sustainability.

The smart grid moves new power grid automation systems from being proprietary and closed to the current state of information technology (IT) which is highly interconnected and open. But open and interconnected automation platforms bring about major security challenges. The power grid automation network has inherent security risks due to the fact that the systems and applications for the power grid were originally designed without much consideration of cybersecurity. This paper first introduces scope and functionalities of power grid, its automation and control system, and communications. Potential cyberattacks and their adverse impacts on power grid operation are discussed, a general SCADA cyberattack process is presented. This paper discusses the major challenges and strategies to protect smart grid against cyberattacks and finally proposes a conceptual layered framework for protecting power grid automation systems against cyberattacks without compromising timely availability of control and signal data. The proposed “bump-in-the-wire” approach also provides security protection for legacy systems which do not have enough computational power or memory space to perform security functionalities. The on-site system test of the developed prototype security system is briefly presented as well.

In recent years, with the deepening of smart grid construction, the data generated by power grid operation have increased rapidly, and the power grid big data environment has gradually formed. The power grid data management based on graph data has gained more and more attention, and its efficient storage and processing have become a research hotspot. In this paper, a subgraph partitioning algorithm for power grid graph data is developed. The power grid graph data are partitioned into multiple subgraphs, and then a parallel topology analysis algorithm for multiple subgraphs is proposed. Related experiments show that the parallel analysis scheme of power grid graph data is effective and meets the actual needs of power grid graph data.

The construction and operation of the ultrahigh voltage power grid has solved the problem of optimal allocation of energy resources and played a key role in promoting social development. However, concerns about its safety have kept growing in recent years. In order to analyze the reliability of ultrahigh voltage AC/DC system combined with the quasi-Monte Carlo method and PSD-BPA simulation, the reliability model of various components and system is established, and the simulation speed is improved with accuracy ensured. In order to ensure the compatibility and efficiency of the software, we design the BPA-Matpower data interface, and the data translation from BPA to Matpower is realized by fourth conversion. Then, we propose an index system for reliability evaluation, concise and easy to compute, to reflect the reliability of the UHV grids and the characteristics of AC and DC systems. Based on actual regional powergrid, we compare the model in this paper with the traditional sequential Monte Carlo method, and carry out the analysis of the component sensitivity to study the multi-fault characteristics and the weakness of the system, and verify the scientific and effective result of this paper.