Enhancing resilience of low-inertia power systems through a novel load shedding method with synchronous condenser power control

Modern power systems require fast and effective load shedding to maintain frequency stability and enhance resilience, especially during disturbances. Traditional load shedding methods suffer from several shortcomings, including slow computational time and negligence of load shedding priorities. To address these challenges, this paper introduces a novel load shedding approach based on frequency prediction and deep reinforcement learning. First, a dynamic frequency response model of the power system is constructed. This model imitates the dynamic frequency response of the power system through the transfer function, and based on this, the dynamic frequency response indices including the steady-state frequency difference and maximum frequency difference can be calculated. Then, a deep Q network (DQN) based load shedding method is presented through designing DQN parameters including DQN state, action, reward function, and training method. Finally, the empirical analysis indicates that the proposed method can achieve a lower frequency nadir and smaller maximum frequency difference than the method based on real-time frequency measurement. Moreover, relative to the model-based method, the proposed method provides faster decision-making speed, contributing positively to system frequency stability and enhancing the resilience of power systems against disturbances.

The increasingly frequent extreme events pose a serious threat to the resilience of the power system. At the same time, the power grid is transforming into a new type of clean and low-carbon power system due to severe environmental issues. The system shows strong randomness with a high proportion of renewable energy, which has increased the difficulty of maintaining the safe and stable operation of the power system. Therefore, it is urgent to improve the resilience of the new power system. This paper first elaborates on the concept of power system resilience, listing the characteristics of new power systems and their impact on grid resilience. Secondly, the evaluation methods for resilient power grids are classified into two categories, and measures to improve the resilience of the new power system are reviewed from various stages of disasters. Then, the critical technologies for improving the resilience of the new power system are summarized. Finally, the prospective research directions for new power system resilience enhancement are expounded.

Grid‐interactive converters with primary frequency control and inertia emulation have emerged and are promising for future renewable generation plants because of the contribution in power system stabilisation. This study gives a synchronous active power control solution for grid‐interactive converters, as a way to emulate synchronous generators for inerita characteristics and load sharing. As design considerations, the virtual angle stability and transient response are both analysed, and the detailed implementation structure is also given without entailing any difficulty in practice. The analytical and experimental validation of frequency support characteristics differentiates the work from other publications on generator emulation control. The 10 kW simulation and experimental frequency sweep tests on a regenerative source test bed present good performance of the proposed control in showing inertia and droop characteristics, as well as the controllable transient response.

DC-side synchronous active power control of two-stage photovoltaic generation for frequency support in Islanded microgrids

Power system resilience and strategies for a sustainable infrastructure: A review

Power systems serve social communities that consist of residential, commercial, and industrial customers. As a result, the disaster resilience of a power system should account for social community resilience. The social behavior and psychological features of all stakeholders involved in a disaster influence the level of power system preparedness, mitigation, recovery, adaptability, and resilience. Hence, there is a need to consider the social community's effect on the power system and the dependence between them in determining a power system's resilient to human-made and natural hazards. The social community, such as a county, city, or state, consists of various stakeholders, e.g., social consumers, social prosumers, and utilities. In this paper, we develop a multi-dimensional output-oriented method to measure resilience. The three key ideas for measuring power system resilience are the multi-dimensionality, output-oriented, and degraded functionality aspects of the power system. To this end, we develop an artificial society based on neuroscience, social science, and psychological theories to model the behavior of consumers and prosumers and the interdependence between power system resilience, comsumer and prosumer well-being, and community capital. Both mental health and physical health are used as metrics of well-being, while the level of cooperation is used to measure community capital resilience.

In recent years, deep reinforcement learning (DRL) has garnered substantial attention in the context of enhancing resilience in power and energy systems. Resilience, characterized by the ability to withstand, absorb, and quickly recover from natural disasters and human-induced disruptions, has become paramount in ensuring the stability and dependability of critical infrastructure. This comprehensive review delves into the latest advancements and applications of DRL in enhancing the resilience of power and energy systems, highlighting significant contributions and key insights. The exploration commences with a concise elucidation of the fundamental principles of DRL, highlighting the intricate interplay among reinforcement learning (RL), deep learning, and the emergence of DRL. Furthermore, it categorizes and describes various DRL algorithms, laying a robust foundation for comprehending the applicability of DRL. The linkage between DRL and power system resilience is forged through a systematic classification of DRL applications into five pivotal dimensions: dynamic response, recovery and restoration, energy management and control, communications and cybersecurity, and resilience planning and metrics development. This structured categorization facilitates a methodical exploration of how DRL methodologies can effectively tackle critical challenges within the domain of power and energy system resilience. The review meticulously examines the inherent challenges and limitations entailed in integrating DRL into power and energy system resilience, shedding light on practical challenges and potential pitfalls. Additionally, it offers insights into promising avenues for future research, with the aim of inspiring innovative solutions and further progress in this vital domain.

Reliability and resilience are the core principles of power system planning and operations around the world. Power systems in South Asia are transforming with increasing penetration of clean energy generation resources, emerging technologies, increasing electricity demand and electrification. At the same time, these power systems are facing challenges posed by extreme weather events and climate change. All these factors would add furthermore importance to the reliability and resilience of future power systems in South Asia. This has motivated us to better understand the country specific challenges and chalk out the pathways for research, modelling and implementation in South Asia. Our research, experience in the region and feedback from key stakeholders indicate following as the key areas where more work is needed to improve reliability and resilience of power systems in the region: Renewable energy Data for power system studies, New Tools and Studies, Resilience Planning, Resource Adequacy, Advanced RE Forecasting, Cybersecurity, Load Forecasting, and Coordinated Planning and Operations.

The increasing penetration of renewable energy sources and the retirement of conventional generation units have decreased system inertia, making power systems more vulnerable to resilience and stability issues. To address this problem, this paper proposes a novel approach using grid‐supportive loads (GSLs) to provide a fast and concise primary frequency response and a deep deterministic policy gradient agent‐based secondary controller to restore the system frequency to the nominal value. The proposed method is evaluated on the single‐area and multi‐area test systems. The simulation results demonstrate that using GSLs enhances the power system's stability and resilience. Compared to conventional controllers, the frequency nadir is improved with GSLs. Additionally, the proposed method effectively enhances resilience even with high penetration. These findings indicate that the proposed approach can improve the resilience and stability of power systems and provide a promising solution for future power systems. The results of this study underscore the importance of utilizing innovative approaches to enhance the stability and resilience of power systems in the context of high penetration of renewable energy sources and the retirement of conventional generation.

Resilience-economy-environment equilibrium based configuration interaction approach towards distributed energy system in energy intensive industry parks

Adaptive transmit power control in 802.11 wireless LANs (WLANs) on a per-link basis helps increase network capacity and improves battery life of WiFi-enabled mobile devices. However, it faces the following challenges: 1) it can exacerbate receiver-side interference and asymmetric channel access; 2) it can incorrectly lead to lowering the data rate of a link; 3) mobility-induced channel variations at short timescales make detecting and avoiding these problems more complex. Despite substantial prior research, state-of-the-art solutions lack comprehensive techniques to address the above problems. In this paper, we design and implement Symphony, a synchronous two-phase rate and power control system whose agility in adaptation enables us to systematically address the three problems while maximizing the benefits of power control on a per-link basis. We implement Symphony in the Linux MadWifi driver and show that it can be realized on hardware that supports transmit power control with no modifications to the 802.11 MAC, thereby fostering immediate deployability. Our extensive experimental evaluation on a real testbed in an office environment demonstrates that Symphony : 1) enables up to 80% of the clients in three different cells to settle at 50%-94% lower transmit power than a per-cell power control solution; 2) increases network throughput by up to 50% across four realistic deployment scenarios; 3) improves the throughput of asymmetry-affected links by 300%; and 4) opportunistically reduces the transmit power of mobile clients running VOIP calls by up to 97% while only causing a negligible degradation of voice quality.

The electric power system is one of the most vital infrastructures, and its security is necessary for the proper functioning of society. The main goal for the electric power system has traditionally been continuity of the electrical power supply. However, in addition to this requirement, power systems must follow the requirements associated with vulnerability and resilience. Vulnerability deals with the assessment of risk, as it relates to physical and economic consequences, arising from the capability of the network to handle an undesirable incident. Resilience deals with the network capability to withstand unknown disturbances, and consequently, the ability to restore stable operating conditions. Despite some research on power system resilience and vulnerability, their basic concepts are still unexplored. This paper aims to discuss the essential concepts of vulnerability and resilience in electric power systems. Their assessment frameworks and quantification metrics are also described. Case studies, on standard test systems, to demonstrate the assessment of power system vulnerability and resilience, are also part of this research.

This research aims to maximize the resilience of an electrical power system after an N−1 contingency, and this objective is achieved by switching the transmission lines connection using a heuristic that integrates optimal dc power flows (DCOPF), optimal transmission switching (OTS) and contingencies analysis. This paper’s methodology proposes to identify the order of re-entry of the elements that go out of the operation of an electrical power system after a contingency, for which DCOPF is used to determine the operating conditions accompanied by OTS that seeks to identify the maximum number of lines that can be disconnected seeking the most negligible impact on the contingency index J. The model allows each possible line-switching scenario to be analyzed and the one with the lowest value of J is chosen as the option to reconnect, this process is repeated until the entire power system is fully operational. As study cases, the IEEE 14, 30 and 39 bus bars were selected, in which the proposed methodology was applied and when the OTS was executed, the systems improved after the contingency; furthermore, when an adequate connection order of the disconnected lines is determined, the systems are significantly improved, therefore, the resilience of power systems is maximized, guaranteeing stable, reliable and safe behavior within operating parameters.

Nowadays, the grid-forming inverter, also referred as the voltage-controlled inverter, has gained greater attention due to its advantages in providing power support to the grid. The power control is central to grid-forming inverters in realizing grid-support functionalities, such as the droop control or virtual inertia emulation. However, in these controls, the dynamic response of the instantaneous power usually suffers from overshoots and oscillations. To improve the dynamic response of the injected instantaneous power, this letter introduces a novel synchronous active power control for the voltage-controlled grid-connected inverter. The droop coefficient can be released from adjusting the damping factor of the system. A novel design method is proposed to reduce the second-order power loop to a first-order model. Consequently, the droop and reference-following controls operate like a first-order system with an excellent dynamic response. Moreover, the virtual inertia can be designed freely without affecting the performance of the power control. The correctness of the control is verified experimentally.

Microgrid-based operational framework for grid resiliency enhancement: A case study at KUET campus in Bangladesh