Resilience assessment of a power system due to disruption of interconnectors

High integration of photovoltaic (PV) systems into the power systems causes negative or positive impacts. Typically, research considers the PV impacts on the RMS voltage, power losses, transformers and feeder stress, and power quality indicators. However, a generalising assessment of the electrical parameters and indicators (P&I) describes the power grid performance. It considers a complete holistic view of the real impacts that many events cause over the power grid operation. Therefore, this research proposes the resilience index in order to quantify and assess the impacts that the PV systems cause in low voltage. This scheme has four stages: i) P&I measurement, ii) P&I normalisation, iii) P&I weights assignment, and iv) resilience index quantification and assessment. The resilience scheme assessment has been applied in a low voltage university building with a PV system interconnected of 11.53 kWp. Monitoring has lasted for a month, with data acquisition every ten minutes. P&I monitored have been RMS voltage, RMS current, active, and non-active power, voltage imbalance, total harmonic distortion of voltage and current, and harmonic components of voltage and current. Results indicate that the PV system has positively affected the resilience index in the point of common coupling and floor four-node because the THDv, Vh, THDi, and Ih improved.

The cyber-physical deep coupling makes power systems face more risks under small-probability and high-risk typhoon disasters. Resilience describes the ability of cyber-physical power system (CPPS) withstanding extreme disasters and resuming normal operation. To improve the resilience assessment and analysis method of CPPS, first, a CPPS resilience assessment framework that considers the space-time metrics of disasters and the interactions of information systems and power grids is proposed, including fault scenarios extraction, response and recovery analysis, quantitative assessment of resilience. Second, from the perspective of the geographical coupling between OPGW and transmission lines and the control coupling between automatic generation control system (AGC), substation automation system (SAS) and power system, the interaction of information flow and energy flow during the failure period is analyzed. The network flow theory is used to establish an information network traffic model to describe the operating status of the information system at each stage. On this basis, a mixed integer linear programming model for DC optimal power flow considering the information network constraints and a multi-stage bi-level model for cyber-physical collaborative recovery are established. Finally, we take the IEEERTS-79 system as an example to show that the proposed method can improve the quantization accuracy comparing with the assessment method of the conventional power system, and evaluate the enhancement of typical measures at different stages.

The secure operation of the renewable-integrated power system is affected by extreme weather conditions such as typhoons. In order to meet the operational requirements of the system, it is necessary to dynamically evaluate the resilience of the renewable-integrated power systems based on meteorological forecast information to guide operators to make reasonable risk prevention and control decisions. A rapid assessment method for power system resilience is proposed to address the uncertainty of extreme weather caused by typhoons. First, with a focus on the impact of typhoon disasters on power system components, corresponding failure probability models are constructed by taking typhoon meteorological forecast information as input and considering the uncertainty of typhoon meteorological forecast. Error probability circles and average absolute errors of intensity forecasts are included in the sampling of typhoon scenarios. Second, for the resilience assessment process, the impact increment method is used to reduce the dimensionality of multiple fault state analysis in the power system, and resilience indexes are calculated by screening the contingency set based on depth-first traversal through a backtracking algorithm. The weak links in the power system are identified through sensitivity analysis of load loss. Finally, the effectiveness of the proposed method is verified using the modified IEEE RTS-79 power system.

The consequence of increasing the use of large amount of renewable non programmable generation capability (wind and PV systems) as well as extreme weather events or, more in general, changing environmental conditions, will have significant impacts on future power systems, in particular on the power system adequacy and on the resiliency assessment. Climate change has changed and will continue to affect both the energy demand and the available generation capacity. For instance, high demand for extreme heat or cold phenomena can determine the presence of critical operating conditions from the point of view of power system adequacy. Meteorological variables, therefore, are essential inputs to study key dimensions that must be kept under close observation to correctly manage the power systems. In this context, the aim of this paper is to propose models to generate profiles of the main meteorological variables (irradiance, wind speed, ambient temperature) considering their interdependence, suitable for adequacy and resilience analysis. In this paper, two models are proposed for the generation of the hourly daily radiation profiles based on statistical data: one is based on data probability distributions and the other on the clear sky solar radiation. Moreover, since climatic variables are interdependent, to generate the hourly temperature profiles a model based on the irradiance profile and the monthly mean daily minimum and maximum hourly temperatures is developed. The temperature is generated starting from the measured data and from irradiance data generated using the two approaches here proposed. Then, the persistence of low and high temperature situations and number of consecutive clear and cloudy days considering measured and simulated data is analysed.

A resilience assessment method is proposed to evaluate the time-varying hurricane impact on the power system, which physically connected to a gas system. Internal complexity, external environmental threats and risk induced by interdependence between critical infrastructures highlight the necessity for incorporation of these threats factors in power system performance analysis. Existing researches focus on one aspect, such as natural hazard impact on power system or effect brought by energy system connection. This paper develops a comprehensive assessment method incorporating natural hazard model, hurricane impact model, natural gas system model and system interdependence model in a compatible way. The method employs sequential Monte Carlo simulation to simulate the spatiotemporal power system evolution. A case study is conducted on the IEEE 24-reliability test system and the 15-node natural gas transmission system. The simulation results verify the effectiveness of the proposed method, in terms of analyzing the power system performance under natural hazards.

Multi-dimensional hurricane resilience assessment of electric power systems

The frequent occurrence of natural disasters and malicious attacks has exerted unprecedented disturbances on power systems, accounting for the extensive attention paid to power system resilience. Combined with the evolving nature of general disasters, this paper proposes resilience assessment approaches for power systems under a tri-stage framework. The pre-disaster toughness is proposed to quantify the robustness of power systems against potential disasters, where the thinking of area division and partitioned multi-objective risk method (PMRM) is introduced. In the case of information deficiency caused by disasters, the during-disaster resistance to disturbance is calculated to reflect the real-time system running state by state estimation (SE). The post-disaster restoration ability consists of response ability, restoration efficiency and restoration economy, which is evaluated by Sequential Monte-Carlo Simulation to simulate the system restoration process. Further, a synthetic metric system is presented to quantify the resilience performance of power systems from the above three aspects. The proposed approaches and framework are validated on the IEEE RTS 79 system, and helpful conclusions are drawn from extensive case studies.

Power systems, particularly those located near forests, are exposed to wildfires during summer seasons especially in regions with high temperatures. This issue may impact on operation of power systems and thus their reliability and resilience. However, the traditional reliability and resilience models may not be effective anymore as such events occur more frequently and their impacts are broader than the ones were previously considered in system reliability assessments. In this study, the byproducts of wildfires are identified, and their impacts on power grids are modeled to provide a better picture for reliability and resilience assessments. These models will help analyze the effect of wildfires on different components in a power system, for instance, the impact of heat, smoke, or ash on the power lines and renewable energy resources. Studying the effects of wildfires on electrical power systems, analyzing and formulating these impacts, and determining their intensity on electrical components and energy production are contributions of this paper.

Due to climate changes, many natural disasters have become more serious, such as the intensity of typhoons that are getting higher every year. The characteristics of such a disaster is high-intensity but low-probability event (HILP). How to survive such disasters and increase system resilience in power systems have become an important issue. This paper used a model about line faults to simulate the line failure probability when wind speeds reach up to a certain level, and used a quantitative method to calculate power system resilience. Then, a high resilience was obtained using different precautionary strategies on power system operations, and the differences between the original operation and improved operations were compared. In addition to resilience assessments, this paper also considers economic value (EV) analyses, which makes the system operators to understand whether these preventive measures have a high economic value to be implemented, and to understand under what circumstances the system operators need to perform appropriate actions to obtain the most benefits. This study used the actual load data of Taiwan's power system during typhoons to analyze both resilience assessments and EV evaluation. The simulation results can provide power system operators with more flexible and cost-optimized suggestions to reduce the risk caused by climate factors that are like extreme weather events.

Resilience assessment of the integrated gas and power systems under extreme weather

Electrical resilience assessment of a building operating at low voltage

With the increase of extreme natural disasters and the frequent occurrence of man-made attacks, resilience studies of power grids have attracted much attention, among which resilience assessment reflects the resistance and resilience of power systems to cope with extreme disasters. To improve the resilience of distribution grids under extreme weather conditions, this paper proposes a resilience assessment framework for distribution grids under typhoon disasters. First, a probabilistic generation model of typhoon is established. Second, a spatiotemporal vulnerability model of the distribution grid lines to quantify the spatiotemporal impacts of typhoon. Third, a breadth-first search algorithm is used to island the distribution grid, and the amount of load shedding of the islanded microgrid is calculated. Meanwhile, the resilience of the distribution grid was quantitatively assessed according to the proposed new resilience index. Finally, the feasibility of the proposed resilience assessment method is verified in the IEEE 33-bus test system, and the results show that the proposed method can accurately account for the impact of typhoon on the distribution grid and provides a quantitative reference basis for later power system planning and scheduling.

As the Power System Network/Infrastructure is continuously growing, so does its complexity. As a result, it is more prone to various adverse events which leads to disruption of power flow or continuity. In this paper an approach towards the power system resiliency has been tried with the help of betweenness centrality and minimum spanning tree concept of graph theory. Betweenness centrality of a power system network have been considered here to analyze resiliency of the system in order to find the most critical bus(es) or node(s) and along with that minimum spanning tree based on active power flow has been taken to find out the critical lines, so that what are the effects towards its associated transmission line(s) can be observed precisely. Also, the critical transmission lines based on Minimum Spanning Tree have been taken into consideration in order to harden them. In order to implement these simulations have been carried out on IEEE 57 Bus System.

Global maximum flow based time-domain simulation method for evaluating power system resilience

Age-dependent resilience assessment and quantification of distribution systems under extreme weather events