Integration of Preventive and Emergency Responses to Boost Distribution System Resilience

Recent years have seen a series of large-scale blackouts due to extreme weather events around the world. These high impact, lower probability events have caused great economic losses to modern society. Therefore, it is urgent to study the resilience improvement measures of power systems to mitigate the effects of adverse extreme events. Current research mainly focuses on the hardening measures where robust optimization is used to solve the problems. However, due to the consideration of worst case of uncertain parameters, the robust optimization method is usually too conservative and uneconomical in many situations. In this thesis, operational measures are deployed to boost the distribution system resilience considering all possible scenarios. An integrated resilience response framework is proposed, which provides distribution system operators solutions to address the resilience enhancement problem in both preventive state and emergency states. The key of the framework is a two-stage stochastic mix-integer linear optimization model. The mathematical formulation and the solving method, progressive hedging algorithm, are presented in this thesis as well. Preventive response includes topology reconfiguration and generator redispatch, while topology reconfiguration, generator redispatch and load curtailment are allowed in emergency response. Case study on IEEE 33 bus system and a modified 69 bus system validates the correctness and effectiveness of the proposed framework and model. Integrated response solution is obtained by solving the model and sensitivity analysis is performed to study the performance of integrated response under different system parameters. The key conclusions include the following: 1) integrated response improve distribution system resilience in a minimum cost; 2) integrated response is preferable to either individual preventive or emergency response; 3) system parameters and abilities such as unit load shedding cost, ramping ability and generator availability influence the system resilience and expected total cost in different degrees

Integration of Preventive and Emergency Responses to Boost Distribution System Resilience

Recent years have seen a series of large-scale blackouts due to extreme weather events around the world. These high impact, lower probability events have caused great economic losses to modern society. Therefore, it is urgent to study the resilience improvement measures of power systems to mitigate the effects of adverse extreme events. Current research mainly focuses on the hardening measures where robust optimization is used to solve the problems. However, due to the consideration of worst case of uncertain parameters, the robust optimization method is usually too conservative and uneconomical in many situations. In this thesis, operational measures are deployed to boost the distribution system resilience considering all possible scenarios. An integrated resilience response framework is proposed, which provides distribution system operators solutions to address the resilience enhancement problem in both preventive state and emergency states. The key of the framework is a two-stage stochastic mix-integer linear optimization model. The mathematical formulation and the solving method, progressive hedging algorithm, are presented in this thesis as well. Preventive response includes topology reconfiguration and generator redispatch, while topology reconfiguration, generator redispatch and load curtailment are allowed in emergency response. Case study on IEEE 33 bus system and a modified 69 bus system validates the correctness and effectiveness of the proposed framework and model. Integrated response solution is obtained by solving the model and sensitivity analysis is performed to study the performance of integrated response under different system parameters. The key conclusions include the following: 1) integrated response improve distribution system resilience in a minimum cost; 2) integrated response is preferable to either individual preventive or emergency response; 3) system parameters and abilities such as unit load shedding cost, ramping ability and generator availability influence the system resilience and expected total cost in different degrees

Resilience assessment and planning in power distribution systems:Past and future considerations

Over the past decade, extreme weather events have significantly increased worldwide, leading to widespread power outages and blackouts. As these threats continue to challenge power distribution systems, the importance of mitigating the impacts of extreme weather events has become paramount. Consequently, resilience has become crucial for designing and operating power distribution systems. This work comprehensively explores the current landscape of resilience evaluation and metrics within the power distribution system domain, reviewing existing methods and identifying key attributes that define effective resilience metrics. The challenges encountered during the formulation, development, and calculation of these metrics are also addressed. Additionally, this review acknowledges the intricate interdependencies between power distribution systems and critical infrastructures, including information and communication technology, transportation, water distribution, and natural gas networks. It is important to understand these interdependencies and their impact on power distribution system resilience. Moreover, this work provides an in-depth analysis of existing research on planning solutions to enhance distribution system resilience and support power distribution system operators and planners in developing effective mitigation strategies. These strategies are crucial for minimizing the adverse impacts of extreme weather events and fostering overall resilience within power distribution systems.Comment: 27 pages, 7 figures, submitted for review to Renewable and Sustainable Energy Review

Operation and restoration of bulk power systems using distributed energy resources and multi-microgrids

The fast-paced and meaningful penetration of distributed energy resources (DERs), such as variable renewable energy sources (RESs), concurrently with the widespread occurrence of natural disasters and man-made threats, has raised several challenges for the modern bulk power systems (BPSs) status quo. Although the DERs are demanding new solutions to ensure adequate stability and security levels, these resources enable significant opportunities to improve multiple BPS perspectives. In this view, seeking to capitalize on these novel features, while aware of the significant changes to BPS outlook, this thesis is focused on developing new methods able to capitalize on modern monitoring infrastructures, DERs and control areas opportunities toward the improvement of BPS operation and stability. Specifically, the thesis focuses on: 1) First, a novel method for the improvement of the static security region (SSR) is proposed based on a new network partitioning algorithm. The proposed algorithm focuses on modern BPS with high penetration of variable RES generation. It divides the BPS into coherence areas according to its criticality mapping, and consequently, areas are adaptively associated with SSRs generators groups. To this end, each bus is assigned a criticality index from the potential energy function, whereas this calculation is based on the data of the wide-area measurement system (WAMS) using phasor measurement unit (PMU); 2) Second, a novel area-based sensitivity index for voltage stability support is proposed, exploring both the network-wide sensitivity and the local characteristics of voltage collapse. The developed index focuses on the determination of the most effective buses for voltage support and their respective capability of increasing the system’s load margin. For this, a novel area-based outlook is developed taking advantage of the new possibilities enabled by BPS distributed controllable resources, such as flexible resources (FRs)

Resilience Enhancement Strategies for Modern Power Systems

The frequency of extreme events (e.g., hurricanes, earthquakes, and floods) and man-made attacks (cyber and physical attacks) has increased dramatically in recent years. These events have severely impacted power systems ranging from long outage times to major equipment (e.g., substations, transmission lines, and power plants) destructions. Also, the massive integration of information and communication technology to power systems has evolved the power systems into what is known as cyber-physical power systems (CPPSs). Although advanced technologies in the cyber layer improve the operation and control of power systems, they introduce additional vulnerabilities to power system performance. This has motivated studying power system resilience evaluation and enhancements methods. Power system resilience can be defined as ``The ability of a system to prepare for, absorb, adapt to, and recover from disruptive events''. Assessing resilience enhancement strategies requires further and deeper investigation because of several reasons. First, enhancing the operational and planning resilience is a mathematically involved problem accompanied with many challenges related to modeling and computation methods. The complexities of the problem increases in CPPSs due to the large number and diverse behavior of system components. Second, a few studies have given attention to the stochastic behavior of extreme events and their accompanied impacts on the system resilience level yielding less realistic modeling and higher resilience level. Also, the correlation between both cyber and physical layers within the context of resilience enhancement require leveraging sophisticated modeling approaches which is still under investigation. Besides, the role of distributed energy resources in planning-based and operational-based resilience enhancements require further investigation. This calls for developing enhancement strategies to improve resilience of power grids against extreme events. This dissertation is divided into four parts as follows. Part I: Proactive strategies: utilizing the available system assets to prepare the power system prior to the occurrence of an extreme event to maintain an acceptable resilience level during a severe event. Various system generation and transmission constraints as well as the spatiotemporal behavior of extreme events should be properly modeled for a feasible proactive enhancement plan. In this part, two proactive strategies are proposed against weather-related extreme events and cyber-induced failure events. First, a generation redispatch strategy is formulated to reduce the amount of load curtailments in transmission systems against hurricanes and wildfires. Also, a defensive islanding strategy is studied to isolate vulnerable system components to cyber failures in distribution systems. Part II: Corrective strategies: remedial actions during an extreme event for improved performance. The negative impacts of extreme weather events can be mitigated, reduced, or even eliminated through corrective strategies. However, the high stochastic nature of resilience-based problem induces further complexities in modeling and providing feasible solutions. In this part, reinforcement learning approaches are leveraged to develop a control-based environment for improved resilience. Three corrective strategies are studied including distribution network reconfiguration, allocating and sizing of distributed energy resources, and dispatching reactive shunt compensators. Part III: Restorative strategies: retain the power service to curtailed loads in a fast and efficient means after a diverse event. In this part, a resilience enhancement strategy is formulated based on dispatching distributed generators for minimal load curtailments and improved restorative behavior. Part IV: Uncertainty quantification: Impacts of uncertainties on modeling and solution accuracy. Though there exist several sources of stochasticity in power systems, this part focuses on random behavior of extreme weather events and the associated impacts on system component failures. First, an assessment framework is studied to evaluate the impacts of ice storms on transmission systems and an evaluation method is developed to quantify the hurricane uncertainties for improved resilience. Additionally, the role of unavailable renewable energy resources on improved system resilience during extreme hurricane events is studied. The methodologies and results provided in this dissertation can be useful for system operators, utilities, and regulators towards enhancing resilience of CPPSs against weather-related and cyber-related extreme events. The work presented in this dissertation also provides potential pathways to leverage existing system assets and resources integrated with recent advanced computational technologies to achieve resilient CPPSs

Modelling and analysis of smart localised energy system for a sustainable future power network

Combating the increasing effect of climate change and averting future energy crisis resulting partly due to our continued dependence on conventional energy sources requires exploring aggressively more sustainable means of generating and utilising energy. Currently, most developed countries are transitioning slowly from a fossil fuel dominated energy system to a sustainable and renewable energy based system. However, for the results of these transitions to be impactful and reduce the global temperature rise to the expected 1.5oC, the approach must be wholistic and encompassing. Although there are a lot of ongoing research in the areas of renewable energy integration into the grid, however, there seems to be a dearth of such studies in some specific aspect of the power system application. Consequently, this thesis models and performs several analyses on a smart localised energy system with the aim of decarbonising some aspects of the future power network. The study investigated the dynamics of residential power demand in Nigeria and modelled the residential energy consumption profile. An excel-based algorithm was developed and applied to the developed model. The results of the residential energy consumption was based on the appliance energy end use methodology. This was used to develop a load profile indicative of a typical urban residential energy demand in Nigeria and employed to predict the effects of residential loads on the power system. Following the frequent use of diesel generators by municipal councils to power street lighting, several case studies demonstrating how to optimise street lighting energy consumption and improve energy efficiency were carried out using simple economic analysis indices such as Life Cycle Cost (LCC), Annualized Life Cycle Cost (ALCC), Net Present Cost (NPC), Cost of Energy (COE), and Return on Investment (ROI). The solar photovoltaic (SPV) system had the lowest LCC and ALCC, thus making it the most economically viable option. The response of the power system to Distributed Energy Resources (DERs) integration was also investigated. Data from a real low voltage (LV) distribution network in Nigeria was obtained and used in modelling the network using PSCAD/EMTDC software package. Different impact studies considering addition of distributed generation sources and increase in the load were performed. Volt-VAr optimisation (VVO) was performed to enable the inverter-based PV systems participate actively in voltage regulation by the provision of flexible reactive power support. A net total of 1.359 MVAr and 1.301 MVAr respectively are utilised from the inverter to regulate voltage within the acceptable limits, hence reducing the substation reactive power by 19.8% and 18.9% respectively during the controlled case study. Also, the total active power loss did reduce from 0.437 MW to 0.172 MW while the deviation of consumer voltages from the nominal system voltage was reduced by 33.4% during the controlled case studies. Overall, the VVO did enhance power quality and reliability by improving the feeder voltage profile and reducing the active power losses in the network. Lastly, to decarbonise some operation of the power system and improve the system resilience, DERs integrated black start restoration (BSR) strategy was implemented. The formulated BSR problem was implemented as a dynamic optimisation problem and the simulation was performed on the Nigerian 330 kV 48-bus system. The mixed-integer linear programming (MILP) technique was adopted and modelled to suit the nature of the BSR method developed. The black start power restoration sequence and the development of a viable restoration strategy were actualised. The simulation of the MILP model was achieved in MATLAB® using the IBM CPLEXTM solver. For the Nigerian 330 kV 48-bus system analysed, it was observed that most loads were optimally restored before the 30th time step for a black start operation. Both the experimental and numerical methodology were adopted in the validation of energy storage system (ESS) adopted for the proposed BSR simulated study. The optimal battery power availability for participating in restoration was reached in less than 50 minutes, with ESS optimally contributing to power restoration achieving 4.3% & 18.1% for Kaduna and Jos respectively