Enhanced Reserve Procurement Policies for Power Systems with Increasing Penetration Levels of Stochastic Resources

abstract: The uncertainty and variability associated with stochastic resources, such as wind and solar, coupled with the stringent reliability requirements and constantly changing system operating conditions (e.g., generator and transmission outages) introduce new challenges to power systems. Contemporary approaches to model reserve requirements within the conventional security-constrained unit commitment (SCUC) models may not be satisfactory with increasing penetration levels of stochastic resources; such conventional models pro-cure reserves in accordance with deterministic criteria whose deliverability, in the event of an uncertain realization, is not guaranteed. Smart, well-designed reserve policies are needed to assist system operators in maintaining reliability at least cost. Contemporary market models do not satisfy the minimum stipulated N-1 mandate for generator contingencies adequately. This research enhances the traditional market practices to handle generator contingencies more appropriately. In addition, this research employs stochastic optimization that leverages statistical information of an ensemble of uncertain scenarios and data analytics-based algorithms to design and develop cohesive reserve policies. The proposed approaches modify the classical SCUC problem to include reserve policies that aim to preemptively anticipate post-contingency congestion patterns and account for resource uncertainty, simultaneously. The hypothesis is to integrate data-mining, reserve requirement determination, and stochastic optimization in a holistic manner without compromising on efficiency, performance, and scalability. The enhanced reserve procurement policies use contingency-based response sets and post-contingency transmission constraints to appropriately predict the influence of recourse actions, i.e., nodal reserve deployment, on critical transmission elements. This research improves the conventional deterministic models, including reserve scheduling decisions, and facilitates the transition to stochastic models by addressing the reserve allocation issue. The performance of the enhanced SCUC model is compared against con-temporary deterministic models and a stochastic unit commitment model. Numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems. Test results illustrate that the proposed reserve models consistently outperform the benchmark reserve policies by improving the market efficiency and enhancing the reliability of the market solution at reduced costs while maintaining scalability and market transparency. The proposed approaches require fewer ISO discretionary adjustments and can be employed by present-day solvers with minimal disruption to existing market procedures.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Performance Enhancement of Power System Operation and Planning through Advanced Advisory Mechanisms

abstract: This research develops decision support mechanisms for power system operation and planning practices. Contemporary industry practices rely on deterministic approaches to approximate system conditions and handle growing uncertainties from renewable resources. The primary purpose of this research is to identify soft spots of the contemporary industry practices and propose innovative algorithms, methodologies, and tools to improve economics and reliability in power systems. First, this dissertation focuses on transmission thermal constraint relaxation practices. Most system operators employ constraint relaxation practices, which allow certain constraints to be relaxed for penalty prices, in their market models. A proper selection of penalty prices is imperative due to the influence that penalty prices have on generation scheduling and market settlements. However, penalty prices are primarily decided today based on stakeholder negotiations or system operator’s judgments. There is little to no methodology or engineered approach around the determination of these penalty prices. This work proposes new methods that determine the penalty prices for thermal constraint relaxations based on the impact overloading can have on the residual life of the line. This study evaluates the effectiveness of the proposed methods in the short-term operational planning and long-term transmission expansion planning studies. The second part of this dissertation investigates an advanced methodology to handle uncertainties associated with high penetration of renewable resources, which poses new challenges to power system reliability and calls attention to include stochastic modeling within resource scheduling applications. However, the inclusion of stochastic modeling within mathematical programs has been a challenge due to computational complexities. Moreover, market design issues due to the stochastic market environment make it more challenging. Given the importance of reliable and affordable electric power, such a challenge to advance existing deterministic resource scheduling applications is critical. This ongoing and joint research attempts to overcome these hurdles by developing a stochastic look-ahead commitment tool, which is a stand-alone advisory tool. This dissertation contributes to the derivation of a mathematical formulation for the extensive form two-stage stochastic programming model, the utilization of Progressive Hedging decomposition algorithm, and the initial implementation of the Progressive Hedging subproblem along with various heuristic strategies to enhance the computational performance.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Structural Reliability Assessment under Fire.

Structural safety under fire has received significant attention in recent years. Current approaches to structural fire design are based on prescriptive codes that emphasize insulation of steel members to achieve adequate fire resistance. The prescriptive approach fails to give a measure of the true performance of structural systems in fire and gives no indication of the level of reliability provided by the structure in the face of uncertainty. The performance-based design methodology overcomes many of the limitations of the prescriptive approach. The quantification of the structural reliability is a key component of performance-based design as it provides an objective manner of comparing alternative design solutions. In this study, a probabilistic framework is established to evaluate the structural reliability under fire considering uncertainties that exist in the system. The structural performance subjected to realistic fires is estimated by numerical simulations of sequentially coupled fire, thermal, and structural analyses. In this dissertation, multiple reliability methods (i.e., Latin hypercube simulation, subset simulation, and the first/second order reliability methods) are extended to investigate the structural safety under fire. The reliability analysis of structures in fire involves (i) the identification and characterization of uncertain parameters in the system, (ii) a probabilistic analysis of the thermo-mechanical response of the structure, and (iii) the evaluation of structural reliability based on a suitable limit state function. Several applications are considered involving the response of steel and steel-concrete composite structures subjected to natural fires. Parameters in the fire, thermal, and structural models are characterized, and an improved fire hazard model is proposed that accounts for fire spread to adjacent rooms. The importance of various parameters is determined by considering the response sensitivity, which is determined by finite difference and direct differentiation methods. The accuracy and efficiency of the various reliability methods, as applied to structures in fire, are compared, and the strengths and weaknesses of each approach are identified.PhDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111381/1/qianru_1.pd

Risk Management for the Future

A large part of academic literature, business literature as well as practices in real life are resting on the assumption that uncertainty and risk does not exist. We all know that this is not true, yet, a whole variety of methods, tools and practices are not attuned to the fact that the future is uncertain and that risks are all around us. However, despite risk management entering the agenda some decades ago, it has introduced risks on its own as illustrated by the financial crisis. Here is a book that goes beyond risk management as it is today and tries to discuss what needs to be improved further. The book also offers some cases

The development of a full probabilistic risk assessment model for quantifying the life safety risk in buildings in case of fire

In het kader van dit onderzoek is een probabilistisch model ontwikkeld dat het brandveiligheidsniveau van een gebouwontwerp kan kwantificeren en dit berekende veiligheidsniveau kan evalueren aan de hand van een vooraf gedefinieerd aanvaardbaar risicocriterium. De ontwikkelde methodiek kan zowel prescriptieve als op prestatie-gebaseerde ontwerpmethoden objectiveren door rekening te houden met de onzekerheid van ontwerpparameters en de betrouwbaarheid van veiligheidssystemen. Het model bestaat uit zowel een deterministisch als een probabilistisch gedeelte. Het deterministische kader is opgebouwd uit verschillende deelmodellen om zowel de verspreiding van brand en rook, als de interactie met evacuerende personen te simuleren. Verschillende deelmodellen zijn ontwikkeld om het effect van geïmplementeerde veiligheidsmaatregelen zoals detectie, sprinklers , rook- en warmteafvoersystemen, enz. mee in rekening te brengen. Het probabilistische kader is opgebouwd uit modellering van responsoppervlakken, steekproeftechnieken en ontwerp van grenstoestanden. De methodiek maakt gebruik van deze technieken om de nodige rekenkracht te beperken. Het uiteindelijke resultaat wordt vertaald naar een kans op sterfte, een individueel risico en een groepsrisico. De grote meerwaarde van de ontwikkelde methodiek is dat het mogelijk wordt om verschillende ontwerpmethodieken objectief met elkaar te vergelijken en het positieve effect van verbeterde veiligheidstechnieken en redundantie mee in rekening te brengen in het eindresultaat

Through-life stochastic carbon emission assessment and optimisation for critical assets

International governments and businesses are increasingly pledging more action to address human-induced climate change, including committing to the Paris Climate Agreement, which seeks to reduce global Greenhouse Gas Emissions (GHGE). Critical assets provide essential capabilities where failure could have catastrophic consequences. These assets have long service lives and are exposed to varying operational conditions and service requirements, which makes assessing through-life GHGE challenging. Current modelling techniques provide deterministic, single-point results, which provides a limited assessment of critical asset through-life GHGE where uncertainty can be significant. Furthermore, no modelling technique was identified that relates asset GHGE to Whole Life Cost (WLC) and operational effectiveness, which are both organisational priorities. This leaves decision-makers without robust information regarding the possible impacts of GHGE reduction strategies on the WLC and the operational effectiveness of their critical assets. This study develops a methodology framework to model critical asset GHGE with WLC and operational availability based on industry best practices and transferrable modelling techniques from other sectors. A model was created based on an in-service helicopter platform and was subjected to four test scenarios to demonstrate effects on WLC, GHGE and operational availability relative to baseline. Monte Carlo simulation was used to appropriately present modelling uncertainty

Operating health analysis of electric power systems

The required level of operating reserve to be maintained by an electric power system can be determined using both deterministic and probabilistic techniques. Despite the obvious disadvantages of deterministic approaches there is still considerable reluctance to apply probabilistic techniques due to the difficulty of interpreting a single numerical risk index and the lack of sufficient information provided by a single index. A practical way to overcome difficulties is to embed deterministic considerations in the probabilistic indices in order to monitor the system well-being. The system well-being can be designated as healthy, marginal and at risk. The concept of system well-being is examined and extended in this thesis to cover the overall area of operating reserve assessment. Operating reserve evaluation involves the two distinctly different aspects of unit commitment and the dispatch of the committed units. Unit commitment health analysis involves the determination of which unit should be committed to satisfy the operating criteria. The concepts developed for unit commitment health, margin and risk are extended in this thesis to evaluate the response well-being of a generating system. A procedure is presented to determine the optimum dispatch of the committed units to satisfy the response criteria. The impact on the response wellbeing being of variations in the margin time, required regulating margin and load forecast uncertainty are illustrated. The effects on the response well-being of rapid start units, interruptible loads and postponable outages are also illustrated. System well-being is, in general, greatly improved by interconnection with other power systems. The well-being concepts are extended to evaluate the spinning reserve requirements in interconnected systems. The interconnected system unit commitment problem is decomposed into two subproblems in which unit scheduling is performed in each isolated system followed by interconnected system evaluation. A procedure is illustrated to determine the well-being indices of the overall interconnected system. Under normal operating conditions, the system may also be able to carry a limited amount of interruptible load on top of its firm load without violating the operating criterion. An energy based approach is presented to determine the optimum interruptible load carrying capability in both the isolated and interconnected systems. Composite system spinning reserve assessment and composite system well-being are also examined in this research work. The impacts on the composite well-being of operating reserve considerations such as stand-by units, interruptible loads and the physical locations of these resources are illustrated. It is expected that the well-being framework and the concepts developed in this research work will prove extremely useful in the new competitive utility environment