An Integrated Method for Optimizing Bridge Maintenance Plans

Bridges are one of the vital civil infrastructure assets, essential for economic developments and public welfare. Their large numbers, deteriorating condition, public demands for safe and efficient transportation networks and limited maintenance and intervention budgets pose a challenge, particularly when coupled with the need to respect environmental constraints. This state of affairs creates a wide gap between critical needs for intervention actions, and tight maintenance and rehabilitation funds. In an effort to meet this challenge, a newly developed integrated method for optimized maintenance and intervention plans for reinforced concrete bridge decks is introduced. The method encompasses development of five models: surface defects evaluation, corrosion severities evaluation, deterioration modeling, integrated condition assessment, and optimized maintenance plans. These models were automated in a set of standalone computer applications, coded using C#.net in Matlab environment. These computer applications were subsequently combined to form an integrated method for optimized maintenance and intervention plans. Four bridges and a dataset of bridge images were used in testing and validating the developed optimization method and its five models. The developed models have unique features and demonstrated noticeable performance and accuracy over methods used in practice and those reported in the literature. For example, the accuracy of the surface defects detection and evaluation model outperforms those of widely-recognized machine leaning and deep learning models; reducing detection, recognition and evaluation of surface defects error by 56.08%, 20.2% and 64.23%, respectively. The corrosion evaluation model comprises design of a standardized amplitude rating system that circumvents limitations of numerical amplitude-based corrosion maps. In the integrated condition, it was inferred that the developed model accomplished consistent improvement over the visual inspection procedures in-use by the Ministry of Transportation in Quebec. Similarly, the deterioration model displayed average enhancement in the prediction accuracies by 60% when compared against the most commonly-utilized weibull distribution. The performance of the developed multi-objective optimization model yielded 49% and 25% improvement over that of genetic algorithm in a five-year study period and a twenty five-year study period, respectively. At the level of thirty five-year study period, unlike the developed model, classical meta-heuristics failed to find feasible solutions within the assigned constraints. The developed integrated platform is expected to provide an efficient tool that enables decision makers to formulate sustainable maintenance plans that optimize budget allocations and ensure efficient utilization of resources

Investigating evolutionary computation with smart mutation for three types of Economic Load Dispatch optimisation problem

The Economic Load Dispatch (ELD) problem is an optimisation task concerned with how electricity generating stations can meet their customers’ demands while minimising under/over-generation, and minimising the operational costs of running the generating units. In the conventional or Static Economic Load Dispatch (SELD), an optimal solution is sought in terms of how much power to produce from each of the individual generating units at the power station, while meeting (predicted) customers’ load demands. With the inclusion of a more realistic dynamic view of demand over time and associated constraints, the Dynamic Economic Load Dispatch (DELD) problem is an extension of the SELD, and aims at determining the optimal power generation schedule on a regular basis, revising the power system configuration (subject to constraints) at intervals during the day as demand patterns change. Both the SELD and DELD have been investigated in the recent literature with modern heuristic optimisation approaches providing excellent results in comparison with classical techniques. However, these problems are defined under the assumption of a regulated electricity market, where utilities tend to share their generating resources so as to minimise the total cost of supplying the demanded load. Currently, the electricity distribution scene is progressing towards a restructured, liberalised and competitive market. In this market the utility companies are privatised, and naturally compete with each other to increase their profits, while they also engage in bidding transactions with their customers. This formulation is referred to as: Bid-Based Dynamic Economic Load Dispatch (BBDELD). This thesis proposes a Smart Evolutionary Algorithm (SEA), which combines a standard evolutionary algorithm with a “smart mutation” approach. The so-called ‘smart’ mutation operator focuses mutation on genes contributing most to costs and penalty violations, while obeying operational constraints. We develop specialised versions of SEA for each of the SELD, DELD and BBDELD problems, and show that this approach is superior to previously published approaches in each case. The thesis also applies the approach to a new case study relevant to Nigerian electricity deregulation. Results on this case study indicate that our SEA is able to deal with larger scale energy optimisation tasks

Lost in optimisation of water distribution systems? A literature review of system design

This is the final version of the article. Available from MDPI via the DOI in this record.Optimisation of water distribution system design is a well-established research field, which has been extremely productive since the end of the 1980s. Its primary focus is to minimise the cost of a proposed pipe network infrastructure. This paper reviews in a systematic manner articles published over the past three decades, which are relevant to the design of new water distribution systems, and the strengthening, expansion and rehabilitation of existing water distribution systems, inclusive of design timing, parameter uncertainty, water quality, and operational considerations. It identifies trends and limits in the field, and provides future research directions. Exclusively, this review paper also contains comprehensive information from over one hundred and twenty publications in a tabular form, including optimisation model formulations, solution methodologies used, and other important details

Various optimization algorithms adaptation and case study applied on optimal location and sizing of distribution generation systems in electric power grids

Abstract: The development of distribution systems consists in determining the optimal site and size of new substations and feeders in order to optimize the future power demand with minimum investment and operational costs and a suitable level of consistency. This problem is a combination of, non-linear and constrained optimization problem. Several optimization methods, such as genetic algorithms, simulated annealing, hybrid genetic algorithm and variable neighbourhood search have been reported in the literature where several optimization methods have been stated with the uses of the minor structures while the others have extensive solution time. The main goal behind this thesis is to presents optimization methodologies in the aim to provide a close optimum solution for the (DG) in distribution networks. In the presented methods we take into our account the randomness of distributed generation based on renewable energies, as well as the randomness of electric demand in the planning horizon. First, state-of-the-art research is carried out on existing models for generation planning in electrical systems and distribution network planning models...D.Ing. (Electrical and Electronic Engineering

Review of Metaheuristic Optimization Algorithms for Power Systems Problems

Metaheuristic optimization algorithms are tools based on mathematical concepts that are used to solve complicated optimization issues. These algorithms are intended to locate or develop a sufficiently good solution to an optimization issue, particularly when information is sparse or inaccurate or computer capability is restricted. Power systems play a crucial role in promoting environmental sustainability by reducing greenhouse gas emissions and supporting renewable energy sources. Using metaheuristics to optimize the performance of modern power systems is an attractive topic. This research paper investigates the applicability of several metaheuristic optimization algorithms to power system challenges. Firstly, this paper reviews the fundamental concepts of metaheuristic optimization algorithms. Then, six problems regarding the power systems are presented and discussed. These problems are optimizing the power flow in transmission and distribution networks, optimizing the reactive power dispatching, optimizing the combined economic and emission dispatching, optimal Volt/Var controlling in the distribution power systems, and optimizing the size and placement of DGs. A list of several used metaheuristic optimization algorithms is presented and discussed. The relevant results approved the ability of the metaheuristic optimization algorithm to solve the power system problems effectively. This, in particular, explains their wide deployment in this field

Optimal composite generation and transmission expansion planning considering renewable energy sources, harmonics and system reliability

Abstract: Electricity generation via conventional generating systems is faced with challenges such as emission of greenhouse gases, uncertainty associated with fossil fuel prices and incidences of failure or outages of generation. This dissertation proposes the incorporation of largescale Renewable Energy Sources (RES) into power systems in order to reduce the challenges associated with conventional generating systems. The first part of this dissertation investigates the contribution of RES and economic incentives to the composite generation and transmission expansion planning procedure. A Mixed Integer Quadratic Programming (MIQP) model based on composite generation and transmission expansion planning is proposed for solving a multi-objective mathematical optimization problem which includes minimization of the investment costs, operational costs, emissions as well as the maximization of economic incentives. Obtained results, when compared with previous works indicate that encouraging economic incentives improves the effective utilization of offshore wind farms and consequently reduces the emissions from conventional generating units....D.Phil. (Electrical and Electronic Engineering

Energy Efficient Policies, Scheduling, and Design for Sustainable Manufacturing Systems

Climate mitigation, more stringent regulations, rising energy costs, and sustainable manufacturing are pushing researchers to focus on energy efficiency, energy flexibility, and implementation of renewable energy sources in manufacturing systems. This thesis aims to analyze the main works proposed regarding these hot topics, and to fill the gaps in the literature. First, a detailed literature review is proposed. Works regarding energy efficiency in different manufacturing levels, in the assembly line, energy saving policies, and the implementation of renewable energy sources are analyzed. Then, trying to fill the gaps in the literature, different topics are analyzed more in depth. In the single machine context, a mathematical model aiming to align the manufacturing power required to a renewable energy supply in order to obtain the maximum profit is developed. The model is applied to a single work center powered by the electric grid and by a photovoltaic system; afterwards, energy storage is also added to the power system. Analyzing the job shop context, switch off policies implementing workload approach and scheduling considering variable speed of the machines and power constraints are proposed. The direct and indirect workloads of the machines are considered to support the switch on/off decisions. A simulation model is developed to test the proposed policies compared to others presented in the literature. Regarding the job shop scheduling, a fixed and variable power constraints are considered, assuming the minimization of the makespan as the objective function. Studying the factory level, a mathematical model to design a flow line considering the possibility of using switch-off policies is developed. The design model for production lines includes a targeted imbalance among the workstations to allow for defined idle time. Finally, the main findings, results, and the future directions and challenges are presented

Distribution Network Operation with High Penetration of Renewable Energy Sources. Joint Active/Reactive Power Procurement: A Market-Based Approach for Operation of Distribution Network

Distributed generators (DGs) are proposed as a possible solution to supply economic and reliable electricity to customers. It is adapted to overcome the challenges that are characterized by centralized generation such as transmission and distribution losses, high cost of fossil fuels and environmental damage. This work presents the basic principles of integrating renewable DGs in low voltage distribution networks and particularly focuses on the operation of DG installations and their impacts on active and reactive power. In this thesis, a novel technique that applies the stochastic approach for the operation of distribution networks with considering active network management (ANM) schemes and demand response (DR) within a joint active and reactive distribution market environment is proposed. The projected model is maximized based on social welfare (SW) using market-based joint active and reactive optimal power flow (OPF). The intermittent behaviour of renewable sources (such as solar irradiance and wind speed) and the load demands are modelled through Scenario-Tree technique. The distributed network frame is recast using mixed-integer linear programming (MILP) that is solved by using the GAMS software and then the obtained results are being analysed and discussed. In addition, the impact of wind and solar power penetration on the active and reactive distribution locational prices (D-LMPs) within the distribution market environment is explored in terms of the maximization of SW considering the uncertainty related to solar irradiance, wind speed and load demands. Finally, a realistic case study (16-bus UK generic medium voltage distribution system) is used to demonstrate the effectiveness of the proposed method. Results show that ANM schemes and DR integration lead to an increase in the social welfare and total dispatched active and reactive power and consequently decrease in active and reactive D-LMPs.Ministry of Higher Education and Scientific Research - IraqThe selected author's publications, the published versions of which were attached at the end of the thesis, have been removed due to copyright

Optimización multiobjetivo de la red de distribución de energía eléctrica

Se ha desarrollado la planificación del diseño óptimo de las redes de distribución de energía eléctrica mediante la aplicación y adaptación del algoritmo evolutivo NSGA II, basado en el elitismo y la dominancia de Pareto. Para ello se han considerado tres objetivos; la minimización de perdidas, la maximización de la fiabilidad de suministro del sistema y una función de costes. Esta función de costes, en lugar de ser la generica de minimización de costes se ha adaptado a la realidad del sector, pasando a ser considerada una función de maximización de la retribución de la actividad de distribución El problema esta sujeto a las restricciones habituales, de caída de tensión, capacidad de elementos, radialidad de la red y balance de potencia. Ademas de haber dos restricciones especificas de la legislación; la estandarización de los elementos y la inversión máxima. Contando como variables de decisión, la localización y tamaño de las lineas y subestaciones a instalar, o ampliarThe optimal design of the electric power distribution grids has been developed through the application and adaptation of the evolutive algorithm NSGAII. This algorithm is based on the elitism and dominance of Pareto. To this end, three objectives have been considered: the maximization of loses; the maximization of the reliability of the system supply and a costs function. This costs function is not the generic one of costs minimization, but a new function adapted to the sector reality, and so it is considered as a function of maximization of the retribution of the retribution activity. The problem is supedited to the habitual restrictions of voltage drop, capability of the elements, radiality of the gris and power balance. There are also two specific restrictions related to the legiation: the standarization of the elements and the maximum investment allowed.The location and size of the lines and substations that must be installed or enlarged are considered decision variables.Junta de Castilla y León (a través del proyecto de referencia BU329U14) y del Ministerio de Economía y Competitividad y Fondos FEDER (a través del proyecto de referencia ECO2013-47129-C4-3-R