Multi-energy Microgrids Incorporating EV Integration : Optimal Design and Resilient Operation

There are numerous opportunities and challenges in integrating multiple energy sources, for example, electrical, heat, and electrified transportation. The operation of multi-energy sources needs to be coordinated and optimized to achieve maximum benefits and reliability. To address the electrical, thermal, and transportation electrification energy demands in a sustainable and environmentally friendly multi-energy microgrid, this paper presents a mixed integer linear optimization model that determines an optimized blend of energy sources (battery, combined heat and power units, thermal energy storage, gas boiler, and photovoltaic generators), size, and associated dispatch. The proposed energy management system seeks to minimize total annual expenses while simultaneously boosting system resilience during extended grid outages, based on an hourly electrical and thermal load profile. This approach has been tested in a hospital equipped with an EV charging station in Okinawa, Japan through several case studies. Following a M1/M2/c queuing model, the proposed grid-tied microgrid successfully integrates EVs into the system and assures continued and economic power supply even during grid failures in different weather conditions.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Risk based multi-objective security control and congestion management

Deterministic security criterion has served power system operation, congestion management quite well in last decades. It is simple to be implemented in a security control model, for example, security constrained optimal power flow (SCOPF). However, since event likelihood and violation information are not addressed, it does not provide quantitative security understanding, and so results in system inadequate awareness. Therefore, even if computation capability and information techniques have been greatly improved and widely applied in the operation support tool, operators are still not able to get rid of the security threat, especially in the market competitive environment.;Probability approach has shown its strong ability for planning purpose, and recently gets attention in operation area. Since power system security assessment needs to analyze consequence of all credible events, risk defined as multiplication of event probability and severity is well suited to give an indication to quantify the system security level, and congestion level as well. Since risk addresses extra information, its application for making BETTER online operation decision becomes an attractive research topic.;This dissertation focus on system online risk calculation, risk based multi-objective optimization model development, risk based security control design, and risk based congestion management. A regression model is proposed to predict contingency probability using weather and geography information for online risk calculation. Risk based multi-objective optimization (RBMO) model is presented, considering conflict objectives: risks and cost. Two types of method, classical methods and evolutionary algorithms, are implemented to solve RBMO problem, respectively. A risk based decision making architecture for security control is designed based on the Pareto-optimal solution understanding, visualization tool and high level information analysis. Risk based congestion management provides a market lever to uniformly expand a security VOLUME , where greater volume means more risk. Meanwhile, risk based LMP signal contracts ALL dimensions of this VOLUME in proper weights (state probabilities) at a time.;Two test systems, 6-bus and IEEE RTS 96, are used to test developed algorithms. The simulation results show that incorporating risk into security control and congestion management will evolve our understanding of security level, improve control and market efficiency, and support operator to maneuver system in an effective fashion

Development and optimization of new generation start-up instrumentation systems (SUI) for domestic CANDU reactors

Due to the age and operating experience of Bruce Power units, equipment ageing and obsolescence has become one of the main challenges that need to be resolved for all systems, structures and components in order to ensure a safe and reliable production of energy. The research objectives of this thesis will focus on methodology for modernization of Start- Up Instrumentation (SUI), both in-core and Control Room equipment, using a new generation of detectors and cables in order to manage obsolescence. The main objective of this thesis is to develop a new systematic approach to SUI installation/replacement procedure development and optimization. Although some additional features, such as real-time data monitoring and storage/archiving solutions for SUI systems are also examined to take full advantage of today???s digital technology, the objective of this thesis does not include detailed parametrical studies of detector or system performance. Instead, a number of technological, operational and maintenance issues associated with Start-Up Instrumentation systems at Bruce Power will be identified in this project and a structured approach to developing a replacement/installation procedure that can be standardized and used across all of the domestic CANDU stations is proposed. Finally, benefits of Hierarchical Control Chart (HCC) methodology for all stages of plant life management, such as system design, development, operation and maintenance are demonstrated. Keywords: Task Breakdown and Analysis methodology, installation/removal procedure development and optimization, risk-based analysis and optimization, Hierarchical Control Chart (HCC) methodology for system maintenance and troubleshooting, Start-Up Instrumentation (SUI), Ion Chambers, Fission Chambers, proportional counters, Shutdown System 1 (SDS1), Shutdown System 2 (SDS2)

Optimal operation of hybrid AC/DC microgrids under uncertainty of renewable energy resources : A comprehensive review

The hybrid AC/DC microgrids have become considerably popular as they are reliable, accessible and robust. They are utilized for solving environmental, economic, operational and power-related political issues. Having this increased necessity taken into consideration, this paper performs a comprehensive review of the fundamentals of hybrid AC/DC microgrids and describes their components. Mathematical models and valid comparisons among different renewable energy sources’ generations are discussed. Subsequently, various operational zones, control and optimization methods, power flow calculations in the presence of uncertainties related to renewable energy resources are reviewed.fi=vertaisarvioitu|en=peerReviewed

Utilization of Integer Programming for Scheduling Maintenance at Nuclear Power Plants

This thesis develops a thought that naturally explores three specific motifs for solving the complexities of scheduling maintenance at Nuclear Power Plants (NPP). The first chapter of this paper will develop the initial thought around creating a schedule for a given work week, including all the various constraints inherent to this problem. Such constraints include but are not limited to personnel availability, allowable component out-of-service time, and the Plant Risk Assessment. The objective function being to minimize the total cost of worker’s compensation for that given week. The second chapter addresses the question of whether this simple schedule can be implemented with a long time horizon as the goal. This section delves into the concept of utilizing maintenance task frequencies and extended preventive maintenance frequencies to once again minimize the objective function of cost due to compensation. The third chapter focuses on the ability of the program to respond to adaptive circumstances. One major obstacle in running any large commercial facility is unplanned downtime of required systems or components. Simulating failures of certain components that shorten the overall allowable out-of-service time, the program will be required to still minimize the objective function while navigating these changing timelines

Overview of electric energy distribution networks expansion planning

Planning of the electric distribution networks is complex and about upgrading the system to satisfy the demand and constraints with the best economic plan. The planning alternatives include the expansion of substations, installing new distributed generation (DG) facilities, upgrading distribution feeders, etc. In the modern networks, distribution planners must gain the confidence of the reversibility of the investment where renewable energy resources (RERs) inject clean and cost-effective electrical power to respond to the rising demand and satisfy environmental standards. This paper is an exhaustive review on the distribution network expansion planning (DEP) including the modelling of DEP (possible objective functions, problem constraints, different horizon time, and problem variables), optimization model (single/multi-objective), the expansion of distributed energy resources (DERs), problem uncertainties, etc. We discuss the requirements of integrated energy district master planning to avoid conflicts between the goal of independence of district planning on energy, e.g. heat and electricity, and that of dependencies on the local electric utilities regarding instant power balance and stability services. Finally, we describe the primary future R&D trends in the field of distribution network planning

Pipe failure prediction and impacts assessment in a water distribution network

Abstract Water distribution networks (WDNs) aim to provide water with desirable quantity, quality and pressure to the consumers. However, in case of pipe failure, which is the cumulative effect of physical, operational and weather-related factors, the WDN might fail to meet these objectives. Rehabilitation and replacement of some components of WDNs, such as pipes, is a common practice to improve the condition of the network to provide an acceptable level of service. The overall aim of this thesis is to predict—long-term, annually and short-term—the pipe failure propensity and assess the impacts of a single pipe failure on the level of service. The long-term and annual predictions facilitate the need for effective capital investment, whereas the short-term predictions have an operational use, enabling the water utilities to adjust the daily allocation and planning of resources to accommodate possible increase in pipe failure. The proposed methodology was implemented to the cast iron (CI) pipes in a UK WDN. The long-term and annual predictions are made using a novel combination of Evolutionary Polynomial Regression (EPR) and K-means clustering. The inclusion of K-means improves the predictions’ accuracy by using a set of models instead of a single model. The long-term predictive models consider physical factors, while the annual predictions also include weather-related factors. The analysis is conducted on a group level assuming that pipes with similar properties have similar breakage patterns. Soil type is another aggregation criterion since soil properties are associated with the corrosion of metallic pipes. The short-term predictions are based on a novel Artificial Neural Network (ANN) model that predicts the variations above a predefined threshold in the number of failures in the following days. The ANN model uses only existing weather data to make predictions reducing their uncertainty. The cross-validation technique is used to derive an accurate estimate of accuracy of EPR and ANN models by guaranteeing that all observations are used for both training and testing, and each observation is used for testing only once. The impact of pipe failure is assessed considering its duration, the topology of the network, the geographic location of the failed pipe and the time. The performance indicators used are the ratio of unsupplied demand and the number of customers with partial or no supply. Two scenarios are examined assuming that the failure occurs when there is a peak in either pressure or demand. The pressure-deficient conditions are simulated by introducing a sequence of artificial elements to all the demand nodes with pressure less than the required. This thesis proposes a new combination of a group-based method for deriving the failure rate and an individual-pipe method for evaluating the impacts on the level of service. Their conjunction indicates the most critical pipes. The long-term approach improves the accuracy of predictions, particularly for the groups with very low or very high failure frequency, considering diameter, age and length. The annual predictions accurately predict the fluctuation of failure frequency and its peak during the examined period. The EPR models indicate a strong direct relationship between low temperatures and failure frequency. The short-term predictions interpret the intra-year variation of failure frequency, with most failures occurring during the coldest months. The exhaustive trials led to the conclusion that the use of four consecutive days as input and the following two days as output results in the highest accuracy. The analysis of the relative significance of each input variable indicates that the variables that capture the intensity of low temperatures are the most influential. The outputs of the impact assessment indicate that the failure of most of the pipes in both scenarios (i.e. peak in pressure and demand) would have low impacts (i.e. low ratio of unsupplied demand and small number of affected nodes). This can be explained by the fact that the examined network is a large real-life network, and a single failure of a distribution pipe is likely to cause pressure-deficient conditions in a small part of it, whereas performance elsewhere is mostly satisfactory. Furthermore, the complex structure of the WDN allows them to recover from local pipe failures, exploiting the topological redundancy provided by closed loops, so that the flow could reach a given demand node through alternative paths