Multi-agent control and operation of electric power distribution systems

This dissertation presents operation and control strategies for electric power distribution systems containing distributed generators. First, models of microturbines and fuel cells are developed. These dynamic models are incorporated in a power system analysis package. Second, operation of these generators in a distribution system is addressed and load following schemes are designed. The penetration of distributed generators (DGs) into the power distribution system stability becomes an issue and so the control of those DGs becomes necessary. A decentralized control structure based on conventional controllers is designed for distributed generators using a new developed optimization technique called Guided Particle Swarm Optimization. However, the limitations of the conventional controllers do not satisfy the stability requirement of a power distribution system that has a high DG penetration level, which imposes the necessity of developing a new control structure able to overcome the limitations imposed by the fixed structure conventional controllers and limit the penetration of DGs in the overall transient stability of the distribution system. Third, a novel multi-agent based control architecture is proposed for transient stability enhancement for distribution systems with microturbines. The proposed control architecture is hierarchical with one supervisory global control agent and a distributed number of local control agents in the lower layer. Specifically, a central control center supervises and optimizes the overall process, while each microturbine is equipped with its own local control agent.;The control of naval shipboard electric power system is another application of distributed control with multi-agent based structure. In this proposal, the focus is to introduce the concept of multi-agent based control architecture to improve the stability of the shipboard power system during faulty conditions. The effectiveness of the proposed methods is illustrated using a 37-bus IEEE benchmark system and an all-electric naval ship

A unified framework for digital twin development in manufacturing

The concept of digital twin (DT) is undergoing rapid transformation and attracting increased attention across industries. It is recognised as an innovative technology offering real-time monitoring, simulation, optimisation, accurate forecasting and bi-directional feedback between physical and digital objects. Despite extensive academic and industrial research, DT has not yet been properly understood and implemented by many industries, due to challenges identified during its development. Existing literature shows that there is a lack of a unified framework to build DT, a lack of standardisation in the development, and challenges related to coherent goals of DT in a multi-disciplinary team engaged in the design, development and implementation of DT to a larger scale system. To address these challenges, this study introduces a unified framework for DT development, emphasising reusability and scalability. The framework harmonises existing DT frameworks by unifying concepts and process development. It facilitates the integration of heterogeneous data types and ensures a continuous flow of information among data sources, simulation models and visualisation platforms. Scalability is achieved through ontology implementation, while employing an agent-based approach, it monitors physical asset performance, automatically detects faults, checks repair status and offers operators feedback on asset demand, availability and health conditions. The effectiveness of the proposed DT framework is validated through its application to a real-world case study involving five interconnected air compressors located at the Connected Facility at Devonport Royal Dockyard, UK. The DT automatically and remotely monitors the performance and health status of compressors, providing guidance to humans on fault repair. This guidance dynamically adapts based on feedback from the DT. Analyses of the results demonstrate that the proposed DT increases the facility’s operation availability and enhances decision-making by promptly and accurately detecting faults.This research was funded by the supported by the EPSRC, UK as part of the ‘Digital Toolkit for optimisation of operators and technology in manufacturing partnerships’ project (DigiTOP; https://digitop.ac.uk; EP/R032718/1), the Centre for Digital Engineering and Manufacturing at Cranfield University and Babcock International

Controllers, observers, and applications thereof

Controller scaling and parameterization are described. Techniques that can be improved by employing the scaling and parameterization include, but are not limited to, controller design, tuning and optimization. The scaling and parameterization methods described here apply to transfer function based controllers, including PID controllers. The parameterization methods also apply to state feedback and state observer based controllers, as well as linear active disturbance rejection (ADRC) controllers. Parameterization simplifies the use of ADRC. A discrete extended state observer (DESO) and a generalized extended state observer (GESO) are described. They improve the performance of the ESO and therefore ADRC. A tracking control algorithm is also described that improves the performance of the ADRC controller. A general algorithm is described for applying ADRC to multi-input multi-output systems. Several specific applications of the control systems and processes are disclosed

Decision support method for contracting of non-original equipment manufacturer aero engine maintenance repair and overhaul service providers.

Non-Original Equipment Manufacturer (Non-OEM) Maintenance Repair and Overhaul (MRO) service providers of aero-engines are facing challenges resulting from the rapidly changing MRO market. They need to offer innovative service solutions to airlines through, for example, PSS (Product Service Systems) offerings that combine service(s) and products. PSS can be achieved by either servitisation to add service offerings to products or productisation to add tangible products to service offerings. Currently, however, MRO contracts that include PSS offerings have been prepared based on experiences and intuitions. Ideally, these contracts should be designed to bring about a win-win situation for both airlines (as customers) and MRO service providers. This research aims to develop a new robust, scientific method to prepare contracts for decision makers of non-OEM MRO service providers. The research began with studying current general situation of the PSS in the aero-engine MRO market as well as, in particular, of a Non-OEM MRO service provider. From these, this research first identified sufficient key parameters that describe MRO operations with regard to flight operations of customer airline. A computer-based simulation model was built to assess the capacity and capability of the shop floor operations taking flight operations of the customer into consideration using the discrete event simulation. The simulation model was run over a set of systematically and exhaustively created combinations of different types of services and products. This has helped in selecting the most favourable combinations services and products, which can lead to the win-win situation for both the airlines and the MRO service providers.PhD in Manufacturin

Performance based diagnostics of a twin shaft aeroderivative gas turbine: water wash scheduling

Aeroderivative gas turbines are used all over the world for different applications as Combined Heat and Power (CHP), Oil and Gas, ship propulsion and others. They combine flexibility with high efficiencies, low weight and small footprint, making them attractive where power density is paramount as off shore Oil and Gas or ship propulsion. In Western Europe they are widely used in CHP small and medium applications thanks to their maintainability and efficiency. Reliability, Availability and Performance are key parameters when considering plant operation and maintenance. The accurate diagnose of Performance is fundamental for the plant economics and maintenance planning. There has been a lot of work around units like the LM2500® , a gas generator with an aerodynamically coupled gas turbine, but nothing has been found by the author for the LM6000® . Water wash, both on line or off line, is an important maintenance practice impacting Reliability, Availability and Performance. This Thesis aims to select and apply a suitable diagnostic technique to help establishing the schedule for off line water wash on a specific model of this engine type. After a revision of Diagnostic Methods Artificial Neural Network (ANN) has been chosen as diagnostic tool. There was no WebEngine model available of the unit under study so the first step of setting the tool has been creating it. The last step has been testing of ANN as a suitable diagnostic tool. Several have been configured, trained and tested and one has been chosen based on its slightly better response. Finally, conclusions are discussed and recommendations for further work laid out

CCGT performance simulation and diagnostics for operations optimisation and risk management

This thesis presents a techno-economic performance simulation and diagnostics computational system for the operations optimisation and risk management of a CCGT power station. The project objective was to provide a technological solution to a business problem originated at the Manx Electricity Authority (MEA). The CCGT performance simulation program was created from the integration of existing and new performance simulation codes of the main components of a CCGT power station using Visual Basic for Applications (VBA) in Excel ®. The specifications of the real gas turbine (GT) engines at MEA demanded the modification of Turbomatch, a GT performance simulation code developed at Cranfield University. The new capabilities were successfully validated against previous work in the public domain. In the case of the steam cycle, the model for a double pressure once-through steam generator (OTSG) was produced. A novel approach using theoretical thermohydraulic models for heat exchangers and empiric correlations delivered positive results. Steamomatch, another code developed at the university, was used for the steam turbine performance simulation. An economic module based on the practitioners’ definition for spark spread was developed. The economic module makes use of the technical results, which are permanently accessible through the user interface of the system. The assessment of an existing gas turbine engine performance diagnostics system, Pythia, was made. The study tested the capabilities of the program under different ambient and operating conditions, signal noise levels and sensor faults. A set of guidelines aimed to increase the success rate of the diagnostic under the data and sensor restricted scenario presented by at MEA was generated. Once the development phase was concluded, technical and economic studies on the particular generation schedule for a cold day of winter 2007 were conducted. Variable ambient and operating conditions for each of the 48 time block forming the schedule were considered. The results showed error values below the 2% band for key technical parameters such as fuel flow, thermal efficiency and power output. On the economic side, the study quantified the loss making operation strategy of the plant during the offpeak market period of the day. But it also demonstrated the profit made during the peak hours lead to an overall positive cash flow for the day. A number of optimisation strategies to increase the profitability of the plant were proposed highlighting the economic benefit of them. These scenarios were based on the technical performance simulation of the plant under these specific conditions, increasing the reliability of the study. Finally, a number of risk management strategies aimed to protect the operations of a power generator from the main technical and economic risk variables were outlined. It was concluded that the use of techno-economic advanced tools such as eCCGT and Pythia can positively affect the way an operator manages a power generation asset through the implementation of virtually proven optimisation and risk management strategies.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Analysis of gas turbine compressor fouling and washing on line

This work presents a model of the fouling mechanism and the evaluation of compressor washing on line. The results of this research were obtained from experimental and computational models. The experimental model analyzed the localization of the particle deposition on the blade surface and the change of the surface roughness condition. The design of the test rig was based on the cascade blade arrangement and blade aerodynamics. The results of the experiment demonstrated that fouling occurred on both surfaces of the blade. This mechanism mainly affected the leading edge region of the blade. The increment of the surface roughness on this region was 1.0 μm. This result was used to create the CFD model (FLUENT). According to the results of the CFD, fouling reduced the thickness of the boundary layer region and increased the drag force of the blade. The model of fouling was created based on the experiment and CFD results and was used to calculate the engine performance in the simulation code (TURBOMATCH). The engine performance results demonstrated that in five days fouling can affect the overall efficiency by 3.5%. The evaluation of the compressor washing on line was based on the experimental tests and simulation of the engine performance. This system demonstrated that it could recover 99% of the original blade surface. In addition, this system was evaluated in a study case of a Power Plant, where it proved itself to be a techno-economic way to recover the power of the engine due to fouling. The model of the fouling mechanism presented in this work was validated by experimental tests, CFD models and information from real engines. However, for further applications of the model, it would be necessary to consider the specific conditions of fouling in each new environment.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Towards Developing a Digital Twin Implementation Framework for Manufacturing Systems

This research studies the implementation of digital twins in manufacturing systems. Digital transformation is relevant due to changing manufacturing techniques and user demands. It brings new business opportunities, changes organizations, and allows factories to compete in the digital era. Nevertheless, digital transformation presents many uncertainties that could bring problems to a manufacturing system. Some potential problems are loss of data, cybersecurity threats, unpredictable behavior, and so on. For instance, there are doubts about how to integrate the physical and virtual spaces. Digital twin (DT) is a modern technology that can enable the digital transformation of manufacturing companies. DT works by collecting real-time data of machines, products, and processes. DT monitors and controls operations in real-time helping in the identification of problems. It performs simulations to improve manufacturing processes and end-products. DT presents several benefits for manufacturing systems. It gives feedback to the physical system, increases the system’s reliability and availability, reduces operational risks, helps to achieve organizational goals, reduces operations and maintenance costs, predicts machine failures, etc. DT presents all these benefits without affecting the system’s operation. xv This dissertation analyzes the implementation of digital twins in manufacturing systems. It uses systems thinking methods and tools to study the problem space and define the solution space. Some of these methods are the conceptagon, systemigram, and the theory of inventive problem solving (TRIZ in Russian acronym). It also uses systems thinking tools such as the CATWOE, the 9-windows tool, and the ideal final result (IFR). This analysis gives some insights into the digital twin implementation issues and potential solutions. One of these solutions is to build a digital twin implementation framework Next, this study proposes the development of a small-scale digital twin implementation framework. This framework could help users to create digital twins in manufacturing systems. The method to build this framework uses a Model-Based Systems Engineering approach and the systems engineering “Vee” model. This framework encompasses many concepts from the digital twin literature. The framework divides these concepts along three spaces: physical, virtual, and information. It also includes other concepts such as digital thread, data, ontology, and enabling technologies. Finally, this dissertation verifies the correctness of the proposed framework. The verification process shows that the proposed framework can develop digital twins for manufacturing systems. For that purpose, this study creates a process digital twin simulation using the proposed framework. This study presents a mapping and a workflow diagram to help users use the proposed framework. Then, it compares the digital twin simulation with the digital twin user and system requirements. The comparison finds that the proposed framework was built right

Regional technology framework: evidence pack

The evidence pack is a body of evidence collected to support the strategic prioritisation contained in the Regional Technology Framework (RTF)