64 research outputs found
Green Technologies for Production Processes
This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies
Internet of things (IoT) based adaptive energy management system for smart homes
PhD ThesisInternet of things enhances the flexibility of measurements under different environments, the
development of advanced wireless sensors and communication networks on the smart grid
infrastructure would be essential for energy efficiency systems. It makes deployment of a
smart home concept easy and realistic. The smart home concept allows residents to control,
monitor and manage their energy consumption with minimal wastage. The scheduling of
energy usage enables forecasting techniques to be essential for smart homes. This thesis
presents a self-learning home management system based on machine learning techniques
and energy management system for smart homes.
Home energy management system, demand side management system, supply side management system, and power notification system are the major components of the proposed
self-learning home management system. The proposed system has various functions including price forecasting, price clustering, power forecasting alert, power consumption alert, and
smart energy theft system to enhance the capabilities of the self-learning home management
system. These functions were developed and implemented through the use of computational
and machine learning technologies. In order to validate the proposed system, real-time power
consumption data were collected from a Singapore smart home and a realistic experimental
case study was carried out. The case study had proven that the developed system performing
well and increased energy awareness to the residents. This proposed system also showcases its customizable ability according to different types of environments as compared to
traditional smart home models.
Forecasting systems for the electricity market generation have become one of the foremost
research topics in the power industry. It is essential to have a forecasting system that can
accurately predict electricity generation for planning and operation in the electricity market.
This thesis also proposed a novel system called multi prediction system and it is developed
based on long short term memory and gated recurrent unit models. This proposed system is
able to predict the electricity market generation with high accuracy.
Multi Prediction System is based on four stages which include a data collecting and
pre-processing module, a multi-input feature model, multi forecast model and mean absolute
percentage error. The data collecting and pre-processing module preprocess the real-time
data using a window method. Multi-input feature model uses single input feeding method,
double input feeding method and multiple feeding method for features input to the multi
forecast model. Multi forecast model integrates long short term memory and gated recurrent
unit variations such as regression model, regression with time steps model, memory between
batches model and stacked model to predict the future generation of electricity. The mean
absolute percentage error calculation was utilized to evaluate the accuracy of the prediction.
The proposed system achieved high accuracy results to demonstrate its performance
Integrated feedstock optimisation for multi-product polymer production
Thesis (PhD)--Stellenbosch University, 2022.ENGLISH ABSTRACT: A chemical complex can have multiple value chains, some of which may
span across geographical locations. Decisions regarding the distribution
of feedstock and intermediate feedstock to different production units can
occur at different time intervals. This is highlighted as two problems, a
feedstock distribution problem and an intermediate feedstock distribution
problem. Unexpected events can cause an imbalanced value chain which
requires timely decision-making to mitigate further adverse consequences.
Scheduling methods can provide decision support during such events. The
purpose of this research study is to develop an integrated decision support
system which handles the two problems as a single problem and maximises
profit in the value chain for hourly and daily decision-making. A high-level
DSS architecture is presented that incorporates metaheuristic algorithms
to generate production schedules for distribution of feedstock through the
value chain. The solution evaluation process contains a balancing period
to enable the application of metaheuristics to this type of problem and
a novel encoding scheme is proposed for the hourly interval problem. It
was found that metaheuristics algorithms can be used for this problem
and integrated into the proposed decision support system.AFRIKAANSE OPSOMMING: ’n Chemiese kompleks kan verskeie waardekettings hê, waarvan sommige
oor geografiese gebiede strek. Besluite rakende die verspreiding van grondstowwe en intermediêre grondstowwe na verskillende produksie-eenhede
kan op verskillende tydsintervalle plaasvind. Dit word uitgelig as twee
probleme: ’n probleem met die verspreiding van grondstowwe en ’n intermediêre grondstowwe verspreidingsprobleem. Onverwagte gebeure kan
’n ongebalanseerde waardeketting veroorsaak wat tydige besluitneming
benodig om verdere gevolge te versag. Beplanningsmetodes kan ondersteuning bied tydens sulke geleenthede. Die doel van hierdie navorsingstudie was om ’n geïntegreerde stelsel vir besluitnemingsondersteuning oor die twee probleme as een probleem te ontwikkel, wat wins in die
waardeketting vir uurlikse en daaglikse besluitneming maksimeer. ’n Hoëvlak DSS-argitektuur word aangebied met metaheuristieke om produksieskedules vir verspreidingstowwe deur die waardeketting te genereer.
Die oplossingsevalueringsproses bevat ’n balanseerperiode om die metaheuristiek op hierdie tipe probleme toe te pas, en ’n nuwe koderingskema
word voorgestel vir die uurlikse intervalprobleem. Die gevolgtrekking word gemaak dat metaheuristieke vir hierdie probleem gebruik kan word
en ge¨ıntegreer kan word in die voorgestelde ondersteuningsstelsel vir besluitneming.Doctora
Situation Awareness for Smart Distribution Systems
In recent years, the global climate has become variable due to intensification of the greenhouse effect, and natural disasters are frequently occurring, which poses challenges to the situation awareness of intelligent distribution networks. Aside from the continuous grid connection of distributed generation, energy storage and new energy generation not only reduces the power supply pressure of distribution network to a certain extent but also brings new consumption pressure and load impact. Situation awareness is a technology based on the overall dynamic insight of environment and covering perception, understanding, and prediction. Such means have been widely used in security, intelligence, justice, intelligent transportation, and other fields and gradually become the research direction of digitization and informatization in the future. We hope this Special Issue represents a useful contribution. We present 10 interesting papers that cover a wide range of topics all focused on problems and solutions related to situation awareness for smart distribution systems. We sincerely hope the papers included in this Special Issue will inspire more researchers to further develop situation awareness for smart distribution systems. We strongly believe that there is a need for more work to be carried out, and we hope this issue provides a useful open-access platform for the dissemination of new ideas
A Polyhedral Study of Mixed 0-1 Set
We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set
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