Towards an Agent Based Framework for Modelling Smart Self-Sustainable Systems

Self-sustainability is a property of a system; a system is considered to be self-sustainable if it can sustain itself without external support in an observed period of time. If this property is mapped to a human settlement in context of resources (water, energy, food, etc.), it would describe a human settlement which is independent of external resources (like the national electrical grid or a central water distribution system), where such external resources are either not available, or not desirable. This article contributes to presenting the state-of-the-art overview of self-sustainability-related research. While self-sustainability as in the above described form was not a direct subject of research, there are several fields which are either related to, or could be of significant value to the self-sustainability research in this context. The extensive literature overview also showed no frameworks for modeling self sustainable systems in the context of human settlements. Herein a motivation for using agent-based modeling and simulation techniques will be given

Simplified Environment Control System For Prototype Vertical Farm

Farming is one of the fundamental inventions that promoted the flourishing or human species on planet earth. Since many centuries have past, this fundamental invention namely the conventional way of it has become reverse which is promoting extinction. Conventional farming has led to many unsustainable acts such as deforestation, heavy use of pesticides and insecticides, feces as fertilizers, open burning and creation of cities. These acts in turn backfired resulting in global warming, extreme climate change (drought, flood, hurricanes etc), exponential rise in human population resulting in consumption of resources over the replenishing rate, pollution of water sources, diseases spreading such as typhoid and cholera. The very main reason such occurrence is because of direct interaction of farming with nature. Farming is not a natural behavior of an ecosystem (Despommier, 2009). It is a creation of human beings to increase its survival rate. Hence in a simple mathematical equation, if we remove farming from nature and put it in a closed system which resembles the nature ecosystem, we can remove the potential unsustainable acts of farming. The concept of vertical farming is to remove the factor of farming from nature to undo the bad deeds before it is too late. This simplistic solution might seem like a dreamer’s solution and appear to be impractical due to its high costs. To prove that argument wrong, this research will show the latest breakthrough in the agriculture industry in growing plants in a building and too how far is a vertical farm concept farfetched? Thus, this research will be proposing to construct simplified miniature 3 storeys vertical farm system that uses hydroponic system and govern by an expert system using the methodology proposed by CLAE

Overcoming information asymmetry in the plastics value chain with digital product passports : how decentralised identifiers and verifiable credentials can enable a circular economy for plastics

This paper analyses the potential of digital information technology to enable the reliable provision of product information along the plastics supply chain. The authors investigate the possible contribution of a product passport equipped with decentralised identifiers and verifiable credentials to overcome information deficits and information asymmetry in the circular plastics economy. Through this, high-quality plastics recycling could be enabled on a larger scale than currently possible

Integration of e-business strategy for multi-lifecycle production systems

Internet use has grown exponentially on the last few years becoming a global communication and business resource. Internet-based business, or e-Business will truly affect every sector of the economy in ways that today we can only imagine. The manufacturing sector will be at the forefront of this change. This doctoral dissertation provides a scientific framework and a set of novel decision support tools for evaluating, modeling, and optimizing the overall performance of e-Business integrated multi-lifecycle production systems. The characteristics of this framework include environmental lifecycle study, environmental performance metrics, hyper-network model of integrated e-supply chain networks, fuzzy multi-objective optimization method, discrete-event simulation approach, and scalable enterprise environmental management system design. The dissertation research reveals that integration of e-Business strategy into production systems can alter current industry practices along a pathway towards sustainability, enhancing resource productivity, improving cost efficiencies and reducing lifecycle environmental impacts. The following research challenges and scholarly accomplishments have been addressed in this dissertation: Identification and analysis of environmental impacts of e-Business. A pioneering environmental lifecycle study on the impact of e-Business is conducted, and fuzzy decision theory is further applied to evaluate e-Business scenarios in order to overcome data uncertainty and information gaps; Understanding, evaluation, and development of environmental performance metrics. Major environmental performance metrics are compared and evaluated. A universal target-based performance metric, developed jointly with a team of industry and university researchers, is evaluated, implemented, and utilized in the methodology framework; Generic framework of integrated e-supply chain network. The framework is based on the most recent research on large complex supply chain network model, but extended to integrate demanufacturers, recyclers, and resellers as supply chain partners. Moreover, The e-Business information network is modeled as a overlaid hypernetwork layer for the supply chain; Fuzzy multi-objective optimization theory and discrete-event simulation methods. The solution methods deal with overall system parameter trade-offs, partner selections, and sustainable decision-making; Architecture design for scalable enterprise environmental management system. This novel system is designed and deployed using knowledge-based ontology theory, and XML techniques within an agent-based structure. The implementation model and system prototype are also provided. The new methodology and framework have the potential of being widely used in system analysis, design and implementation of e-Business enabled engineering systems

The Plant Growth Promoting Ability of the Microbiome of \u3cem\u3eCeanothus velutinus\u3c/em\u3e from the Intermountain West Region

Due to the ever-changing climate and deterioration of the earth’s ecosystem, environmental stresses like abiotic (drought, salinity) and biotic stresses (pathogen infection) gravely affected plant growth. Native plants are a great way of improving these effects on the urban landscape. They can be used as ornamental plants in landscaping as they are accustomed to their natural environment. The Center for Water-Efficient Landscaping at Utah State University has released a list of plants to be used for low water use landscaping. One such native plant is Ceanothus velutinus (snowbrush ceanothus). They are evergreen plants that can grow in dry and harsh conditions and are native to the Intermountain West region of North America. This study focused on the effect of rhizosphere and endosphere microbiome on the growth and development of snowbrush ceanothus plants. A comparative metagenomic study in the bulk soil, rhizosphere, and endosphere of snowbrush ceanothus revealed the microbial diversity and presence of several plant growth promoting rhizobacteria (PGPR). So next, the effect of this native soil was observed on the growth and development of snowbrush ceanothus under the greenhouse conditions. Inoculation of native soil to the propagation media enhanced the rooting and survival rate of snowbrush ceanothus cuttings. The inoculation of native soil in the snowbrush ceanothus plants developed from cutting propagation and seedlings in the greenhouse revealed an improved growth compared to control plants. The metagenomic study of the rhizosphere and endosphere of snowbrush ceanothus plants treated with native soil revealed the presence of several PGPR that were absent in the control plants. Nodulation was observed for the first time in snowbrush ceanothus plants grown in the greenhouse and inoculated with native soil. So finally, an attempt was made to isolate as many PGPR species as possible from the rhizosphere and endosphere of snowbrush ceanothus plants. Many of these isolates tested positive for one or more specific traits such as siderophore production, indole acetic acid production, catalase production, nitrogen fixation, and phosphate solubilization. The isolates were further tested for their plant growth-promoting properties in plants. We found many of these bacterial isolates could potentially be used as bio-fertilizers or bio-stimulants

Future strategic plan analysis for integrating distributed renewable generation to smart grid through wireless sensor network: Malaysia prospect

AbstractIntegration of Distributed Renewable Generation (DRG) to the future Smart Grid (SG) is one of the important considerations that is highly prioritized in the SG development roadmap by most of the countries including Malaysia. The plausible way of this integration is the enhancement of information and bidirectional communication infrastructure for energy monitoring and controlling facilities. However, urgency of data delivery through maintaining critical time condition is not crucial in these facilities. In this paper, we have surveyed state-of-the-art protocols for different Wireless Sensor Networks (WSNs) with the aim of realizing communication infrastructure for DRG in Malaysia. Based on the analytical results from surveys, data communication for DRG should be efficient, flexible, reliable, cost effective, and secured. To meet this achievement, IEEE802.15.4 supported ZigBee PRO protocol together with sensors and embedded system is shown as Wireless Sensor (WS) for DRG bidirectional network with prospect of attaining data monitoring facilities. The prospect towards utilizing ZigBee PRO protocol can be a cost effective option for full integration of intelligent DRG and small scale Building-Integrated Photovoltaic (BIPV)/Feed-in-Tariff (FiT) under SG roadmap (Phase4: 2016–2017) conducted by Malaysia national utility company, Tenaga Nasional Berhad (TNB). Moreover, we have provided a direction to utilize the effectiveness of ZigBee-WS network with the existing optical communication backbone for data importing from the end DRG site to the TNB control center. A comparative study is carried out among developing countries on recent trends of SG progress which reveals that some common projects like smart metering and DRG integration are on priority

Assessment of novel distributed control techniques to address network constraints with demand side management

The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid.The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid

Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits