Embedding the United Nations Sustainable Development Goals Into Energy Systems Analysis: Expanding the Food–Energy–Water Nexus

Background There have been numerous studies that consider the nexus interactions between energy systems, land use, water use and climate adaptation and impacts. These studies have filled a gap in the literature to allow for more effective policymaking by considering the trade-offs between land use, energy infrastructure as well as the use of water for agriculture and providing energy services. Though these studies fill a significant gap in the modelling literature, we argue that more work is needed to effectively consider policy trade-offs between the 17 United Nations sustainable development goals (SDGs) to avoid missing important interactions.   Results We examine the 17 SDGs individually to determine if it should be included in a modelling framework and the challenges of doing so. We show that the nexus of climate, land, energy and water needs to be expanded to consider economic well-being of both individuals and the greater economy, health benefits and impacts, as well as land use in terms of both food production and in terms of sustaining ecological diversity and natural capital. Such an expansion will allow energy systems models to better address the trade-offs and synergies inherent in the SDGs. Luckily, although there are some challenges with expanding the nexus in this way, we feel the challenges are generally modest and that many model structures can already incorporate many of these factors without significant modification.   Finally, we argue that SDGs 16 and 17 cannot be met without open-source models and open data to allow for transparent analysis that can be used and reused with a low cost of entry for modellers from less well-off nations.   Conclusions To effectively address the SDGs, there is a need to expand the common definition of the nexus of climate, land, energy, and water to include the synergies and trade-offs of health impacts, ecological diversity and the system requirements for human and environmental well-being. In most cases, expanding models to be able to incorporate these factors will be relatively straight forward, but open models and analysis are needed to fully support the SDGs

The geothermal potential of Clarke Lake and Milo gas fields in northeast British Columbia

The increasing consumption of energy and its side-effects on the environment are driving an international effort to enhance the use of more environmentally-friendly energy resources such as geothermal energy which this research addresses. The work has involved an analysis of data provided by the B.C. Ministry of Energy, Mines and Petroleum Resources collected from oil and gas wells drilled in the Northeast region of British Columbia for the purpose of evaluating the potential to exploit geothermal energy in the region. The study area was narrowed to two gas fields near Fort Nelson – Clarke Lake and Milo. The objectives of the project have been 1. to investigate the geothermal potential of the area; and, 2. to examine if non-geothermal wells could be used to recover geothermal energy; Using data gathered from the gas well log records, temperature gradient and heat flow maps were successfully generated for the study area using ArcGIS. A preliminary reservoir assessment has been done based on these maps. The results show the region has notably high potential for a deep geothermal project using Enhanced Geothermal System (EGS) methodologies to produce significant amounts of electrical energy for a very long time in a sustainable fashion. It is recommended that additional exploration and exploitation drilling should be done at Clarke Lake to verify the conclusions and strengthen the assumptions about suitable local rock permeability and fluid availability at depth. With respect to geothermal energy production from spent oil and gas wells, there is currently insufficient temperature and fluid flow to either recover heat for a district heating system in the nearby community of Fort Nelson or to generate electricity using a Binary Cycle process. The quantity of heat is too low to be an economically viable investment while the temperature is too low at the current gas plants to technically generate power. The research has demonstrated that data from drilled oil and gas wells when studied can be used with confidence to evaluate the geothermal potential of a region and should be applied to other locations in British Columbia and elsewhere to produce similar temperature gradient and heat flow maps.Applied Science, Faculty ofMining Engineering, Keevil Institute ofGraduat

Performance evaluation of ECMA-368 medium access control protocol for UWB ad-hoc networks

Ultra Wideband (UWB) is an emerging technology for high rate, short range wireless communications. Its unique features such as low power operation, robustness to multi-path fading, and accurate positioning capabilities makes UWB a good platform for wireless personal area networks (WPANs). One of the recent UWB standards standardized by the European Computer Manufacturers Association (ECMA) International is the ECMA- 368, which defines the physical (PHY) and media access control (MAC) layers for high rate WPANs. The MAC protocol in ECMA-368 has a superframe structure. Each superframe is divided into three different time periods. The beacon period is used for control purposes. The distributed reserved protocol (DRP) period allows devices to reserve bandwidth for data transmission. The PCA (prioritized contention access) period supports contention-based access between different traffic classes. In this thesis, we propose an analytical model to evaluate the performance of the ECMA-368 MAC protocol. We assume that packets follow the Markovian Arrival Process (MAP) and various service times can be modeled by different phase type distributions (PHYs). We apply the Matrix Geometric Method (MGM) technique and model the system as a MAP/PHY/1 queueing system. We derive the probability mass function (pmf) for the number of the packets in the queue, as well as the cumulative distribution function (CDF) for the waiting time of the packets in the queue. The correctness of our proposed analytical model is validated via simulations. We create the ECMA-368 module by using the OPNET simulator. Analytical and simulation results are presented under different scenariosScience, Faculty ofComputer Science, Department ofGraduat

Improving transport layer performance over multi-hop wireless networks by machine learning

The emerging use of multi-homed wireless devices along with simultaneous multi-path data transfer offers tremendous potentials to improve the capacity of multi-hop wireless networks. Concurrent Multi-path Transfer (CMT) over Stream Control Transmission Protocol (SCTP) is a form of reliable multi-path transport layer protocol with unique features that resonate with multi-path nature of the multi-hop wireless networks. The present thesis identifies and addresses some of the challenges of CMT-SCTP over wireless multi-hop networks. One main challenge raised by the multi-hop wireless network for CMT-SCTP is the out-of-order packet arrival. SCTP uses packet sequence number to ensure delivery. As such, the out-of-order packet arrival triggers receive buffer blocking in CMT-SCTP that causes throughput degradation. Another challenge in using CMT-SCTP over multi-hop wireless networks is the unfair resource allocation towards flows coming from farther away hops. The first part of this thesis focuses on integrating machine learning and network coding in CMT-SCTP to resolve the receive buffer blocking problem. Our state-of-the-art scheme uses Q-learning, a form of Reinforcement Learning (RL), to enable the network coding module to adjust to network dynamics. We confirm the veracity of our proposal by a queuing theory based mathematical model. Moreover, the effectiveness of the proposed scheme is demonstrated through simulations and testbed experiments. In the second part of the thesis, we investigate the fairness behavior of CMT-SCTP towards other CMT or non-CMT flows coming from farther away hops on a multi-hop wireless network. We introduce a Q-learning distributed mechanism to enhance fairness in CMT-SCTP. The proposed method uses Q-learning to acquire knowledge about the dynamics of the network. Consequently, the acquired knowledge is used to choose the best action to improve the fairness index of the network. We evaluate our proposal against standard CMT-SCTP and Resource Pool CMT-SCTP (CMT/RP-SCTP). In the third part of this thesis, we apply our findings in the second part to TCP to demonstrate that the benefits of our fairness mechanism can be extended to other transport layer protocols. The findings of this thesis bring us closer to realization of the vast potential of multi-path data transfer over multi-hop wireless networks.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat

Framework and maturity model to guide and evaluate corporate contributions to sustainable development of neighbouring communities : specific focus on geothermal power projects

The goal of this research is to present a new way of thinking (in the form of a framework) about how geothermal power projects can contribute to sustainable development (SD) in a way that harmonizes these projects with SD plans of their neighbouring communities. The research aims to create a SD approach for the greater geothermal power industry that is consistent with the expectations and values of today’s society. A framework, referred to as the Geothermal Sustainable Development (GSD) framework, is proposed aiming to guide and evaluate the contributions of a geothermal power project to SD in the local and regional communities. After developing the framework, to help companies and other interested parties to track and evaluate the progress of the project with respect to its approach towards SD, an evaluation strategy in the form of a maturity model is proposed. The maturity model aims to highlight the depth and quality of SD-thinking and its influence within a company/project development paradigm. The research is based on a combination of quantitative and qualitative research approaches to evaluate and test these outcomes. A survey was used that represents the quantitative research approach. This survey set out to assess whether the identified objectives presented in the framework are indeed suitable and effective as tools for the intended purposes of the framework. A second part of the research consisted of interviews (qualitative research approach) to evaluate the maturity model and its applications. Six case studies were discussed with interviewees. The developed framework can be used by the industry, communities, NGOs, and government as a starting-point to establish common ground in the development of geothermal power projects to focus the attention of everyone. It also provides the industry with an opportunity to assess their performance and communicate their approaches, contributions, and progress to the stakeholders and (possible) investors consistently and clearly. The combination of a GSD framework and the proposed SD maturity model could be used by any company at project and corporate levels that have already committed or are willing to commit to SD to evaluate their performance.Applied Science, Faculty ofMining Engineering, Keevil Institute ofGraduat

How network monitoring and reinforcement learning can improve tcp fairness in wireless multi-hop networks

Wireless mesh network (WMN) is an emerging technology for the last-mile Internet access. Despite extensive research and the commercial implementations of WMNs, there are still serious fairness issues in the transport layer, where the transmission control protocol (TCP) favors flows with a smaller number of hops to flows with a larger number of hops. TCP unfair behavior is a known anomaly over WMN that attracts much attention in recent years and is the focus of this paper. In this article, we propose a distributed network monitoring mechanism using a cross-layer approach that deploys reinforcement learning techniques (RL) to achieve fair resource allocation for nodes within the wireless mesh setting. In our approach, we deploy Q-learning, a reinforcement learning mechanism, to monitor the dynamics of the network. The Q-learning agent creates a state map of the network based on the medium access control (MAC) parameters and takes actions to enhance TCP fairness and throughput of the starved flows in the network. The proposal creates a distributed cooperative mechanism where each node hosting a TCP source monitors the network and adjusts its TCP parameters based on the network dynamics. Extensive simulation results and testbed analysis demonstrate that the proposed method significantly improves the TCP fairness in a multi-hop wireless environment.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofReviewedFacult

Electrification policy impacts on land system in British Columbia, Canada

British Columbia (BC) is committed to transitioning to a low-carbon energy system to meet its CO2 emission reduction targets, but this shift towards renewable energy sources may have significant implications for land use. This paper investigates the land-use impacts of different electrification pathways and technology choices in BC's energy system using the BC Nexus model. Our analysis highlights the potential increase in land-use requirements associated with transitioning from fossil fuels to renewable energy sources, with the occupied land of the power system potentially increasing up to six times larger than the current total build-up land (depending on the scale of electrification and technology choice). These findings have important implications for policymakers in terms of balancing the trade-offs between energy security, economic development, and environmental sustainability. By understanding the physical footprint of the energy transition, decision-makers can develop more effective climate policies and sustainable development strategies