42 research outputs found

    Uncertain Multi-Criteria Optimization Problems

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    Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

    Future Transportation

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    Greenhouse gas (GHG) emissions associated with transportation activities account for approximately 20 percent of all carbon dioxide (co2) emissions globally, making the transportation sector a major contributor to the current global warming. This book focuses on the latest advances in technologies aiming at the sustainable future transportation of people and goods. A reduction in burning fossil fuel and technological transitions are the main approaches toward sustainable future transportation. Particular attention is given to automobile technological transitions, bike sharing systems, supply chain digitalization, and transport performance monitoring and optimization, among others

    Low-carbon Energy Transition and Planning for Smart Grids

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    With the growing concerns of climate change and energy crisis, the energy transition from fossil-based systems to a low-carbon society is an inevitable trend. Power system planning plays an essential role in the energy transition of the power sector to accommodate the integration of renewable energy and meet the goal of decreasing carbon emissions while maintaining the economical, secure, and reliable operations of power systems. In this thesis, a low-carbon energy transition framework and strategies are proposed for the future smart grid, which comprehensively consider the planning and operation of the electricity networks, the emission control strategies with the carbon response of the end-users, and carbon-related trading mechanisms. The planning approach considers the collaborative planning of different types of networks under the smart grid context. Transportation electrification is considered as a key segment in the energy transition of power systems, so the planning of charging infrastructure for electric vehicles (EVs) and hydrogen refueling infrastructure for fuel cell electric vehicles is jointly solved with the electricity network expansion. The vulnerability assessment tools are proposed to evaluate the coupled networks towards extreme events. Based on the carbon footprint tracking technologies, emission control can be realized from both the generation side and the demand side. The operation of the low-carbon oriented power system is modeled in a combined energy and carbon market, which fully considers the carbon emission right trading and renewable energy certificates trading of the market participants. Several benchmark systems have been used to demonstrate the effectiveness of the proposed planning approach. Comparative studies to existing approaches in the literature, where applicable, have also been conducted. The simulation results verify the practical applicability of this method

    A Generalized Optimal Planning Platform for Microgrids of Remote Communities Considering Frequency and Voltage Regulation Constraints

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    Access to electricity is a key factor behind development and expansion of modern societies, and electric power systems are the backbone infrastructure for economic growth of nations and communities. However, more than a billion people all over the world have no or limited access to electricity and are deprived of basic services. Furthermore, there are many communities that rely on small-scale isolated microgrids to supply their electric power demands, and many challenges exist in keeping those microgrids operating. The cost of operating isolated microgrids is a major issue which impacts the availability of a proper power network in remote communities. Hence, many organizations, communities and governments around the world are looking into alternative options for electrification of remote communities by considering Renewable Energy (RE) resources, such as wind and solar power, and utilization of Energy Storage Systems (ESS). This thesis investigates the feasibility of RE deployment in remote communities, by proposing a generalized optimal planning platform and conducting comprehensive simulation studies based on real measured data, and evaluates the impact of economic, technical and operation constraints on the planning of an isolated microgrid involving conventional generation, RE resources and ESS. This work suggests that further investigation should be made on the potential impacts of the integration of RE resource on systems operation constraints, such as frequency and voltage regulation, and the results justify the importance of such investigations. Detailed studies on the impact of operation constraints on the planning and sizing of the microgrid are performed. The impact of ESS on planning studies and its potential role in system operation are analyzed. Furthermore, the impact of RE integration on reduction of diesel generation and thus carbon footprint in remote communities is evaluated. The inclusion of a demand response management strategy in microgrid planning problem is considered and its impact on the integration of RE and ESS in remote communities is analyzed. The proposed planning platform is applied to the microgrid of Kasabonika Lake First Nation (KLFN), a northern Ontario remote community. The results indicate that RE and ESS integration projects are achievable considering alternative incentives and funding resources. It is also shown that frequency regulation constraints have remarkable impact on the sizing of the RE units and ESS. A sensitivity analysis is also performed in order to study the effect of variable parameters on the optimal design of the microgrid at KLFN

    Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

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    The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios
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