73 results found
Bustos-Turu G, van Dam KH, Acha S, et al., 2023, An agent-based decision support framework for a prospective analysis of transport and heat electrification in urban areas, Energies, Vol: 16, ISSN: 1996-1073
One of the main pathways that cities are taking to reduce greenhouse gas emissions is the decarbonisation of the electricity supply in conjunction with the electrification of transport and heat services. Estimating these future electricity demands, greatly influenced by end-users’ behaviour, is key for planning energy systems. In this context, support tools can help decision-makers assess different scenarios and interventions during the design of new planning guidelines, policies, and operational procedures. This paper presents a novel bottom-up decision support framework using an agent-based modelling and simulation approach to evaluate, in an integrated way, transport and heat electrification scenarios in urban areas. In this work, an open-source tool named SmartCityModel is introduced, where agents represent energy users with diverse sociodemographic and technical attributes. Based on agents’ behavioural rules and daily activities, vehicle trips and building occupancy patterns are generated together with electric vehicle charging and building heating demands. A representative case study set in London, UK, is shown in detail, and a summary of more than ten other case studies is presented to highlight the flexibility of the framework to generate high-resolution spatiotemporal energy demand profiles in urban areas, supporting decision-makers in planning low-carbon and sustainable cities.
Yang L, Iwami M, Chen Y, et al., 2023, Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review, PROGRESS IN PLANNING, Vol: 168, ISSN: 0305-9006
Yang L, Iwami M, Chen Y, et al., 2023, A Systematic Review of Urban Design and Computer Modelling Methods to Support Smart City Development in a Post-COVID Era, Pages: 1234-1246, ISBN: 9789811952166
The COVID-19 pandemic emphasised the need for decision-support tools to assist urban designers in building resilient and smart cities. Therefore, a multi-disciplinary systematic review was conducted following the PRISMA guideline to identify papers relevant for selecting appropriate methodologies that can be applied to build decision-support tools for resilient cities. This paper presents a list of 109 key references, selected from 8,737 records found from the searches, and identified major research themes, fundamental design interventions, and computer modelling techniques. We extracted six groups of interventions categorised by different scales of action: from an individual, crowds (social distancing and travel-related interventions), to a building, a neighbourhood/district, and a city. In addition, there are three sorts of computational modelling approaches, i.e., computer simulation, statistical models, and AI algorithms. Most of the studies developed models for predictive purposes, and 28% of the modelling studies built models for descriptive purposes. This work intends to empower urban designers and planners to overcome and get prepared for unpredictable disasters in pursuit of resilient and smart cities, particularly in the post-pandemic world. This review enables them to quickly find relevant papers as well as suitable methodologies and tools for a particular research purpose.
Yang L, Majumdar A, van Dam KH, et al., 2022, Theories and practices for reconciling transport, public space, and people - a review, PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-MUNICIPAL ENGINEER, Vol: 175, Pages: 187-203, ISSN: 0965-0903
Yang L, van Dam KH, 2022, Data-Driven Agent-Based Model Development to Support Human-Centric Transit-Oriented Design, Editors: Melo, Fang, Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 60-66, ISBN: 978-3-031-20178-3
Pedro MS, Hardy J, Van Dam K, 2021, Agent-based simulation to assess the impact of electric vehicles on power networks: Swindon Borough Case Study, The 10th International Workshop on Agent-based Mobility, Traffic and Transportation Models, (ABMTRANS), Publisher: Elsevier, Pages: 668-673, ISSN: 1877-0509
Due to air quality concerns and stricter carbon targets, surface transport electrification is quickly spreading, posing questions on the impact it will have on national and local electrical networks. This paper proposes an agent-based model to assess the per-minute weekday and weekend impact of the uptake of Electric Vehicles (EVs) over the next decade on local electrical and charging infrastructures, aimed at local decision-makers and stakeholders for transport electrification forecasting purposes. This study compares two scenarios, the first assessing the case where no restrictions are imposed on the daily charging events, and the second scenario where the peak electrical demand period between 5pm and 8.30pm is constrained for charging. Swindon Borough is selected as case study since it has one of UK’s highest EV adoption rates and has ambitious aims for decarbonisation. The results show that, over time, scenario two consistently lessened the constraints imposed on the grid by lowering the weekday and weekend peak loads up to 7% and 20%, respectively, and through lowering the usage rate of the charging infrastructure by around 12%. This scenario postponed the 5pm to 8.30pm EV charging demand to later hours, resulting in delayed load waves in residential areas that, over time, took values of higher proportion of the daily peak, forecasted to match it by 2036. However, controlling the EV demand through this strategy became less effective over time, and so, constraining charging between 7am and 2.30pm is suggested for further control. To conclude, this scenario can be portrayed in reality by adding flexibility to the grid, through the use of time-of-use tariffs (TOUTs), hence, if well implemented, postponing the upgrade of the grid and the charging infrastructure, presenting savings to the network operator, charging network stakeholders and EV users. The paper thus highlights the advantages of using a model of a heterogeneous population with fine spatial and te
Yang L, Zhang L, Philippopoulos-Mihalopoulos A, et al., 2021, Integrating agent-based modeling, serious gaming, and co-design for planning transport infrastructure and public spaces, URBAN DESIGN INTERNATIONAL, Vol: 26, Pages: 67-81, ISSN: 1357-5317
Yang L, van Dam KH, Zhang L, 2020, Developing Goals and Indicators for the Design of Sustainable and Integrated Transport Infrastructure and Urban Spaces, SUSTAINABILITY, Vol: 12
Cremi MR, Pantaleo AM, van Dam KH, et al., 2020, Optimal design and operation of an urban energy system applied to the Fiera Del Levante exhibition centre, Applied Energy, Vol: 275, Pages: 1-22, ISSN: 0306-2619
To move from centralised fossil fuel-based energy systems, synergies between distributed renewable generation, storage and demand-side strategies can be exploited to lower environmental impact and costs. This paper proposes an optimisation model for the techno-economic assessment of energy management strategies with a short-term investment horizon aimed at business managers and decision-makers in the commercial sector. The main novelty is the selection of a combination of on-site technologies and peak shaving strategies to minimise energy costs under time-of-use electricity tariffs, and the adaptation of a general methodology for a specific socio-technical context under seasonal loads. The “Fiera del Levante” exhibition centre in the city of Bari is selected due to the high seasonality of its electricity demand. The optimal solution uses a combined system with photovoltaics, diesel-fired and gas-fired combined-heat-and-power, including part-load operation and electric storage. The cost minimisation scenario reports up to 20% cost savings and 35% carbon emission savings with a 1MWp photovoltaic plant, compared to the baseline. This presents a five-year return on investment of 75%, and levelized cost of energy of €0.14 kWh−1. When coupled with a lithium-ion battery, solar energy brings up to 60% carbon emission savings through load shifting strategies, though this reduces the five-year return on investment by 9%. This hybrid setup is not financially competitive in the Italian retail market, but a hypothetical 25% rise of the grid import prices would make it economically viable. The proposed model is flexible and can be adapted to commercial end-users, providing decision-support in urban energy systems under local conditions.
Guo M, van Dam KH, Touhami NO, et al., 2020, Multi-level system modelling of the resource-food-bioenergy nexus in the global south, Energy, Vol: 197, Pages: 1-12, ISSN: 0360-5442
To meet the demands for resources, food and energy, especially in fast developing countries in the Global South, new infrastructure investments, technologies and supply chains are required. It is essential to manage a transition that minimises the impacts on global environmental degradation while benefits local socio-economic development. Food-bioenergy integration optimising natural capital resources and considering wider environmental and socio-economic sustainability offers a way forward. This study presents an integrative approach enabling whole systems modelling to address the interlinkage and interaction of resource-food-bioenergy systems and optimise supply chains considering poly-centric decision spaces. Life cycle sustainability assessment, optimisation, agent-based modelling and simulation were coupled to build an integrated systems modelling framework applicable to the resource-food-bioenergy nexus. The model building blocks are described before their applications in three case studies addressing agricultural residues and macro-fungi in the Philippines, sugar cane biorefineries in South Africa, and Nipa palm biofuel in Thailand. Our case studies revealed the great potential of untapped biomass including agricultural waste and non-food biomass grown on marginal lands. Two value chain integration case studies – i.e. straw-fungi-energy in Philippines and sugar-energy in Africa – have been suggested as sustainable solutions to recover waste as value-added products to meet food and energy security. Case studies highlight how an integrative modelling framework can be applied to address multi-level questions, taking into account decision-making at different levels, which contribute to an overall sustainability goal.
Zhang Z, Jing R, Lin J, et al., 2020, Combining agent-based residential demand modeling with design optimization for integrated energy systems planning and operation, APPLIED ENERGY, Vol: 263, ISSN: 0306-2619
Yang L, Zhang L, Stettler MEJ, et al., 2020, Supporting an integrated transportation infrastructure and public space design: A coupled simulation method for evaluating traffic pollution and microclimate, Sustainable Cities and Society, Vol: 52, ISSN: 2210-6707
Traditional urban and transport infrastructure planning that emphasized motorized transport has fractured public space systems and worsened environmental quality, leading to a decrease in active travel. A novel multiscale simulation method for supporting an integrated transportation infrastructure and public space design is presented in this paper. This method couples a mesoscale agent-based traffic prediction model, traffic-related emission calculation, microclimate simulations, and human thermal comfort assessment. In addition, the effects of five urban design strategies on traffic pollution and pedestrian level microclimate are evaluated (i.e., a “two-fold” evaluation). A case study in Beijing, China, is presented utilizing the proposed urban modeling-design framework to support the assessment of a series of transport infrastructure and public space scenarios, including the Baseline scenario, a System-Internal Integration scenario, and two External Integration scenarios. The results indicate that the most effective way of achieving an environmentally- and pedestrian- friendly urban design is to concentrate on both the integration within the transport infrastructure and public space system and the mitigation of the system externalities (e.g., air pollution and heat exhaustion). It also demonstrates that the integrated blue-green approach is a promising way of improving local air quality, micro-climatic conditions, and human comfort.
Yang L, van Dam KH, Majumdar A, et al., 2019, Integrated design of transport infrastructure and public spaces considering human behavior: A review of state-of-the-art methods and tools, FRONTIERS OF ARCHITECTURAL RESEARCH, Vol: 8, Pages: 429-453, ISSN: 2095-2635
Miu LM, Mazur CM, Van Dam KH, et al., 2019, Going smart, staying confused: perceptions and use of smart thermostats in British homes, Energy Research and Social Science, Vol: 57, ISSN: 2214-6296
Given the significant contribution of housing to energy consumption, research into how residents use energy-saving technologies has been gathering pace. In this study, we investigate the perception and use of domestic smart heating controls by a small group of residents in London, UK. These residents are supplied by a district heat network (DHN) through underfloor heating systems, and took part in a trial where their controls were upgraded from traditional thermostats to smart thermostats. Pre- and post-trial interviews were used to assess changes in how residents interacted with and perceived their controls and heating systems. After the upgrade, more residents were satisfied with the usability of their controls and programmed heating schedules which matched their actual occupancy patterns, but they also made ad-hoc temperature and schedule adjustments more frequently. These changes provide insight into how a unique sample of residents, “twice removed” from the most intuitive methods of heating control, adjusted their behaviour and perceptions following a technology upgrade. Although the small sample size and lack of long-term monitoring limits the generalizability of our results, the findings open avenues for further research into whether smart heating controls change user behaviour in a way that improves the predictability of heating demand, a crucial aspect of improving DHN operation and reducing related emissions.
Wang X, van Dam KH, Triantafyllidis C, et al., 2019, Energy-water nexus design and operation towards the sustainable development goals, COMPUTERS & CHEMICAL ENGINEERING, Vol: 124, Pages: 162-171, ISSN: 0098-1354
Mazur C, Hoegerle Y, Brucoli M, et al., 2019, A holistic resilience framework development for rural power systems in emerging economies, Applied Energy, Vol: 235, Pages: 219-232, ISSN: 0306-2619
Infrastructure and services within urban areas of developed countries have established reliable definitions of resilience and its dependence on various factors as an important pathway for achieving sustainability in these energy systems. However, the assessment, design, building and maintenance of power systems situated in rural areas in emerging economies present further difficulties because there is no a clear framework for such circumstances. Aiming to address this issue, this paper combines different visions of energy-related resilience both in general and under rural conditions in order to provide a robust practical framework for local and international stakeholders to derive the right actions in the rural context of emerging economies. An in-depth review is implemented to recompile information of resilience in general, in energy systems and in rural areas in particular, and a number of existing frameworks is also consulted. In order to acknowledge the particular circumstances and identify the important factors influencing the resilience of rural electrification in emerging economies, a holistic rural power system resilience framework is developed and presented. This consists of twenty-one indicators for technical resilience, eight indicators for social resilience, and thirteen indicators for economic resilience. This framework can be used by system owners and operators, policy makers, NGOs and communities to ensure the longevity of power systems. This work also paves the way for the creation of appropriate and effective resilience standards specifically targeted for application in these regions - aiming to achieve the delivery of global and local sustainability goals.
Wang X, Yang W, Noor S, et al., 2019, Blockchain-based smart contract for energy demand management, 10th International Conference on Applied Energy (ICAE), Publisher: ELSEVIER SCIENCE BV, Pages: 2719-2724, ISSN: 1876-6102
Blanchet CAC, Pantaleo AM, van Dam KH, 2019, A process systems engineering approach to designing a solar/biomass hybrid energy system for dairy farms in Argentina, 29th European Symposium on Computer-Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 1609-1614, ISSN: 1570-7946
van Dam KH, Feng B, Wang X, et al., 2019, Model-based decision-support for waste-to-energy pathways in New South Wales, Australia, Editors: Kiss, Zondervan, Lakerveld, Ozkan, Publisher: ELSEVIER SCIENCE BV, Pages: 1765-1770, ISBN: 978-0-12-819940-4
Noor S, Yang W, Guo M, et al., 2018, Energy Demand Side Management within micro-grid networks enhanced by blockchain, APPLIED ENERGY, Vol: 228, Pages: 1385-1398, ISSN: 0306-2619
Kis Z, Koppelaar RHEM, Sule MN, et al., 2018, Framework for WASH sector data improvements in data-poor environments, applied to Accra, Ghana, Water, Vol: 10, ISSN: 2073-4441
Improvements in water, sanitation and hygiene (WASH) service provision are hampered by limited open data availability. This paper presents a data integration framework, collects the data and develops a material flow model, which aids data-based policy and infrastructure development for the WASH sector. This model provides a robust quantitative mapping of the complete anthropogenic WASH flow-cycle: from raw water intake to water use, wastewater and excreta generation, discharge and treatment. This approach integrates various available sources using a process-chain bottom-up engineering approach to improve the quality of WASH planning. The data integration framework and the modelling methodology are applied to the Greater Accra Metropolitan Area (GAMA), Ghana. The highest level of understanding of the GAMA WASH sector is achieved, promoting scenario testing for future WASH developments. The results show 96% of the population had access to improved safe water in 2010 if sachet and bottled water was included, but only 67% if excluded. Additionally, 66% of 338,000 m3 per day of generated wastewater is unsafely disposed locally, with 23% entering open drains, and 11% sewage pipes, indicating poor sanitation coverage. Total treated wastewater is <0.5% in 2014, with only 18% of 43,000 m3 per day treatment capacity operational. The combined data sets are made available to support research and sustainable development activities.
Noor S, Guo M, van Dam KH, et al., 2018, Energy demand side management with supply constraints: Game theoretic approach, Applied Energy Symposium and Forum on Renewable Energy Integration with Mini/Microgrid Systems (REM), Publisher: Elsevier, Pages: 368-373, ISSN: 1876-6102
The management of energy supply and demand is becoming more challenging in regions where the demand continues to grow rapidly and more intermittent renewable supply sources are added to the energy infrastructure. In this context, Demand Side Management (DSM) can be employed to improve reliability of supply and stretch the capacity limits of the existing grid infrastructure. A game theoretic approach for DSM model incorporating storage components is suggested in this paper for environments with supply constraints. The proposed model is able to not only reduce the Peak-to-Average ratio to benefit the electric grid, but also smoothen the dips in load profile caused by supply constraints.
Liu M, van Dam KH, Pantaleo AM, et al., 2018, Optimisation of integrated bioenergy and concentrated solar power supply chains in South Africa, 28th European Symposium on Computer-Aided Process Engineering (ESCAPE), Publisher: Elsevier, Pages: 1463-1468, ISSN: 1570-7946
Climate change and energy security are complex challenges whose solutions depend on multi-faceted interactions between different actors and socio-economic contexts. Energy innovation through integration of renewable energies in existing systems offers a partial solution, with high potential identified for bioenergy and solar energy. In South Africa there is potential to further integrate renewable energies to meet local demands and conditions. Various concentrated solar power (CSP) projects are in place, but there is still land available to generate electricity from the sun. In combination with sustainable biomass resources these can offer synergetic benefits in improving the power generation’s flexibility. While thermodynamic and thermo-economic modelling for hybrid CSP-Biomass technology have been proposed, energy modelling in the realm of supply chains and demand/supply dynamics has not been studied sufficiently.We present a spatially and temporally Mixed Integer Linear Programming (MILP) model, to optimize the choice and location of technologies in terms of economic cost while being characterised by realistic supply/demand constraints as well as spatially-explicit environmental constraints. The model is driven by electricity demand, resource availability and technology costs as it aspires to emulate key energy and sustainability issues. A case study in the South African province of Gauteng was implemented over 2015-2050 to highlight the potential and challenges for hybrid CSP-Biomass and integrated systems assessment and the applicability of the modelling approach.From the range of hybrid CSP-Biomass technologies considered, based on detailed techno-economic characteristics from the literature, the Biomass only EFGT plant is identified as the cost optimal. When distributed generation (DG) technologies, small-scale Solar PV and Wind Turbines were introduced to the model as a competing alternative, they were demonstrated to be more economically optimal (&eur
Bieber N, Kee JH, Wang X, et al., 2018, Erratum to "Sustainable planning of the energy-water-food nexus using decision making tools" [Energy Policy 113, (2018) 584, 2018], Energy Policy, Vol: 116, Pages: 289-289, ISSN: 0301-4215
Wang X, Guo M, Koppelaar RHEM, et al., 2018, A nexus approach for sustainable urban energy-water-waste systems planning and operation, Environmental Science and Technology, Vol: 52, Pages: 3257-3266, ISSN: 0013-936X
Energy, water and waste systems analyzed at a nexus level is key to move towards more sustainable cities. In this paper, the “resilience.io” platform is developed and applied to emphasize on waste-to-energy pathways, along with the water and energy sectors, aiming to develop waste treatment capacity and energy recovery with the lowest economic and environmental cost. Three categories of waste including wastewater (WW), municipal solid waste (MSW) and agriculture waste are tested as the feedstock for thermochemical treatment via incineration, gasification or pyrolysis for combined heat and power generation, or biological treatment such as anaerobic digestion (AD) and aerobic treatment. A case study is presented for Ghana in Sub-Saharan Africa, considering a combination of waste treatment technologies and infrastructure, depending on local characteristics for supply and demand. The results indicate that the biogas generated from waste treatment turns out to be a promising renewable energy source in the analyzed region, while more distributed energy resources can be integrated. A series of scenarios including the business-as-usual, base case, natural constrained, policy interventions and environmental and climate change impacts demonstrate how simulation with optimization models can provide new insights in the design of sustainable value chains, with particular emphasis on whole-system analysis and integration.
Triantafyllidis CP, Koppelaar RHEM, Wang X, et al., 2018, An integrated optimisation platform for sustainable resource and infrastructure planning, Environmental Modelling and Software, Vol: 101, Pages: 146-168, ISSN: 1364-8152
It is crucial for sustainable planning to consider broad environmental and social dimensions and systemic implications of new infrastructure to build more resilient societies, reduce poverty, improve human well-being, mitigate climate change and address other global change processes. This article presents resilience.io, 2 a platform to evaluate new infrastructure projects by assessing their design and effectiveness in meeting growing resource demands, simulated using Agent-Based Modelling due to socio-economic population changes. We then use Mixed-Integer Linear Programming to optimise a multi-objective function to find cost-optimal solutions, inclusive of environmental metrics such as greenhouse gas emissions. The solutions in space and time provide planning guidance for conventional and novel technology selection, changes in network topology, system costs, and can incorporate any material, waste, energy, labour or emissions flow. As an application, a use case is provided for the Water, Sanitation and Hygiene (WASH) sector for a four million people city-region in Ghana.
Bieber N, Ker JH, Wang X, et al., 2017, Sustainable planning of the energy-water-food nexus using decision making tools, Energy Policy, Vol: 113, Pages: 584-607, ISSN: 0301-4215
Developing countries struggle to implement suitable electric power and water services, failing to match infrastructure with urban expansion. Integrated modelling of urban water and power systems would facilitate the investment and planning processes, but there is a crucial gap to be filled with regards to extending models to incorporate the food supply in developing contexts. In this paper, a holistic methodology and platform to support the resilient and sustainable planning at city region level for multiple sectors was developed for applications in urban energy systems (UES) and the energy-water-food nexus, combining agent-based modelling - to simulate and forecast resource demands on spatial and temporal scales - with resource network optimization, which incorporates capital expenditures, operational costs, environmental impacts and the opportunity cost of food production foregone (OPF). Via a scenario based approach, innovative water supply and energy deployment policies are presented, which address the provision of clean energy for every citizen and demonstrate the potential effects of climate change. The results highlighted the vulnerability of Ghanas power generation infrastructure and the need for diversification. Feed-in tariffs and investment into supporting infrastructure and agriculture intensification will effectively increase the share of renewable energy and reduce carbon emissions.
Gurguc Z, O'Connor J, Van Dam K, 2017, Delivering Urban Transformation through Collaborative Frameworks: Future Cities in the UK, Academy of Management
Crémel S, Guo M, Bustos-Turu G, et al., 2017, Optimal design of urban energy systems with demand side management and distributed generation, 27th European Symposium on Computer Aided Process Engineering, Publisher: Elsevier, Pages: 2371-2376, ISSN: 1570-7946
To tackle prominent societal challenges such as increasing energy demands and climate change due to greenhouse gas (GHGs) emissions demand side management (DSM) and distributed generation (DG) have been proposed as effective solutions particularly for urban areas with high energy densities and diverse types of energy demands. However, urban energy systems are complex, involving supply-demand interconnections, interaction of whole system level with various stakeholders (e.g. end-users, centralised suppliers) and regulation effects of policy instruments. The potential roles of integrated DSM and DG for the climate change mitigation under the urban energy system context haven been yet well understood. Our research aims to advance the understanding of such promising urban energy solutions and generate new insights via modelling framework development. In this study, an optimisation model is developed to simulate the combined effects of DSM and DG strategies in the optimal design of urban energy systems, and investigate the trade-offs between environmental and economic targets. The results of our case study on a hypothetical urban area suggest that the effects of just DSM on climate change mitigation are relatively low whereas urban system would benefit significantly from the introduction of more carbon efficient and economically competitive DG technologies. The set of Pareto optimal solutions derived from the model provide insights into the trade-offs between conflicting GHG and economic objectives: the environmentally optimal solutions with up to 39-43% of the GHG reduction are derived at the expenses of a cost increase by 73-87%; relatively cost efficient systems with marginal increase in economic profiles (4-5%) but significant GHG reductions (32-33%) are achievable. This study demonstrates the insights such model could provide for the decision-making and paradigm shifts towards sustainable urban energy systems and smart operational strategies.
Riveros M, Guo M, van dam, et al., 2017, Carbon Arbitrage with Stationary Batteries in the City of London, 27th European Symposium on Computer Aided Process Engineering, Publisher: Elsevier, Pages: 529-534, ISSN: 1570-7946
Stationary batteries could facilitate provision of carbon arbitrage services in cities. Such services offer a smart solution to integrate low-carbon energy technology into grid electricity supply and help tackle climate change. In this paper the environmental implications and overall profitability of this approach are assessed. A modelling framework has been developed to design an energy storage system with optimal capacity to maximise carbon savings. The City of London was used as a case study to demonstrate model applicability and analyse the potential effect of intermittent renewable energy sources in the supply system. The total savings obtained for the carbon arbitrage service were economically valorised using carbon market prices. In addition, a critical profitability thresholds for carbon trading prices are identified. Results show that this approach could bring environmental benefits depending on the carbon intensity of the grid, but that high carbon trading prices are required before it is economically feasible.
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