Installation
resilience.io Package Overview
Using the model –step by step
resilience.io Testing Capabilities (and Limitations)
resilience.io Use Examples
Q&A / Interactive Session
Dr Xiaonan Wang presents the How to build resilience.io for sustainable urban energy and water systems, Energy seminar for The Energy Futures Lab at Imperial College, London on 2nd December 2016
The team will cover the Current Status of the project (Rembrandt Koppelaar), Water Demands (Xiaonan Wang, Koen H. van Dam), Infrastructure construction (Rembrandt Koppelaar) and Toilet usage (Xiaonan Wang, Koen H. van Dam)
Setting the scene, including updates on our work around our global demonstrator regions, and then talk through WASH priorities and available data (based on a structure we will provide in advance), identifying gaps with you and how we might address them.
This study uses an ecologically-based hybrid life cycle assessment (Eco-LCA) model to evaluate the resource consumption and emissions of continuously reinforced concrete (CRCP) and hot-mix asphalt (HMA) pavements. The Eco-LCA model accounts for ecological goods and services used by considering mass, energy, industrial exergy, and ecological exergy. The results found that CRCP involves greater consumption of energy and industrial exergy than HMA, though HMA has slightly higher total mass and ecological exergy consumption. Material production was the most resource intensive life cycle phase for both pavements due to high energy and material demands of production. Transportation was also resource intensive for CRCP specifically.
This document discusses a study that conducted a hybrid life cycle sustainability assessment and multi-objective decision making analysis to evaluate four different passenger vehicle technologies (internal combustion vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, and battery electric vehicles) for Qatar. The analysis quantified 14 macro-level sustainability indicators using a global multi-regional input-output model. A compromise programming model was developed based on the sustainability assessment results to determine the optimal vehicle fleet distributions under different weighting scenarios of the sustainability indicators and analysis scopes. The optimal distributions showed that hybrid electric vehicles should comprise over 90% of the fleet when environmental indicators were prioritized. With a balanced weighting, the optimal fleet consisted of around 81% hybrid electric vehicles and 19% battery electric
This document presents a novel uncertainty-embedded dynamic life cycle sustainability assessment framework to evaluate alternative vehicle technologies from 2015 to 2050. The framework uses a system dynamics modeling approach to capture dynamic relationships and uncertainties among environmental, economic, and social parameters. Monte Carlo simulation is used to conduct multivariate uncertainty analysis for seven sustainability impact categories: carbon dioxide emissions, particulate matter formation, photochemical oxidant formation, vehicle ownership cost, contribution to GDP, employment generation, and human health impacts. The framework finds that while electric vehicles have the largest uncertainty, they are expected to best reduce human health impacts and air pollution over the long term compared to internal combustion, hybrid, and plug-in hybrid vehicles.
This study uses an input-output model based on the Eora database to assess the environmental, economic, and social impacts of automated diesel and electric heavy-duty trucks over their life cycles. The study finds that automated diesel trucks cause more fatalities and have higher global warming potential than automated electric trucks. Health impact costs are also twice as high for automated diesel trucks compared to electric trucks. While automation brings improvements across several sustainability indicators, the study finds trade-offs between environmental gains and losses of mineral and fossil resources that complicate decision making regarding truck automation technology.
An overview of potential future lifecycle impacts of low carbon vehicles. Shifting to hybrid and electric vehicles will mean that an increasing share of lifecycle GHG emissions come from the production of the vehicle and electricity. Presentation given at the annual LowCVP conference by Nik Hill, knowledge leader for transport technology at Ricardo-AEA
Dr Xiaonan Wang presents the How to build resilience.io for sustainable urban energy and water systems, Energy seminar for The Energy Futures Lab at Imperial College, London on 2nd December 2016
The team will cover the Current Status of the project (Rembrandt Koppelaar), Water Demands (Xiaonan Wang, Koen H. van Dam), Infrastructure construction (Rembrandt Koppelaar) and Toilet usage (Xiaonan Wang, Koen H. van Dam)
Setting the scene, including updates on our work around our global demonstrator regions, and then talk through WASH priorities and available data (based on a structure we will provide in advance), identifying gaps with you and how we might address them.
This study uses an ecologically-based hybrid life cycle assessment (Eco-LCA) model to evaluate the resource consumption and emissions of continuously reinforced concrete (CRCP) and hot-mix asphalt (HMA) pavements. The Eco-LCA model accounts for ecological goods and services used by considering mass, energy, industrial exergy, and ecological exergy. The results found that CRCP involves greater consumption of energy and industrial exergy than HMA, though HMA has slightly higher total mass and ecological exergy consumption. Material production was the most resource intensive life cycle phase for both pavements due to high energy and material demands of production. Transportation was also resource intensive for CRCP specifically.
This document discusses a study that conducted a hybrid life cycle sustainability assessment and multi-objective decision making analysis to evaluate four different passenger vehicle technologies (internal combustion vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, and battery electric vehicles) for Qatar. The analysis quantified 14 macro-level sustainability indicators using a global multi-regional input-output model. A compromise programming model was developed based on the sustainability assessment results to determine the optimal vehicle fleet distributions under different weighting scenarios of the sustainability indicators and analysis scopes. The optimal distributions showed that hybrid electric vehicles should comprise over 90% of the fleet when environmental indicators were prioritized. With a balanced weighting, the optimal fleet consisted of around 81% hybrid electric vehicles and 19% battery electric
This document presents a novel uncertainty-embedded dynamic life cycle sustainability assessment framework to evaluate alternative vehicle technologies from 2015 to 2050. The framework uses a system dynamics modeling approach to capture dynamic relationships and uncertainties among environmental, economic, and social parameters. Monte Carlo simulation is used to conduct multivariate uncertainty analysis for seven sustainability impact categories: carbon dioxide emissions, particulate matter formation, photochemical oxidant formation, vehicle ownership cost, contribution to GDP, employment generation, and human health impacts. The framework finds that while electric vehicles have the largest uncertainty, they are expected to best reduce human health impacts and air pollution over the long term compared to internal combustion, hybrid, and plug-in hybrid vehicles.
This study uses an input-output model based on the Eora database to assess the environmental, economic, and social impacts of automated diesel and electric heavy-duty trucks over their life cycles. The study finds that automated diesel trucks cause more fatalities and have higher global warming potential than automated electric trucks. Health impact costs are also twice as high for automated diesel trucks compared to electric trucks. While automation brings improvements across several sustainability indicators, the study finds trade-offs between environmental gains and losses of mineral and fossil resources that complicate decision making regarding truck automation technology.
An overview of potential future lifecycle impacts of low carbon vehicles. Shifting to hybrid and electric vehicles will mean that an increasing share of lifecycle GHG emissions come from the production of the vehicle and electricity. Presentation given at the annual LowCVP conference by Nik Hill, knowledge leader for transport technology at Ricardo-AEA
FCA resilience.io Platform:
Resource Economic Human Ecosystem
Modelling Platform Prototype
Foster Mensah
Centre for Remote Sensing and Geographic Information Services (CERSGIS)
University of Ghana
Rachael Kemp, Future Earth Ltd
Stephen Passmore, The Ecological Sequestration Trust
Koen H. van Dam and Harry Triantafyllidis
Department of Chemical Engineering
Imperial College London, UK
6 August 2015
This document presents a strategic design optimization model for microgrids with multiple energy storage technologies and demand response aggregation. The model (1) uses game theory to model the strategic behavior of utilities, aggregators, and consumers, (2) determines optimal tradeoffs between power imported from the grid and demand response resources, and (3) allocates various storage technologies cost-optimally. The model was tested on a 100% renewable energy microgrid in New Zealand, reducing lifetime costs by an estimated 21% compared to a business-as-usual approach without demand response.
Status ETSAP_TIAM Git project and starting up ETSAP-TIAM updateIEA-ETSAP
The document discusses two projects related to improving collaboration on and updating the ETSAP-TIAM energy systems model. The ETSAP_TIAM Git project aims to enhance collaboration through a version control system to track model changes. The 2-year ETSAP-TIAM Update Project aims to ensure the model remains relevant by updating technologies, data, and scenarios through workshops and collaborative development among members. It will deliver an updated model, documentation, and standard scenarios in a new VEDA-BE database. A reviewer group was also announced to review proposed model changes.
The document summarizes research applying genetic algorithms to optimize the design of large water distribution networks. It describes using a genetic algorithm to minimize the total cost of a real network in Suez City, Egypt with 341 nodes and 389 pipes. The genetic algorithm optimizes pipe diameters to meet hydraulic constraints like minimum pressure levels at nodes. It presents the formulation of the optimization problem and genetic algorithm approach. The case study applies the method to the Suez City network, demonstrating the approach's ability to solve large-scale, real-world optimization problems.
An Economic Analysis of Green and Grey Infrastructure - TRIECA Conference 2019Robert Muir
TRIECA Conference , 2019, An Economic Analysis of Green and Grey Infrastructure Benefits and Costs, Robert J. Muir, M.A.Sc., P.Eng., Manager, Stormwater, City of Markham, Fabian Papa, M.A.Sc., MBA, P.Eng., President, FP&P HydraTek
Presentation reviews regulations on policies on infrastructure cost, provides a history of cost benefit analysis, reviews Ontario green infrastructure policy and cost considerations, identifies research gaps in cost benefit analysis, evaluates the costs and benefits of grey, green and blended grey and green infrastructure strategies considering full lifecycle costs and system-wide implementation in the City of Markham. Analysis is based on this upcoming WEAO paper https://www.cityfloodmap.com/2019/03/an-economic-analysis-of-green-v-grey.html
Hydro-economic modelling approaches for agricultural water resources management AngelosAlamanos
Hydro-economic modelling approaches for agricultural water resources management in a Greek Watershed. In: 11th World Congress on Water Resources and Environment (EWRA 2019), Madrid, Spain. June 25-29, 2019
An Economic Analysis of Green v. Grey InfrastructureRobert Muir
Water Environment Association of Ontario 2019 Annual Conference, Toronto, Ontario, April 16, 2019
by Robert J. Muir, M.A.Sc., P.Eng., Fabian Papa, MBA, P.Eng.
Presentation reviews policies and regulations in Ontario promoting cost-effective infrastructure servicing. Summarizes the assessment of cost effectiveness of grey, green and blended green and grey flood damage reduction strategies on a system-wide basis. Identifies triple-bottom-line benefits of erosion mitigation reduction and water quality improvements due to green infrastructure implementation. Details of the analysis are presented in the proceedings paper also included here: https://www.cityfloodmap.com/2019/03/an-economic-analysis-of-green-v-grey.html
The analysis indicates benefit cost ratios for flood control and other benefits and assesses funding impacts on stormwater utility fees in a case study in the City of Markham. Markham's current Flood Control Program consisting largely of grey infrastructure is shown to be cost-effective with benefits exceeding costs by 2 to 1 based on insured loss deferral (and a higher ratio considering higher total losses). Green infrastructure is shown to be less cost-effective at delivering flood control and the cost for achieving water quality benefits exceeds the estimated willingness to pay 'value' of those benefits. The analysis suggests that a critical, strategic evaluation of green infrastructure implementation targets is required prior to system-wide implementation, given cost concerns.
The document summarizes research on integrated water management of the Red-Thai Binh river system in Vietnam under changing conditions. The researchers used optimization methods to design reservoir operating policies that balance multiple objectives like hydropower production, flood control, and water supply. Climate change assessments showed vulnerabilities are amplified by operations and depend on uncertain future scenarios. Further research will introduce socio-economic factors and robust optimization to support adaptation strategy design.
Emission impacts of marginal electricity demand in FranceIEA-ETSAP
This document summarizes research on estimating the carbon dioxide (CO2) emissions impacts of marginal electricity demand increases in France out to the year 2050. The research combined a bottom-up model of future electricity demand with a TIMES model of France's electricity supply system. Preliminary results for one scenario showed CO2 intensities of electricity could reach up to 300 gCO2/kWh by 2050, varying seasonally and hourly. Applying a carbon tax reduced CO2 intensities and even led to negative emissions some hours as biomass with carbon capture and storage displaced other generation. The analysis highlighted the need to better represent plant dynamics and interactions to accurately assess hourly CO2 impacts.
Putting hydropower and renewables in contextCPWF Mekong
This document summarizes a project assessing the potential role of renewables in power supply in the Mekong region. It finds that renewables have significant technical potential, including over 90 GW from solar, wind, geothermal, small hydro and biomass. However, renewables face barriers to wider deployment. Hydropower currently plays a major role in centralized grid systems, while renewables are smaller-scale and connected to distribution networks. High renewable penetration will require technologies like gas or hydropower that can respond quickly to output variations. While not direct substitutes, hydropower and renewables could complement each other, with hydropower helping to integrate variable renewables. Realizing their synergies would require changes to institutional
Evaluation of the role of energy storages in Europe with TIMES PanEUIEA-ETSAP
This document summarizes the results of scenario analyses conducted using the TIMES PanEU energy system model and ESTMAP storage database to evaluate the role of energy storage in Europe. The analyses found that increased electricity demand and electrification of the energy system are needed to meet EU GHG reduction targets. Additional electricity storage capacity investments from 2030 onward are also needed to integrate more variable renewable energy from wind and solar. First investments are in diabatic CAES and battery storage, shifting later to pump storage and adiabatic CAES as costs decrease. Energy storage, along with other flexibility options, helps reduce GHG emissions compared to scenarios relying more on natural gas storage.
Clean Air Partnership Green Infrastructure CAC Meeting - Don Mills Channel Fl...Robert Muir
Presentation on the application of Cost Benefit Analysis to water resources engineering projects, including for municipal flood control as part of Municipal Class Environmental Assessment infrastructure projects and city-wide programs. Evaluation of green infrastructure (Low Impact Development (LID)) capital costs and grey infrastructure costs.
1) The document presents a process model for material recovery facilities (MRFs) that can be used in life-cycle assessments of solid waste management systems.
2) The model includes four modules for different types of MRFs that process single-stream, dual-stream, pre-sorted, and mixed waste. It estimates costs, energy use, and product flows for each type based on equipment requirements and input waste composition.
3) Results from the model show total amortized costs ranging from $19.8 to $24.9 per metric ton of waste processed across MRF types. Electricity use ranges from 4.7 to 7.8 kilowatt-hours per metric ton. Glass separation
An integrated OPF dispatching model with wind power and demand response for d...IJECEIAES
In the day-ahead dispatching of network-constrained electricity markets, renewable energy and distributed resources are dispatched together with conventional generation. The uncertainty and volatility associated to renewable resources represents a new paradigm to be faced for power system operation. Moreover, in various electricity markets there are mechanisms to allow the demand participation through demand response (DR) strategies. Under operational and economic restrictions, the operator each day, or even in intra-day markets, dispatchs an optimal power flow to find a feasible state of operation. The operation decisions in power markets use an optimal power flow considering unit commitment to dispatch economically generation and DR resources under security restrictions. This paper constructs a model to include demand response in the optimal power flow under wind power uncertainty. The model is formulated as a mixed-integer linear quadratic problem and evaluated through Monte-Carlo simulations. A large number of scenarios around a trajectory bid captures the uncertainty in wind power forecasting. The proposed integrated OPF model is tested on the standard IEEE 39-bus system.
The document analyzes the current energy consumption patterns and forecasts the future energy demand of Jaya Container Terminal (JCT) in Sri Lanka by 2020. It models the current energy use using LEAP software and evaluates the per TEU energy consumption for different container types handled by JCT. It then forecasts JCT's energy demand by 2020 based on projections for container throughput. Finally, it analyzes potential demand side management options to reduce energy costs and consumption at JCT in the future.
This document outlines funding opportunities for energy research and innovation under the Horizon 2020 program. It discusses 14 specific calls related to competitive low-carbon energy, smart cities and communities, energy storage, sustainable biofuels, enabling decarbonization of fossil fuels, and modernizing the European electricity grid. Each call is described in 1-2 paragraphs covering its goals, challenges, funding amount, and technology readiness levels targeted.
This document summarizes a webinar on urban flood risk mapping presented by Robert Muir from the City of Markham. The webinar outlined a tiered vulnerability assessment approach for mapping riverine, wastewater, and storm drainage flood risks to guide best practices and projects. Simple, intermediate, and advanced risk mapping methods were described for each system. The risk maps can be used to identify policies, programs, and capital projects to reduce flood risk from flood plains to floor drains. Combining risk factors across systems was also discussed.
World Energy Resources Report 2016, E-storage: Shifting from cost to value 20...Private Consultants
The document summarizes a report by the World Energy Council on energy storage technologies. It finds that the costs of energy storage are forecasted to reduce by up to 70% by 2030. While levelized cost of energy is a useful metric, it has limitations and the true value of storage lies in improving power reliability and quality. Storage creates additional value by balancing loads, enabling deferred grid investments, and enabling price arbitrage. The report models costs of different storage technologies and finds lithium-ion batteries and pumped hydro make up most installed capacity currently. It recommends examining storage holistically in context and developing flexible markets to maximize value beyond cost alone.
Storm intensity not increasing - factual review of engineering data - Canada ...Robert Muir
Storm Intensity Not Increasing. Review of Weather Event Statement in Insurance Bureau of Canada’s “Telling the Weather Story” prepared by Institute for Catastrophic Loss Reduction. Environment Canada analysis and engineering dataset review for Canada and Ontario, July, 2015. "Old extremes are the new normal".
As illustrated through these slides, Telling the Weather Story makes a statement on the increased frequency of storms and weather events, indicating that in parts of Canada, events that occurred every 40 years are occurring every 6 years, due to climate change.
The statement on increased frequency is unfounded as (based on ICLR's IPCC source and material and IBC's presentation to the Empire Club of Canada) it is based on a theoretical shift in temperature frequency from a global climate change report, and is contrary to Environment Canada’s actual analysis and data on local rainfall intensity trends.
The Telling the Weather Story statement on increased storm intensity, based on temperature theory has been i) embraced as rainfall facts and research by many organizations, ii) embellished to apply to extreme rainfall, and iii) considered in policy and economic reports. Organizations promoting the misinformation in the statement include TD Economics, The Toronto Star / thestar.com, CBC News, Canadian Chamber of Commerce, Columbia Institute Centre for Civic Governance, Civic Action, CBC Doc Zone, The Calgary Sun, CanadianUnderwriter.ca, Aviva Canada, Insurance Bureau of Canada.
Due to the unfounded Telling the Weather Story Weather Story statement, policies and efforts toward mitigating increasing urban flood damages may be misdirected to climate change mitigation, as opposed to more effective risk identification/management efforts, urban planning / stormwater management policies and infrastructure remediation / capital investment efforts that address the root causes of increased damages, not related to theoretical storm frequency shifts.
It is an inconvenient truth that increases in temperature, and in theory water vapour, have not translated into increased rainfall intensities. Research at MIT and Columbia in fact states the contrary, that rainfall intensities can decrease at higher temperatures and that intensities are governed by CAPE and not temperature.
Environment Canada has been correcting false reporting by the insurance industry on this topic of increasing rainfall frequency, for example correcting CBC reporting:
http://www.cbc.ca/news/canada/windsor/more-than-half-of-homeowners-insurance-claims-stem-from-water-damage-broker-says-1.3291111
Or recent reporting in Canadian Underwriter, specifically on the Weather Story:
http://www.canadianunderwriter.ca/insurance/new-ibc-flood-model-shows-1-8-million-canadian-households-at-very-high-risk-1004006457/
CBC/Radio-Canada Ombudsman Guy Gendron's ruling highlights media issues with accurate extreme rain reporting here as well: https://bit.ly/2RPx7p9
During this meeting, the technical team from Imperial College London (ICL) and the Institute for Integrated Economics Research (IIER) showed the preliminary results from the resilience.io model prototype. They showed the water demand per district and how the technology infrastructure modelling can be used to meet water demands and sanitation treatment needs, as well as use case indicators and model functionality.
The Hillsborough County Wastewater BEST Group developed three models - BioWin, Ansys, and a Neural Network - to optimize the Valrico Advanced Wastewater Treatment Facility. BioWin accurately models the plant processes and kinetics using experimental influent data. Ansys models flow patterns in oxidation ditches. A Neural Network smooths noisy influent data and predicts future flows to help operators control the plant economically. Aerator energy consumption was correlated to the BioWin model to assess energy impacts. The models enable testing control strategies without risking plant performance. The goals of Hillsborough County Public Utilities Department have been met to continue optimizing Valrico's operation.
FCA resilience.io Platform:
Resource Economic Human Ecosystem
Modelling Platform Prototype
Foster Mensah
Centre for Remote Sensing and Geographic Information Services (CERSGIS)
University of Ghana
Rachael Kemp, Future Earth Ltd
Stephen Passmore, The Ecological Sequestration Trust
Koen H. van Dam and Harry Triantafyllidis
Department of Chemical Engineering
Imperial College London, UK
6 August 2015
This document presents a strategic design optimization model for microgrids with multiple energy storage technologies and demand response aggregation. The model (1) uses game theory to model the strategic behavior of utilities, aggregators, and consumers, (2) determines optimal tradeoffs between power imported from the grid and demand response resources, and (3) allocates various storage technologies cost-optimally. The model was tested on a 100% renewable energy microgrid in New Zealand, reducing lifetime costs by an estimated 21% compared to a business-as-usual approach without demand response.
Status ETSAP_TIAM Git project and starting up ETSAP-TIAM updateIEA-ETSAP
The document discusses two projects related to improving collaboration on and updating the ETSAP-TIAM energy systems model. The ETSAP_TIAM Git project aims to enhance collaboration through a version control system to track model changes. The 2-year ETSAP-TIAM Update Project aims to ensure the model remains relevant by updating technologies, data, and scenarios through workshops and collaborative development among members. It will deliver an updated model, documentation, and standard scenarios in a new VEDA-BE database. A reviewer group was also announced to review proposed model changes.
The document summarizes research applying genetic algorithms to optimize the design of large water distribution networks. It describes using a genetic algorithm to minimize the total cost of a real network in Suez City, Egypt with 341 nodes and 389 pipes. The genetic algorithm optimizes pipe diameters to meet hydraulic constraints like minimum pressure levels at nodes. It presents the formulation of the optimization problem and genetic algorithm approach. The case study applies the method to the Suez City network, demonstrating the approach's ability to solve large-scale, real-world optimization problems.
An Economic Analysis of Green and Grey Infrastructure - TRIECA Conference 2019Robert Muir
TRIECA Conference , 2019, An Economic Analysis of Green and Grey Infrastructure Benefits and Costs, Robert J. Muir, M.A.Sc., P.Eng., Manager, Stormwater, City of Markham, Fabian Papa, M.A.Sc., MBA, P.Eng., President, FP&P HydraTek
Presentation reviews regulations on policies on infrastructure cost, provides a history of cost benefit analysis, reviews Ontario green infrastructure policy and cost considerations, identifies research gaps in cost benefit analysis, evaluates the costs and benefits of grey, green and blended grey and green infrastructure strategies considering full lifecycle costs and system-wide implementation in the City of Markham. Analysis is based on this upcoming WEAO paper https://www.cityfloodmap.com/2019/03/an-economic-analysis-of-green-v-grey.html
Hydro-economic modelling approaches for agricultural water resources management AngelosAlamanos
Hydro-economic modelling approaches for agricultural water resources management in a Greek Watershed. In: 11th World Congress on Water Resources and Environment (EWRA 2019), Madrid, Spain. June 25-29, 2019
An Economic Analysis of Green v. Grey InfrastructureRobert Muir
Water Environment Association of Ontario 2019 Annual Conference, Toronto, Ontario, April 16, 2019
by Robert J. Muir, M.A.Sc., P.Eng., Fabian Papa, MBA, P.Eng.
Presentation reviews policies and regulations in Ontario promoting cost-effective infrastructure servicing. Summarizes the assessment of cost effectiveness of grey, green and blended green and grey flood damage reduction strategies on a system-wide basis. Identifies triple-bottom-line benefits of erosion mitigation reduction and water quality improvements due to green infrastructure implementation. Details of the analysis are presented in the proceedings paper also included here: https://www.cityfloodmap.com/2019/03/an-economic-analysis-of-green-v-grey.html
The analysis indicates benefit cost ratios for flood control and other benefits and assesses funding impacts on stormwater utility fees in a case study in the City of Markham. Markham's current Flood Control Program consisting largely of grey infrastructure is shown to be cost-effective with benefits exceeding costs by 2 to 1 based on insured loss deferral (and a higher ratio considering higher total losses). Green infrastructure is shown to be less cost-effective at delivering flood control and the cost for achieving water quality benefits exceeds the estimated willingness to pay 'value' of those benefits. The analysis suggests that a critical, strategic evaluation of green infrastructure implementation targets is required prior to system-wide implementation, given cost concerns.
The document summarizes research on integrated water management of the Red-Thai Binh river system in Vietnam under changing conditions. The researchers used optimization methods to design reservoir operating policies that balance multiple objectives like hydropower production, flood control, and water supply. Climate change assessments showed vulnerabilities are amplified by operations and depend on uncertain future scenarios. Further research will introduce socio-economic factors and robust optimization to support adaptation strategy design.
Emission impacts of marginal electricity demand in FranceIEA-ETSAP
This document summarizes research on estimating the carbon dioxide (CO2) emissions impacts of marginal electricity demand increases in France out to the year 2050. The research combined a bottom-up model of future electricity demand with a TIMES model of France's electricity supply system. Preliminary results for one scenario showed CO2 intensities of electricity could reach up to 300 gCO2/kWh by 2050, varying seasonally and hourly. Applying a carbon tax reduced CO2 intensities and even led to negative emissions some hours as biomass with carbon capture and storage displaced other generation. The analysis highlighted the need to better represent plant dynamics and interactions to accurately assess hourly CO2 impacts.
Putting hydropower and renewables in contextCPWF Mekong
This document summarizes a project assessing the potential role of renewables in power supply in the Mekong region. It finds that renewables have significant technical potential, including over 90 GW from solar, wind, geothermal, small hydro and biomass. However, renewables face barriers to wider deployment. Hydropower currently plays a major role in centralized grid systems, while renewables are smaller-scale and connected to distribution networks. High renewable penetration will require technologies like gas or hydropower that can respond quickly to output variations. While not direct substitutes, hydropower and renewables could complement each other, with hydropower helping to integrate variable renewables. Realizing their synergies would require changes to institutional
Evaluation of the role of energy storages in Europe with TIMES PanEUIEA-ETSAP
This document summarizes the results of scenario analyses conducted using the TIMES PanEU energy system model and ESTMAP storage database to evaluate the role of energy storage in Europe. The analyses found that increased electricity demand and electrification of the energy system are needed to meet EU GHG reduction targets. Additional electricity storage capacity investments from 2030 onward are also needed to integrate more variable renewable energy from wind and solar. First investments are in diabatic CAES and battery storage, shifting later to pump storage and adiabatic CAES as costs decrease. Energy storage, along with other flexibility options, helps reduce GHG emissions compared to scenarios relying more on natural gas storage.
Clean Air Partnership Green Infrastructure CAC Meeting - Don Mills Channel Fl...Robert Muir
Presentation on the application of Cost Benefit Analysis to water resources engineering projects, including for municipal flood control as part of Municipal Class Environmental Assessment infrastructure projects and city-wide programs. Evaluation of green infrastructure (Low Impact Development (LID)) capital costs and grey infrastructure costs.
1) The document presents a process model for material recovery facilities (MRFs) that can be used in life-cycle assessments of solid waste management systems.
2) The model includes four modules for different types of MRFs that process single-stream, dual-stream, pre-sorted, and mixed waste. It estimates costs, energy use, and product flows for each type based on equipment requirements and input waste composition.
3) Results from the model show total amortized costs ranging from $19.8 to $24.9 per metric ton of waste processed across MRF types. Electricity use ranges from 4.7 to 7.8 kilowatt-hours per metric ton. Glass separation
An integrated OPF dispatching model with wind power and demand response for d...IJECEIAES
In the day-ahead dispatching of network-constrained electricity markets, renewable energy and distributed resources are dispatched together with conventional generation. The uncertainty and volatility associated to renewable resources represents a new paradigm to be faced for power system operation. Moreover, in various electricity markets there are mechanisms to allow the demand participation through demand response (DR) strategies. Under operational and economic restrictions, the operator each day, or even in intra-day markets, dispatchs an optimal power flow to find a feasible state of operation. The operation decisions in power markets use an optimal power flow considering unit commitment to dispatch economically generation and DR resources under security restrictions. This paper constructs a model to include demand response in the optimal power flow under wind power uncertainty. The model is formulated as a mixed-integer linear quadratic problem and evaluated through Monte-Carlo simulations. A large number of scenarios around a trajectory bid captures the uncertainty in wind power forecasting. The proposed integrated OPF model is tested on the standard IEEE 39-bus system.
The document analyzes the current energy consumption patterns and forecasts the future energy demand of Jaya Container Terminal (JCT) in Sri Lanka by 2020. It models the current energy use using LEAP software and evaluates the per TEU energy consumption for different container types handled by JCT. It then forecasts JCT's energy demand by 2020 based on projections for container throughput. Finally, it analyzes potential demand side management options to reduce energy costs and consumption at JCT in the future.
This document outlines funding opportunities for energy research and innovation under the Horizon 2020 program. It discusses 14 specific calls related to competitive low-carbon energy, smart cities and communities, energy storage, sustainable biofuels, enabling decarbonization of fossil fuels, and modernizing the European electricity grid. Each call is described in 1-2 paragraphs covering its goals, challenges, funding amount, and technology readiness levels targeted.
This document summarizes a webinar on urban flood risk mapping presented by Robert Muir from the City of Markham. The webinar outlined a tiered vulnerability assessment approach for mapping riverine, wastewater, and storm drainage flood risks to guide best practices and projects. Simple, intermediate, and advanced risk mapping methods were described for each system. The risk maps can be used to identify policies, programs, and capital projects to reduce flood risk from flood plains to floor drains. Combining risk factors across systems was also discussed.
World Energy Resources Report 2016, E-storage: Shifting from cost to value 20...Private Consultants
The document summarizes a report by the World Energy Council on energy storage technologies. It finds that the costs of energy storage are forecasted to reduce by up to 70% by 2030. While levelized cost of energy is a useful metric, it has limitations and the true value of storage lies in improving power reliability and quality. Storage creates additional value by balancing loads, enabling deferred grid investments, and enabling price arbitrage. The report models costs of different storage technologies and finds lithium-ion batteries and pumped hydro make up most installed capacity currently. It recommends examining storage holistically in context and developing flexible markets to maximize value beyond cost alone.
Storm intensity not increasing - factual review of engineering data - Canada ...Robert Muir
Storm Intensity Not Increasing. Review of Weather Event Statement in Insurance Bureau of Canada’s “Telling the Weather Story” prepared by Institute for Catastrophic Loss Reduction. Environment Canada analysis and engineering dataset review for Canada and Ontario, July, 2015. "Old extremes are the new normal".
As illustrated through these slides, Telling the Weather Story makes a statement on the increased frequency of storms and weather events, indicating that in parts of Canada, events that occurred every 40 years are occurring every 6 years, due to climate change.
The statement on increased frequency is unfounded as (based on ICLR's IPCC source and material and IBC's presentation to the Empire Club of Canada) it is based on a theoretical shift in temperature frequency from a global climate change report, and is contrary to Environment Canada’s actual analysis and data on local rainfall intensity trends.
The Telling the Weather Story statement on increased storm intensity, based on temperature theory has been i) embraced as rainfall facts and research by many organizations, ii) embellished to apply to extreme rainfall, and iii) considered in policy and economic reports. Organizations promoting the misinformation in the statement include TD Economics, The Toronto Star / thestar.com, CBC News, Canadian Chamber of Commerce, Columbia Institute Centre for Civic Governance, Civic Action, CBC Doc Zone, The Calgary Sun, CanadianUnderwriter.ca, Aviva Canada, Insurance Bureau of Canada.
Due to the unfounded Telling the Weather Story Weather Story statement, policies and efforts toward mitigating increasing urban flood damages may be misdirected to climate change mitigation, as opposed to more effective risk identification/management efforts, urban planning / stormwater management policies and infrastructure remediation / capital investment efforts that address the root causes of increased damages, not related to theoretical storm frequency shifts.
It is an inconvenient truth that increases in temperature, and in theory water vapour, have not translated into increased rainfall intensities. Research at MIT and Columbia in fact states the contrary, that rainfall intensities can decrease at higher temperatures and that intensities are governed by CAPE and not temperature.
Environment Canada has been correcting false reporting by the insurance industry on this topic of increasing rainfall frequency, for example correcting CBC reporting:
http://www.cbc.ca/news/canada/windsor/more-than-half-of-homeowners-insurance-claims-stem-from-water-damage-broker-says-1.3291111
Or recent reporting in Canadian Underwriter, specifically on the Weather Story:
http://www.canadianunderwriter.ca/insurance/new-ibc-flood-model-shows-1-8-million-canadian-households-at-very-high-risk-1004006457/
CBC/Radio-Canada Ombudsman Guy Gendron's ruling highlights media issues with accurate extreme rain reporting here as well: https://bit.ly/2RPx7p9
During this meeting, the technical team from Imperial College London (ICL) and the Institute for Integrated Economics Research (IIER) showed the preliminary results from the resilience.io model prototype. They showed the water demand per district and how the technology infrastructure modelling can be used to meet water demands and sanitation treatment needs, as well as use case indicators and model functionality.
The Hillsborough County Wastewater BEST Group developed three models - BioWin, Ansys, and a Neural Network - to optimize the Valrico Advanced Wastewater Treatment Facility. BioWin accurately models the plant processes and kinetics using experimental influent data. Ansys models flow patterns in oxidation ditches. A Neural Network smooths noisy influent data and predicts future flows to help operators control the plant economically. Aerator energy consumption was correlated to the BioWin model to assess energy impacts. The models enable testing control strategies without risking plant performance. The goals of Hillsborough County Public Utilities Department have been met to continue optimizing Valrico's operation.
The document discusses using real-time and dynamic control technologies to improve management of rainwater harvesting and low impact development systems. It describes how programmable logic controllers, microcontrollers, and single board computers are enabling more advanced control approaches. Examples are given of using dynamic controls for hydrology matching, water quality optimizations, and predictive management of systems across entire watersheds. The potential for embedded modeling, distributed system designs, and internet-accessible data sources to enhance control capabilities is also explored.
SMART WATER THROUGH THE OPERATOR’S LENS: COLLECT, CONNECT, OPTIMIZE, AND ADVISEwle-ss
SUEZ is a global utility company that addresses water challenges through technology and expertise. Their SES approach involves a 4-step strategy of collecting data from sensors and logbooks, connecting disparate data systems, optimizing operations through analysis and plans, and providing real-time decision advisories. Case studies demonstrate how this approach helped utilities improve compliance, reduce costs and energy usage, and optimize infrastructure planning through integrated data systems and analytics. The discussion encourages utilities to build digital solutions step-by-step to maximize value, starting with strong data foundations.
This document presents a mathematical model for analyzing a generic single channel, multi-phase production line. The model aims to minimize system costs by reducing idle machine times and work-in-process inventory levels between machines. The model accounts for machine cycle times and calculates the times at which products enter and exit each machine in the production line. It assumes deterministic arrival rates and develops equations to determine the optimal level of service to minimize the total expected costs of providing service and of waiting for service.
This document provides instructions for using an energy balance assessment tool (EBAT) to estimate the energy usage and carbon emissions from urban water systems. It explains the tool's worksheets and input parameters for estimating supply, households, industry, treatment and equipment details. Key results are presented on energy consumption and carbon emissions for different stages of the water cycle. Background data and calculations are also included.
DC4Cities project has been presented by Jordi Guijarro, trials leader, at Datacenter Dynamics CONVERGED Madrid 2015, a congress where operators and managers of data center infrastructure and IT strategy meet to exchange specialized knowledge on data centers.
In particular, Jordi has presented the state and main goals of DC4Cities, as well as the extent to which the project aims at using data centers for energy optimization within and outside the smart city, reducing energy consumption and emissions.
The document discusses the DC4Cities project, which aims to make data centres more energy adaptive and environmentally sustainable. The goal is to find ways for data centres to adapt their energy consumption based on external constraints like renewable energy availability and smart city needs, in order to use minimal energy without impacting quality of service. It also aims to develop new energy metrics and standards. The project will test ways for data centres to adapt to renewable energy availability 80% of the time through controlling software, hardware, and power consumption.
This poster focuses on three single-use technologies suited for use in antibody drug conjugate production and shows examples of performance data for the following:
• Mixers
• Chromatography
• Tangential Flow Filtration
To learn more about this topic or collaborate with our technical experts, schedule an in-person or remote visit at our M Lab™ Collaboration Centers: www.emdmillipore.com/mlab
Three Steps for Reducing Total Cost of Ownership in Pumping SystemsSchneider Electric
Electricity usage costs have become an increasing fraction of the total cost of ownership (TCO) for industrial pumping systems. In fact, energy cost represents 40% of the TCO of a typical pump. It is possible to reduce the electrical consumption by at least 30% through appropriate energy management practices while reducing the maintenance cost. This paper explains how to reduce TCO with a limited investment.
The document describes a Resilience.IO simulation model to evaluate water, sanitation, and hygiene (WASH) scenarios in the Greater Accra Metropolitan Area (GAMA) of Ghana. It includes a synthetic population model to simulate water and sanitation demands. Technology datasets are used to model infrastructure options. Three use cases are presented: assessing ongoing projects, increasing water access, and analyzing toilet availability. Baseline results show ongoing projects will not meet 2025 goals, while city-wide systems achieving 100% access and treatment would require over $2 billion of investment from 2015-2025.
This document provides an overview of non-conventional energy sources and renewable energy development in India. It discusses how renewable energy sources like solar, wind and biomass can help meet growing energy demands in a sustainable way. It outlines India's efforts to promote renewable energy through programs and policies that encourage grid-connected power generation from sources like solar, wind and small hydropower. The document emphasizes the need to commercialize renewable technologies and develop entrepreneurship in the renewable energy sector to fully utilize India's renewable energy potential.
Top 10 Products That Save Money - David McDougall, EnerNOCMassRecycle
Presentation delivered at MassRecycle's 4th Annual Green Office / Green Facility Conference, Bentley University, June 15, 2010. Get invited to next year’s conference by signing up to MassRecycle’s free email newsletter at www.massrecycle.org.
POWER PLANT ECONOMICS AND ENVIRONMENTAL CONSIDERATIONS - SNISTS.Vijaya Bhaskar
This document discusses various topics related to power plant economics and environmental considerations. It covers cost analysis including fixed costs like land, equipment, interest, depreciation, and operational costs like fuel, labor, maintenance. It also discusses factors affecting power plant design, load curves, and terms used in the power industry. Finally, it covers major pollutants from fossil fuel and nuclear power plants and methods to control emissions.
The document discusses Merck's Mobius single-use product line for bioprocessing applications. It summarizes the performance of their single-use mixers, chromatography systems, and tangential flow filtration systems. The mixers provide customizable bags and vessels for gentle or high-performance mixing. The chromatography and TFF systems use pre-designed assemblies to simplify implementation and feature low minimum working volumes and high recovery yields. Common elements like recipe templates and sensor designs are used to enhance modularity.
This document discusses the need for green data centers and provides strategies for making data centers more energy efficient. It notes that while many organizations say they are green, few have specific targets or programs to reduce their carbon footprint. As data center electricity consumption and costs rise, running out of power capacity, cooling capacity, and physical space are major concerns. The document then provides questions to assess a data center's energy efficiency in terms of facilities, IT equipment, and utilization rates. It recommends strategies like optimizing infrastructure utilization and choosing more efficient hardware and cooling options. The goal is to improve the data center infrastructure efficiency metric and lower costs by reducing redundant, underutilized resources.
FluidFlow is a modular piping system modeling software that allows users to model liquid, gas, two-phase, and slurry systems. It uses established models and correlations to solve complex piping networks. The software includes components, fluids, pumps, and heat transfer functionality in its database. It can size pipes and equipment, model transient behavior, and optimize system performance through its scripting module. Engineers use FluidFlow to accelerate design of systems like LNG plants, gas networks, and mining operations.
Similar to resilience.io WASH sector prototype debut training workshop (20)
We invite investment, in 3 categories, into a new Resilience Brokerage Fund RESBR to be used to complete development and deployment of a unique prototyped Resilience Brokerage software Platform resilience.io into most countries of the world by 2023. Resilience.io supports planning and investment in resilient city development, and has embedded Apps for the best clean technologies to be included in project pipelines.
We invite a minimum of 4 “Core Platform Builders” to invest $5m each for a 6 year term to receive annual interest and dividends.
We invite clean technology investors to invest $2m each for a 6 year term, to receive annual interest and use of the resilience.io platform with 4 Apps for their technologies added.
We invite Geographic investors to make a minimum grant investment of $500,000 for exclusive use of resilience.io in their region/country for integrated land use planning and investment.
Stephen Passmore and Peter Head of The Ecological Sequestration Trust are joined by Bob Bishop of the International Centre for Earth Simulation to discuss there pioneering project creating Global to Local Scale, Human, Economic, Ecological, Systems Models
Stephen Passmore, Head of Platform Delivery, The Ecological Sequestration Trust presents the work on resilience.io in GAMA, Accra, Ghana over the previous 18 months to a World Cafe session at the Cities Alliance, Africa Strategy Workshop, Sept 2016
In June 2016, with the culmination of 18 months work by the the team from IIER, Imperial College, Future Earth Ltd and the Trust, we visited Accra to debut the WASH sector prototype of our modelling app at the Accra International Conference Centre, 22nd June 2016.
resilience.io is an open-source, collaborative
human, ecological, economic, resource systems, modelling platform to enable “public good”
we also showed this video https://www.youtube.com/watch?v=EGyCyxyatAQ
The Trust
The future of the collaboratory
Discuss planning of June debut workshops and activities - identify expert users, identify needs and wishes for the interactive workshop sessions, identify particular WASH policy challenges that the Use Cases and prototype can help to inform
Update on FCA, Ghana, Cities Alliance partnership
Update on global activities
ICL IIER Team
Brief outline of early use case findings
Update on visualisations as part of the demonstration of the resilience.io prototype
Lightning Talk by Peter Head CBE FREng FRSA at the RSA Scaling for impact event 1 February 2016.
https://www.thersa.org/events/fellowship-events/2016/2/rsa-engage-scaling-for-impact----1-feb/
My journey to provide and scale support to city regions to meet Global Goals by 2030
In 2008 I was working in Arup, heading up their global planning business with a world class team of transport, environmental, urban and policy and economics experts. Before that I had worked in infrastructure design and delivery, particularly Public Private Partnerships, around the World and I was also an adviser to the Mayor of London Ken Livingstone on his Sustainable Development Commission and so I was very aware of the challenges of achieving improved city resilience.
My team at Arup was working at the cutting edge of low carbon sustainable city planning worldwide, particularly in China. It was there I got very inspired by their vision of an ecological civilisation, living in harmony with nature, as the next phase of development after the industrial model. However getting the plans built everywhere we worked was very difficult because success still revolved around GDP growth and that was the metric decision making. We knew that this was damaging the health of land and ocean ecology, and human well-being was not necessarily improving as a result, but everyone thought that this was the “price of progress”. Development was becoming less inclusive in many more developed countries as well.
I was given the opportunity to develop and articulate a roadmap towards a more resilient Ecological Age in the 2008-9 Brunel Lecture sponsored by Institution of Civil Engineers in London.
I gave this presentation all over the world in 45 cities in 2008-9, and the feedback was very positive, but many were skeptical that a more resilient Ecological Age could be delivered. The financial crash did not help the mood. It was very clear that the disconnect between investment decision making and the community social/ecological system impact at global and local scales was a huge problem. We did not have the tools and understanding of how human and ecology systems and resource flows interact and how this affects investment and health-productivity risks. It was clear to most people that city regions would be critical in determining a successful outcome for humanity by 2050, because of the projected urbanisation and the resulting investment drawn into those locations. The analysis showed that we had to embrace a factor 4 reduction in pollution and resource consumption, including greenhouse gas emissions, by 2050 both in retrofitting existing city regions and in the model for new urbanisation, if a successful outcome was to be achieved...
http://resilience.io/about/rsa-scaling-for-impact/
November 17th 2015, 11:00 – 12:30 – An outline summary of potential use cases to demonstrate the functionality of the prototype of resilience.io. The cases outlined at this meeting are based on inputs given by the GTG at the September meeting. Use-case development will be collaborative with the GTG and the final selection of use cases will take place in January 2016.
September 10th 2015, 10:00 – 11:30 – The development of WASH use case studies to simulate in the model – GTG Webinar. We will also discuss sets of technology and policy options that are to be investigated as well as anticipated population and economic development scenarios and their impacts on the WASH sector. The initial use cases will be presented by Rembrandt Koppelaar with interactive input and discussion by GTG members. Thereafter GTG will be asked to provide own use cases.
The document provides an overview of the Resilience.io modeling platform and its components for simulating an integrated urban system. It describes:
1) The agent-based and optimization modeling approaches used to simulate activities, resource flows, infrastructure networks and markets.
2) How the model represents population demographics, resource processes, infrastructure and service consumption.
3) The process of building a model of Ulaanbaatar, Mongolia, including developing an integrated data map and adjusting model rulesets to the local context.
This presentation by The Ecological Sequestration Trust and partners Institute for Integrated Economics Research (IIER), Geodan and the International Centre for Earth Simulation (ICES), will show how the integrated systems platform resilience.io can help UB City achieve its goals; how it can help assess new infrastructure project risk and return and identify policies and projects offering the greatest long-term ecological-social-economic benefits for UB citizens.
It will outline how the platform can be used to provide a clear economic case for investment in low carbon sustainable projects and enable global and regional investment to be mobilised to help deliver the UB City Economic Development Strategy.
Transition from agricultural to ecological age
Газар тариалангаас экологийн зуунд шилжих
A new paradigm of urban and rural development with integrated urban and rural resource flows
Хот, хөдөөний нөөцийн нэгдсэн урсгал бүхий хот, хөдөөг хөгжүүлэх шинэ парадигм
Tools for measuring and implementing a “scientific approach to development” and measuring “ecological progress”
“Хөгжилд шинжлэх ухааны үүднээс хандах” явдлыг хэмжих ба хэрэгжүүлэх хэрэгслүүд, “экологийн дэвшлийг” хэмжих
Future Cities Africa
resilience.io prototype development in GAMA
Supporting inclusive, resilient low carbon development
Stephen Passmore
24th March 2015
Future Cities Africa
Future proofing to climate, environment and natural resource challenges
Supporting inclusive, resilient low carbon development
Peter Head CBE FREng FRSA
March 24th 2015
The document discusses the EPA's systems approach called Triple Value (3V) which provides an integrative framework for systems thinking. The 3V approach addresses sustainability and resilience issues in communities by understanding the interactions between economic, social, and environmental systems. EPA has applied the 3V approach successfully to pilot projects in different regions to identify unintended consequences of decisions and achieve sustainable solutions. The document provides an overview of the 3V framework and examples of its application to issues like nutrient pollution management.
This document discusses insurance and risk management for catastrophic events. It provides links to organizations that focus on regional resilience, catastrophe risk modeling, and using insurance to address global risks. The links are for foundations and initiatives that use simulation and modeling to help manage risks from extreme events and build more resilient communities and regions.
Connecting global & regional finance to projects - Finance for #SDGs High Level Meeting – #financeforSDGs – Christoph Waldersee – Bellagio – 25-27 February 2015
This document provides an introduction and objectives for a meeting on mobilizing finance for resilience. The objectives are to learn from each other, create new knowledge on scaling development efforts toward the UN Sustainable Development Goals, create a report to share this knowledge, learn collaborative tools, and help case study regions advance quickly. Introductory remarks discuss investing in resilience and climate risks, a more stable finance system investing in the real economy, and the role of data and systems modeling in facilitating incremental to transformational change, from siloed to collaborative work, and from lowest cost to performance-based approaches.
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
karnataka housing board schemes . all schemesnarinav14
The Karnataka government, along with the central government’s Pradhan Mantri Awas Yojana (PMAY), offers various housing schemes to cater to the diverse needs of citizens across the state. This article provides a comprehensive overview of the major housing schemes available in the Karnataka housing board for both urban and rural areas in 2024.
Bharat Mata - History of Indian culture.pdfBharat Mata
Bharat Mata Channel is an initiative towards keeping the culture of this country alive. Our effort is to spread the knowledge of Indian history, culture, religion and Vedas to the masses.
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
UN WOD 2024 will take us on a journey of discovery through the ocean's vastness, tapping into the wisdom and expertise of global policy-makers, scientists, managers, thought leaders, and artists to awaken new depths of understanding, compassion, collaboration and commitment for the ocean and all it sustains. The program will expand our perspectives and appreciation for our blue planet, build new foundations for our relationship to the ocean, and ignite a wave of action toward necessary change.
United Nations World Oceans Day 2024; June 8th " Awaken new dephts".Christina Parmionova
The program will expand our perspectives and appreciation for our blue planet, build new foundations for our relationship to the ocean, and ignite a wave of action toward necessary change.
This report explores the significance of border towns and spaces for strengthening responses to young people on the move. In particular it explores the linkages of young people to local service centres with the aim of further developing service, protection, and support strategies for migrant children in border areas across the region. The report is based on a small-scale fieldwork study in the border towns of Chipata and Katete in Zambia conducted in July 2023. Border towns and spaces provide a rich source of information about issues related to the informal or irregular movement of young people across borders, including smuggling and trafficking. They can help build a picture of the nature and scope of the type of movement young migrants undertake and also the forms of protection available to them. Border towns and spaces also provide a lens through which we can better understand the vulnerabilities of young people on the move and, critically, the strategies they use to navigate challenges and access support.
The findings in this report highlight some of the key factors shaping the experiences and vulnerabilities of young people on the move – particularly their proximity to border spaces and how this affects the risks that they face. The report describes strategies that young people on the move employ to remain below the radar of visibility to state and non-state actors due to fear of arrest, detention, and deportation while also trying to keep themselves safe and access support in border towns. These strategies of (in)visibility provide a way to protect themselves yet at the same time also heighten some of the risks young people face as their vulnerabilities are not always recognised by those who could offer support.
In this report we show that the realities and challenges of life and migration in this region and in Zambia need to be better understood for support to be strengthened and tuned to meet the specific needs of young people on the move. This includes understanding the role of state and non-state stakeholders, the impact of laws and policies and, critically, the experiences of the young people themselves. We provide recommendations for immediate action, recommendations for programming to support young people on the move in the two towns that would reduce risk for young people in this area, and recommendations for longer term policy advocacy.
Indira awas yojana housing scheme renamed as PMAYnarinav14
Indira Awas Yojana (IAY) played a significant role in addressing rural housing needs in India. It emerged as a comprehensive program for affordable housing solutions in rural areas, predating the government’s broader focus on mass housing initiatives.
A Guide to AI for Smarter Nonprofits - Dr. Cori Faklaris, UNC CharlotteCori Faklaris
Working with data is a challenge for many organizations. Nonprofits in particular may need to collect and analyze sensitive, incomplete, and/or biased historical data about people. In this talk, Dr. Cori Faklaris of UNC Charlotte provides an overview of current AI capabilities and weaknesses to consider when integrating current AI technologies into the data workflow. The talk is organized around three takeaways: (1) For better or sometimes worse, AI provides you with “infinite interns.” (2) Give people permission & guardrails to learn what works with these “interns” and what doesn’t. (3) Create a roadmap for adding in more AI to assist nonprofit work, along with strategies for bias mitigation.
Combined Illegal, Unregulated and Unreported (IUU) Vessel List.Christina Parmionova
The best available, up-to-date information on all fishing and related vessels that appear on the illegal, unregulated, and unreported (IUU) fishing vessel lists published by Regional Fisheries Management Organisations (RFMOs) and related organisations. The aim of the site is to improve the effectiveness of the original IUU lists as a tool for a wide variety of stakeholders to better understand and combat illegal fishing and broader fisheries crime.
To date, the following regional organisations maintain or share lists of vessels that have been found to carry out or support IUU fishing within their own or adjacent convention areas and/or species of competence:
Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR)
Commission for the Conservation of Southern Bluefin Tuna (CCSBT)
General Fisheries Commission for the Mediterranean (GFCM)
Inter-American Tropical Tuna Commission (IATTC)
International Commission for the Conservation of Atlantic Tunas (ICCAT)
Indian Ocean Tuna Commission (IOTC)
Northwest Atlantic Fisheries Organisation (NAFO)
North East Atlantic Fisheries Commission (NEAFC)
North Pacific Fisheries Commission (NPFC)
South East Atlantic Fisheries Organisation (SEAFO)
South Pacific Regional Fisheries Management Organisation (SPRFMO)
Southern Indian Ocean Fisheries Agreement (SIOFA)
Western and Central Pacific Fisheries Commission (WCPFC)
The Combined IUU Fishing Vessel List merges all these sources into one list that provides a single reference point to identify whether a vessel is currently IUU listed. Vessels that have been IUU listed in the past and subsequently delisted (for example because of a change in ownership, or because the vessel is no longer in service) are also retained on the site, so that the site contains a full historic record of IUU listed fishing vessels.
Unlike the IUU lists published on individual RFMO websites, which may update vessel details infrequently or not at all, the Combined IUU Fishing Vessel List is kept up to date with the best available information regarding changes to vessel identity, flag state, ownership, location, and operations.
resilience.io WASH sector prototype debut training workshop
1. Resilience.IO WASH
Training Workshop
Rembrandt Koppelaar, Xiaonan Wang,
Department of Chemical Engineering, Imperial College London, UK
IIER – Institute for Integrated Economic Research
Accra - June 2016
Resilience.IO platform
2. Outline
Installation
resilience.io Package Overview
Using the model – step by step
resilience.io Testing Capabilities (and Limitations)
resilience.io Use Examples
Q&A / Interactive Session
2
6. A data-driven simulation model of a synthetic
population
To experiment with different scenarios by generating
demand profiles
And to find supply from a description of technologies
and networks using optimisation with key
performance metrics
The approach: Resilience.IO Model
6
7. Everything in one folder
7
1. Creation of Synthetic
Population Change
2. Simulate demands
3. Examine what
infrastructure can best
supply demands
Double-click to run:
start_resilience.io_socio_de
mographics_calculation
start_resilience.io_demand_c
alculation
start_resilience.io_supply_cal
culation
In Main folder c:/resilienceIO_final
8. In Sub-folders storage of data-files
8
File storage of Synthetic Population Change:
C:resilienceIO_finalresilience.io.abmdataagent_data
File storage of simulated demands:
C:resilienceIO_finalresilience.io.abmfileoutput
File storage of infrastructure supply simulation
C:resilienceIO_finalresilience.io.rtnvisual_outputs
C:resilienceIO_finalresilience.io.rtntext_outputs
10. How to use the model: step-by-step
10
main folder: start_resilience.io_socio_dem_model
Step 1: Double clicks the
resilience.io_socio_dem_mod
el file
Step 2: User can inputs the
years to be simulated after
the instruction line (the
starting base year is 2010
with existing complete
information) and press Enter
key.
Step 3: The generated data is
stored into two categories of
spreadsheets to record the
population and business
sectors information
respectively.
11. How to use the model: step-by-step
11
results folder: population and companies master tables
ResilienceIO/ resilience.io.abm / data agent_data
By changing the
selected year's file
name to
“GAMA_Agent_ma
stertable” and
“GAMA_Company
_mastertable”,
users can plan the
supply matching
with any year’s
data.
12. How to use the model: step-by-step
12
main folder: start_resilience.io_demand_model
Step 1: Double clicks the
resilience.io_demand_model file
Step 2: Check the parameters to the left if
you want to change any settings, otherwise
the default parameters are used.
Step 3: Click on Initialize model to load the
map and agents, and click Run to start
simulation.
Initialize model / Run
13. How to use the model: step-by-step
13
Running: calculations are going on
Stopped: results are ready now
Agents/people are starting their daily activities:
pink- female
blue- male
14. How to use the model: step-by-step
14
results folder: demand and costs
All results are stored
in the folder
ResilienceIO/resilienc
e.io.abm/FileOutput
with a comprehensive
list of the WASH
sector key
characteristics,
especially the water
demand file and waste
to be treated
15. How to use the model: step-by-step
15
main folder: double click resilience.io_supply_model
Equivalently, you can click on resilience.io_supply_textoutputs to store
results in spreadsheets/ text format
17. Demographics module
17
Loads Population and Company Master Table
C:resilienceIO_finalresilience.io.abmdataagent_dataGAMA_Agent_
Mastertable.csv
C:resilienceIO_finalresilience.io.abmdataagent_dataGAMA_Compa
ny_Mastertable.csv
18. Demographics module
18
Calculates changes in population for each
population type per year for X number of years (e.g.
female, unemployed, access to drinking water)
Adds births (specify no births per 1000 people)
Subtracts deaths (specify no deaths per 1000 people)
Adds immigration (specify no immigrants per 1000 people
Adds emigration (specify no emigrants per 1000 people
19. Demographics module – how to change?
19
Open YAML file with text editor (notepad)
C:resilienceIO_finalresilience.io.abmdatasocio_economic_data_input.yml
20. Demographics module – how to change?
20
Change file in text editor (notepad)
Example larger immigration rate
Order of MMDA values for all district specific data
Change value in immigration rate row for Accra (second value)
Save file
Now the module can be operated with new settings!
21. Demographics module – Additional Settings
21
Changes from low income to medium income population
(value for lowtomediumstart, 0.003 0.3% per year)
Changes from medium to high income population (value
for mediumtohighstart, 0.003 0.3% per year)
Maximum employment of 15+ year population (Value for
maximumEmployment15plus, 0.80 80%)
Ageing of population from 0-14 to 15+ (Value for
ageintRate14to15, 0.06 6% per year )
22. Demand Systems module – what can be changed?
22
Setting water demands in litres / day / person
Currently: Medium-income 1 * 70 to 90 litres 70-90
Low-income 0.73 * 70 to 90 51 to 66 litres
High-income 1.56 * 70 to 90 109 to 140 litres
Setting toilet use, faeces and urine per toilet use
23. Demand Systems module – what can be changed?
23
Costs for water and toilets for calculation assuming
100% demands at end point would be met (no non-
revenue, ideal situation)
Tariffs as set by PURC
Estimated market
values calculated
from GHS to USD
24. Supply infrastructure module – what can be changed?
24
Load the desired starting scenario file by copying
from folder:
C:resilienceIO_finalresilience.io.rtnoutputyaml_input_filesuse
_case_x_yaml_files
And pasting to folder:
C:resilienceIO_finalresilience.io.rtnoutputyaml_input_files
Store any other existing files in another folder (or
delete them if not useful)
Open Scenario YML file to change settings
25. Supply infrastructure module – what can be changed?
25
Number and name of districts and coordinates
Coordinates of “cells” (MMDAs) based on real
coordinate systems,
in the order of “names_of_cells”
Values entered twice, once for calculation and
once for visualisation
MMDAs, the order is important for further data input!
26. Technology data
Supply infrastructure module – what can be changed?
26
Capacity of technologies per half year (182.5
days)
Names of technologies, the order is important for
further data input!
Load factor of technologies (75% - 85%)
Boreholes 15,000 m3 per year capacity * 75% load
11,250 m3 per year operation
27. Technology-Resource data
Supply infrastructure module – what can be changed?
27
Which resources are available in the
model (again the order is important for
further settings!). Also which resources can
flow (usually both are set to the same)
Input and output of resources for
technologies. Every row is a
technology and every column a
resource
Negative value is input, and positive
value is output
Input of raw_source_water
28. Technology-Cost data
Supply infrastructure module – what can be changed?
28
Investment cost per technology in order
Source water treatment plant 45,197,947 USD
Borehole source water system 3,325,541 USD
(boreholes + local town water system)
Protected well or protected spring 50,000 USD
29. Technology-Cost data
Supply infrastructure module – what can be changed?
29
Operational cost for technology
Source water treatment plant 0.23 USD per m3
Borehole source water system 0.237 USD per m3
Protected well or protected spring 1 USD per m3
And greenhouse gas emissions for technology use
Source water treatment plant 0.017 kg per m3
Borehole source water system 0.0065 USD per m3
Protected well or protected spring 0 USD per m3
30. Settings for what to optimise (find lowest cost)
Supply infrastructure module – what can be changed?
30
Set objectives to minimize capital & operational
expenditure & CO2 emissions (do not change!)
Set importance in minimization for objectives.
Values are multipliers. Currently:
CAPEX [1] so as to represent total capital cost
OPEX [15] so as to represent 15 years of OPEX
CO2 [0.5] arbitrarily chosen
Set which resource demands to meet, values
correspond to order in resource column, additional
demands can be added!
Set % of demands to meet [1,1] 100%, 100%
31. Supply infrastructure module – what can be changed?
31
Settings for resource to meet demands
If true reads simulated demands from file, if
false reads demands from ODS
demands for set resources per year, only
used if read_ABM is set false,
Every row is demand for an MMDA in order of
names of cells as set earlier:
[ Adenta 3010999, 2408799]
[ Accra_Metropolitan 175684715, 6054772]
Numbers represent resources for which
demands are set in file (in this case water and
influent waste-water), additional demand values
can be added here!
32. Settings for pipes and flows
Supply infrastructure module – what can be changed?
32
Pipe type names (potable water and waste-
water). Order is important!
Resources which flow through pipes
pw_pipe potable_water
ww_pipe influent_wastewater
Leakage % in pipes (currently
27%)
Capacity per pipe per year for resource
[4,7]
33. Settings for meeting resource import needs (e.g. outside
GAMA or outside WASH sector).
Supply infrastructure module – what can be changed?
33
MMDAs which can
import resources
Import maximum (50,000,000) per MMDA The resources which can be
imported
raw_source_water from waterbodies
Electricity from electricity sector
Labour_hours from population
Liquid_effluent special settings to
make waste-water calculation work
Cost of imports
Electricity 0.02 USD per MJ
Labour-hours 2.4 USD per hour
34. Initial infrastructure already in place
Supply infrastructure module – what can be changed?
34
Every row is an MMDA, and every column is number of technologies
Boreholes in AMA 329 * 15,000 m3 per year capacity
is equal to 5 million m3 per year, or 13,500 m3 per day
35. Initial pipe infrastructure already in place from/to
Supply infrastructure module – what can be changed?
35
AM potable water pipes
AM1 waste-water pipes
If all values are 0, then no pipes are in existence prior to
model run, such as for waste-water pipes
Pipe exists from/to
From Accra Metropolitan
To La-Dade Kotopon
36. Pipe connections which are allowed to be built by model
Supply infrastructure module – what can be changed?
36
AM2 potable water pipes
AM3 waste-water pipes
If all values are 0, then no pipes can be built, if all values
are 1 then all connections can be built
Pipe allowed from/to
From Ga-South
To Ga-West
37. Cost of building trunk pipes and operating them
Supply infrastructure module – what can be changed?
37
Capital cost of pipe per km
Potable water pipe 2,350,000 USD
Waste-water pipe 235,000 USD
Operational cost of pipe per m3
per flowable resource value for
potable water set to 0.001
USD per m3
38. Additional settings for resource to meet demands
Supply infrastructure module – what can be changed?
38
Number of major periods (years) and minor
periods in a year (two) don’t change setting
Year which is printed in the output results
(doesn’t influence model)
Split for minor periods in year (8760 hours per year),
in this case 1756 hours and 7008 hours
These settings are for the model to calculate sub-periods
within a year when useful
39. Additional Settings
Supply infrastructure module – what can be changed?
39
Amount of potable water turned into waste-water
Available budget for investment + operation per
year
Set all facilities forced to full operation (100%)
No investments are allowed (can lead to not being
able to meet demands no solution)
The number of solutions tried out (Lower is better,
higher is faster), 0.01 is highest value allowed
41. Already prepared Use cases and Scenarios
41
Use Case 3
Toilets & Waste-water
Use Case 1:
Water & Waste-water
Baseline
Use Case 2
Water supply
Baseline
City-Wide
Decentralised districts
Low pipe leakage variants
Local Pipe Source
Central Pipe
Source
High immigration
variants
Baseline
Public toilet and local
district treatment
Sustainable Development
Goal targets
Private toilets and
central GAMA treatment
Various Input files in folder:
C:resilienceIO_finalresilience.io.rtnYAML_INPUT_FILES
43. Example, change the costs of a technology
43
We have new/improved data for the costs of a
technology such as conventional water treatment
First step Edit the YAML file(s) that you want to run
the model with:
Open:
C:ResilienceIO_Finalresilience.io.rtnoutputYAML_INPUT_FILESuse_ca
se_2_yaml_filesCentral_pipe_4_2025.yml
44. Go to the investment cost table VIJA
Look up which row is the source water treatment plant
Adjust the value and save the file
Example, change the costs of a technology
44
45. Example, change the costs of a technology
45
We have new/improved data for the costs of a
technology such as conventional water treatment
Second step Copy the YAML file to the base folder
that you want to run with
From:
C:ResilienceIO_Finalresilience.io.rtnoutputYAML_INPUT_FILESuse_ca
se_2_yaml_filesCentral_pipe_4_2015.yml
To:
C:ResilienceIO_Finalresilience.io.rtnoutputYAML_INPUT_FILESCentral
_pipe_4_2015.yml
47. Example, effect change in pipe leakage
47
We want to run for 2025 the impacts of a 10% pipe
leakage reduction for improved potable water.
Use case 2 scenario files are for potable water only
Decide what to compare?
Situation / year 2015 2025
Scenario A
Baseline 27%
Continuation
27% leakage
Scenario B Reduction to
17% leakage
48. Example, effect change in pipe leakage
48
We want to run for 2025 the impacts of a 10% pipe
leakage reduction for improved potable water.
Use case 2 scenario files are for potable water only
Decide what to compare?
Situation / year 2015 2025
Scenario A
Baseline 27%
Continuation
27% leakage
Scenario B Reduction to
17% leakage
49. Example, effect change in pipe leakage
49
First step Run Demographics module for 15 years
(from 2010 to 2025) with input settings.
Second step Rename the earlier generated
population data for 2025 in the folder before demands
calculation
Take file
C:ResilienceIO_FinalResilienceIO_Finalresilience.io.abmdata
agent_dataagentMasterTable-2015
Rename into
C:ResilienceIO_FinalResilienceIO_Finalresilience.io.abmdata
agent_dataGAMA_Agent_mastertable
And do the same for companyMasterTable-2015 and rename
into GAMA_Company_mastertable
50. Example, effect change in pipe leakage
50
Third step Run baseline demand situation for 2015
demographics with input settings.
Fourth step Run Supply to meet generated demands
for baseline using baseline scenario file use Case 2
C:ResilienceIO_Finalresilience.io.rtnoutputYAML_INPUT_FIL
ESuse_case_2_yaml_filesBaseline_1_2015.yml
The baseline scenario files contain a “dummy” technology
called “unimproved_w_inv” and “unimproved_ww_inv” for adding
unimproved sources “to meet demands” without investment
(no cost)
51. Example, effect change in pipe leakage
51
Fifth step Save all generated results for
demographics, demands, and supply in a new folder (for
example c:ResilienceIO_FinalScenario_Results20_June_leakage)
Files can be found in the following folders:
C:resilienceIO_finalresilience.io.abmdataagent_data
C:resilienceIO_finalresilience.io.abmfileoutput
C:resilienceIO_finalresilience.io.rtnvisual_outputs
C:resilienceIO_finalresilience.io.rtntext_outputs
52. Example, effect change in pipe leakage
52
We now have the results for baseline_scenario for the
year 2015 with 27% pipe leakage!
Situation / year 2015 2025
Scenario A
Baseline 27%
Continuation
27% leakage
Scenario B Reduction to
17% leakage
53. Example, effect change in pipe leakage
53
Sixth step Rename the earlier generated population
data for 2025 in the agent_data folder to run demands
Take file
C:ResilienceIO_FinalResilienceIO_Finalresilience.io.abmdata
agent_dataagentMasterTable-2025
Rename into
C:ResilienceIO_FinalResilienceIO_Finalresilience.io.abmdata
agent_dataGAMA_Agent_mastertable
And do the same for companyMasterTable-2025 and rename
into GAMA_Company_mastertable
Seventh step Run demand simulation based on 2025
demographics with input settings.
54. Example, effect change in pipe leakage
54
Eight step Run Supply to meet generated demands
for 2025 by using scenario file:
C:ResilienceIO_Finalresilience.io.rtnoutputYAML_INPUT
_FILESuse_case_2_yaml_filesCentral_pipe_4_2025.yml
Ninth step Save all generated results for
demographics, demands, and supply in the new folder
Situation / year 2015 2025
Scenario A
Baseline 27%
Continuation
27% leakage
Scenario B Reduction to 17%
leakage
55. Example, effect change in pipe leakage
55
Tenth step Adjust YAML file Central_pipe_4_2025.yml
Change leakage rate:
Eleventh step Run Supply to meet generated demands
for 2025 by using adjusted YAML scenario file.
Last step Save all generated results for demographics,
demands, and supply in the new folder for 17% leakage
rate.
Situation / year 2015 2025
Scenario A
Baseline 27%
Continuation
27% leakage
Scenario B Reduction to
17% leakage
56. Example, effect change in pipe leakage
56
Now we should have in folder
c:ResilienceIO_FinalScenario_Results20_June_leakage
- Results for baseline 27% run for 2015
- Results for 2025 100% improved water 27% leakage
- Results for 2025 100% improved water 17% leakage
We can now compare results for changes in population,
changes in demands (2015-2025), difference in costs
between 27% and 17% leakage, etc. using the csv files,
text output file for supply, and generated graphs
57. A Sample of Results
57
Population in 2025 near 7 million
Water Demand in 2025 close to 636,000 m3/day (will
differ somewhat for each model run and number of agents)
C:ResilienceIO_Finalresilience.io.abmFileOutputday-0-
waterDemandTotal
58. A Sample of Results – 2025 w 27% leakage
58
Investment cost 2015-2025 3.26 billion USD
Operational cost in 2025 105 million USD
59. Interpreting Results
59
The supply side outcomes are influenced by the
constraints and limitations
For example: It invests in conventional water treatment at
Lake Weija mainly because
There are no limits to expansion at Lake Weija
Building treatment plants are similar in cost at Lake Weija are at
Volta River / Kpone
Only the distance for pipe connections are taken into account
(greater distance to Volta River versus Lake Weija)
Elevation and difference in source water intake are not taken into
account
60. Example 3 – Adding
entirely new technologies
(and demands)
60
62. Start with the desired YAML file
62
Take and copy to the input folder:
C:resilienceIO_finalresilience.io.rtnoutputyaml_input_files
use_case_1_yaml_filesSustainable_Development_Goals_4
_2030.yml
Since we are running additional demands (for biogas) -
which are not generated by the demand module - we want
to open the YAML file and flag read_abm: false
Now we can make further adjustments!
63. Example: Adding Biogas into model
63
read_ABM : false
ODS:
- [4632193 , 3705754, 200]
- [89126797 , 71301437, 200]
- [11961616 , 9569293, 0]
- [7504044 , 6003235, 0]
- [8506051 , 6804841, 0]
- [28814317 , 23051454, 0]
- [12085454 , 9668363, 0]
- [6670931 , 5336745, 0]
- [8770558 , 7016447, 0]
- [6908802 , 5527041, 0]
- [9799336 , 7839469, 0]
- [12679806 , 10143845, 200]
- [3126596 , 2501277, 0]
- [5024429 , 4019543, 0]
- [1550251 , 1240201, 0]
- [1,1,1]
Pilot:
Which districts
would like to use
bio-gas?
[ADMA, AMA, ASHMA, GCMA, GSMA,
GWMA,GEMA, KKMA, LADMA,
LANKMA, LEKMA, TEMA, ASMA,
ASEMA, NAMA, VOLTA]
Demand of biogas: 2000 m3 per year for
the selected district each
67. VIJA: capital expenditure, operational cost, environmental cost
- [45197947,0,0]
- [3325541,0,0]
- [50000,0,0]
- [43065,0,0]
- [2478334,0,0]
- [150,0,0]
- [100,0,0]
- [53398778,0,0]
- [14145810,0,0]
- [768544,0,0]
- [1516850,0,0]
- [4816845,0,0]
- [3092,0,0]
- [244500,0,0]
- [130000000,0,0]
- [7200,0,0]
Example: Adding Biogas into model
67
What else do you
need to change?
-
-
-
68. VIJA: capital expenditure, operational cost, environmental cost
- [45197947,0,0]
- [3325541,0,0]
- [50000,0,0]
- [43065,0,0]
- [2478334,0,0]
- [150,0,0]
- [100,0,0]
- [53398778,0,0]
- [14145810,0,0]
- [768544,0,0]
- [1516850,0,0]
- [4816845,0,0]
- [3092,0,0]
- [244500,0,0]
- [130000000,0,0]
- [7200,0,0]
Example: Adding Biogas into model
68
What else do you need to
change?
- VPJ - [0,0.08,0]
- N_alloc_matrix:
no existing plants, all 0
- dp: 1 Qmax: 10000
69. 69
Results: new investment on infrastructure
Investments('decentralised_anaerobic_biogas_treatment_plant'.AMA.2030) =4
Investments('decentralised_anaerobic_biogas_treatment_plant'.LEKMA.2030) = 3020
Investments('decentralised_anaerobic_biogas_treatment_plant'.TEMA.2030) = 2
Investments('decentralised_anaerobic_biogas_treatment_plant'.ASMA.2030) = 1
70. 70
Results: new investment on infrastructure
Investments('biogas_plant'.AMA.2030) = 1
What happened if costs reduced for affordable large-scale biogas technology?
71. 71
Results: new investment on infrastructure
Investments('biogas_plant'.AMA.2030) = 2
24000 m3 capacity per year each plant
72. 72
Results: new investment on infrastructure
ProductionRate('biogas_plant'.ADMA.1.2030) = 930
ProductionRate('biogas_plant'.ADMA.2.2030) = 3699
ProductionRate('biogas_plant'.TEMA.1.2030) = 393
ProductionRate('biogas_plant'.TEMA.2.2030) = 1570
73. Supply module Sometimes the connection to the
visualisation software does not work, and you get an
error in the code, or graphs don’t appear:
Click Ctrl-Alt-Delete go to task manager click on
process called Rserve.exe and end task
Now rerun the model
Troubleshooting
73
74. Troubleshooting
74
Demand module restarting the interface instead of
running the model a few times
You can always email:
Xiaonan.wang@imperial.ac.uk
Koppelaar@iier.ch