The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Julien J Harou - One of the best experts on this subject based on the ideXlab platform.
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least economic cost regional water supply planning optimising infrastructure investments and Demand Management for south east england s 17 6 million people
Water Resources Management, 2013Co-Authors: Silvia Padula, Julien J Harou, Lazaros G Papageorgiou, Mohammad Ahmad, Nigel HepworthAbstract:This paper presents a deterministic capacity expansion optimisation model designed for large regional or national water supply systems. The annual model selects, sizes and schedules new options to meet predicted Demands at minimum cost over a multi-year time horizon. Options include: supply-side schemes, Demand Management (water conservation) measures and bulk transfers. The problem is formulated as a mixed integer linear programming (MILP) optimisation model. Capital, operating, carbon, social and environmental costs of proposed discrete schemes are considered. User-defined annual water saving profiles for Demand Management schemes are allowed. Multiple water Demand scenarios are considered simultaneously to ensure the supply–Demand balance is preserved across high Demand conditions and that variable costs are accurately assessed. A wide range of supplementary constraints are formulated to consider the interdependencies between schemes (pre-requisite, mutual exclusivity, etc.). A two-step optimisation scheme is introduced to prevent the infeasibilities that inevitably appear in real applications. The model was developed for and used by the ‘Water Resources in the South East’ stakeholder group to select which of the 316 available supply schemes (including imports) and 511 Demand Management options (considering 272 interdependencies) are to be activated to serve the inhabitants of South East of England. Selected schemes are scheduled and sized over a 25 year planning horizon. The model shows Demand Management options can play a significant role in the region’s water supply and should be considered alongside new supplies and regional transfers. Considering Demand Management schemes reduced overall total discounted economic costs by 10 % and removed two large reservoirs from the least-cost plan. This case-study optimisation model was built using a generalised data Management software platform and solved using a mixed integer linear programme.
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selecting portfolios of water supply and Demand Management strategies under uncertainty contrasting economic optimisation and robust decision making approaches
Water Resources Management, 2013Co-Authors: Evgenii S Matrosov, Silvia Padula, Julien J HarouAbstract:Planning appropriate portfolios of new water supplies and Demand Management measures requires considering a wide array of options and their interactions over a largely unknown future. Various modelling-assisted approaches are available to help this planning process. This paper applies two such frameworks to the UK’s Thames water resource system and compares their methods and outputs: how they consider uncertainty, how they represent supply and Demand Management options, and what plans each recommends. The first method is the current England and Wales industry standard: annual least-cost capacity expansion optimisation over a 25 to 30 year time horizon considering capital, operating (fixed and variable), social and environmental costs. The second approach uses stochastic simulation and regret analysis to select a preferred alternative, then statistical cluster analysis to identify causes of system failure enabling further plan improvement. When applied iteratively with system planners this second approach is referred to as Robust Decision Making (RDM). The economic optimisation approach considers all plausible combinations of supply and conservation schemes and recommends the least-cost schedule of their implementation. Our RDM application considers a smaller number of options but makes a more detailed assessment of the effect of uncertainty (supply, Demand and energy price uncertainty were considered) on multiple criteria of system performance. The simulation-based approach also enables more realistic interaction amongst supply and Demand Management schemes. Both approaches recommended different plans which we explain by discussing the benefits and limitations of each. Joint application is recommended to produce least-cost plans that are robust considering multiple criteria of performance across a wide range of futures.
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selecting portfolios of water supply and Demand Management strategies under uncertainty contrasting economic optimisation and robust decision making approaches
Water Resources Management, 2013Co-Authors: Evgenii S Matrosov, Silvia Padula, Julien J HarouAbstract:Planning appropriate portfolios of new water supplies and Demand Management measures requires considering a wide array of options and their interactions over a largely unknown future. Various modelling-assisted approaches are available to help this planning process. This paper applies two such frameworks to the UK’s Thames water resource system and compares their methods and outputs: how they consider uncertainty, how they represent supply and Demand Management options, and what plans each recommends. The first method is the current England and Wales industry standard: annual least-cost capacity expansion optimisation over a 25 to 30 year time horizon considering capital, operating (fixed and variable), social and environmental costs. The second approach uses stochastic simulation and regret analysis to select a preferred alternative, then statistical cluster analysis to identify causes of system failure enabling further plan improvement. When applied iteratively with system planners this second approach is referred to as Robust Decision Making (RDM). The economic optimisation approach considers all plausible combinations of supply and conservation schemes and recommends the least-cost schedule of their implementation. Our RDM application considers a smaller number of options but makes a more detailed assessment of the effect of uncertainty (supply, Demand and energy price uncertainty were considered) on multiple criteria of system performance. The simulation-based approach also enables more realistic interaction amongst supply and Demand Management schemes. Both approaches recommended different plans which we explain by discussing the benefits and limitations of each. Joint application is recommended to produce least-cost plans that are robust considering multiple criteria of performance across a wide range of futures. Copyright Springer Science+Business Media B.V. 2013
Silvia Padula - One of the best experts on this subject based on the ideXlab platform.
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least economic cost regional water supply planning optimising infrastructure investments and Demand Management for south east england s 17 6 million people
Water Resources Management, 2013Co-Authors: Silvia Padula, Julien J Harou, Lazaros G Papageorgiou, Mohammad Ahmad, Nigel HepworthAbstract:This paper presents a deterministic capacity expansion optimisation model designed for large regional or national water supply systems. The annual model selects, sizes and schedules new options to meet predicted Demands at minimum cost over a multi-year time horizon. Options include: supply-side schemes, Demand Management (water conservation) measures and bulk transfers. The problem is formulated as a mixed integer linear programming (MILP) optimisation model. Capital, operating, carbon, social and environmental costs of proposed discrete schemes are considered. User-defined annual water saving profiles for Demand Management schemes are allowed. Multiple water Demand scenarios are considered simultaneously to ensure the supply–Demand balance is preserved across high Demand conditions and that variable costs are accurately assessed. A wide range of supplementary constraints are formulated to consider the interdependencies between schemes (pre-requisite, mutual exclusivity, etc.). A two-step optimisation scheme is introduced to prevent the infeasibilities that inevitably appear in real applications. The model was developed for and used by the ‘Water Resources in the South East’ stakeholder group to select which of the 316 available supply schemes (including imports) and 511 Demand Management options (considering 272 interdependencies) are to be activated to serve the inhabitants of South East of England. Selected schemes are scheduled and sized over a 25 year planning horizon. The model shows Demand Management options can play a significant role in the region’s water supply and should be considered alongside new supplies and regional transfers. Considering Demand Management schemes reduced overall total discounted economic costs by 10 % and removed two large reservoirs from the least-cost plan. This case-study optimisation model was built using a generalised data Management software platform and solved using a mixed integer linear programme.
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selecting portfolios of water supply and Demand Management strategies under uncertainty contrasting economic optimisation and robust decision making approaches
Water Resources Management, 2013Co-Authors: Evgenii S Matrosov, Silvia Padula, Julien J HarouAbstract:Planning appropriate portfolios of new water supplies and Demand Management measures requires considering a wide array of options and their interactions over a largely unknown future. Various modelling-assisted approaches are available to help this planning process. This paper applies two such frameworks to the UK’s Thames water resource system and compares their methods and outputs: how they consider uncertainty, how they represent supply and Demand Management options, and what plans each recommends. The first method is the current England and Wales industry standard: annual least-cost capacity expansion optimisation over a 25 to 30 year time horizon considering capital, operating (fixed and variable), social and environmental costs. The second approach uses stochastic simulation and regret analysis to select a preferred alternative, then statistical cluster analysis to identify causes of system failure enabling further plan improvement. When applied iteratively with system planners this second approach is referred to as Robust Decision Making (RDM). The economic optimisation approach considers all plausible combinations of supply and conservation schemes and recommends the least-cost schedule of their implementation. Our RDM application considers a smaller number of options but makes a more detailed assessment of the effect of uncertainty (supply, Demand and energy price uncertainty were considered) on multiple criteria of system performance. The simulation-based approach also enables more realistic interaction amongst supply and Demand Management schemes. Both approaches recommended different plans which we explain by discussing the benefits and limitations of each. Joint application is recommended to produce least-cost plans that are robust considering multiple criteria of performance across a wide range of futures.
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selecting portfolios of water supply and Demand Management strategies under uncertainty contrasting economic optimisation and robust decision making approaches
Water Resources Management, 2013Co-Authors: Evgenii S Matrosov, Silvia Padula, Julien J HarouAbstract:Planning appropriate portfolios of new water supplies and Demand Management measures requires considering a wide array of options and their interactions over a largely unknown future. Various modelling-assisted approaches are available to help this planning process. This paper applies two such frameworks to the UK’s Thames water resource system and compares their methods and outputs: how they consider uncertainty, how they represent supply and Demand Management options, and what plans each recommends. The first method is the current England and Wales industry standard: annual least-cost capacity expansion optimisation over a 25 to 30 year time horizon considering capital, operating (fixed and variable), social and environmental costs. The second approach uses stochastic simulation and regret analysis to select a preferred alternative, then statistical cluster analysis to identify causes of system failure enabling further plan improvement. When applied iteratively with system planners this second approach is referred to as Robust Decision Making (RDM). The economic optimisation approach considers all plausible combinations of supply and conservation schemes and recommends the least-cost schedule of their implementation. Our RDM application considers a smaller number of options but makes a more detailed assessment of the effect of uncertainty (supply, Demand and energy price uncertainty were considered) on multiple criteria of system performance. The simulation-based approach also enables more realistic interaction amongst supply and Demand Management schemes. Both approaches recommended different plans which we explain by discussing the benefits and limitations of each. Joint application is recommended to produce least-cost plans that are robust considering multiple criteria of performance across a wide range of futures. Copyright Springer Science+Business Media B.V. 2013
Evgenii S Matrosov - One of the best experts on this subject based on the ideXlab platform.
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selecting portfolios of water supply and Demand Management strategies under uncertainty contrasting economic optimisation and robust decision making approaches
Water Resources Management, 2013Co-Authors: Evgenii S Matrosov, Silvia Padula, Julien J HarouAbstract:Planning appropriate portfolios of new water supplies and Demand Management measures requires considering a wide array of options and their interactions over a largely unknown future. Various modelling-assisted approaches are available to help this planning process. This paper applies two such frameworks to the UK’s Thames water resource system and compares their methods and outputs: how they consider uncertainty, how they represent supply and Demand Management options, and what plans each recommends. The first method is the current England and Wales industry standard: annual least-cost capacity expansion optimisation over a 25 to 30 year time horizon considering capital, operating (fixed and variable), social and environmental costs. The second approach uses stochastic simulation and regret analysis to select a preferred alternative, then statistical cluster analysis to identify causes of system failure enabling further plan improvement. When applied iteratively with system planners this second approach is referred to as Robust Decision Making (RDM). The economic optimisation approach considers all plausible combinations of supply and conservation schemes and recommends the least-cost schedule of their implementation. Our RDM application considers a smaller number of options but makes a more detailed assessment of the effect of uncertainty (supply, Demand and energy price uncertainty were considered) on multiple criteria of system performance. The simulation-based approach also enables more realistic interaction amongst supply and Demand Management schemes. Both approaches recommended different plans which we explain by discussing the benefits and limitations of each. Joint application is recommended to produce least-cost plans that are robust considering multiple criteria of performance across a wide range of futures.
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selecting portfolios of water supply and Demand Management strategies under uncertainty contrasting economic optimisation and robust decision making approaches
Water Resources Management, 2013Co-Authors: Evgenii S Matrosov, Silvia Padula, Julien J HarouAbstract:Planning appropriate portfolios of new water supplies and Demand Management measures requires considering a wide array of options and their interactions over a largely unknown future. Various modelling-assisted approaches are available to help this planning process. This paper applies two such frameworks to the UK’s Thames water resource system and compares their methods and outputs: how they consider uncertainty, how they represent supply and Demand Management options, and what plans each recommends. The first method is the current England and Wales industry standard: annual least-cost capacity expansion optimisation over a 25 to 30 year time horizon considering capital, operating (fixed and variable), social and environmental costs. The second approach uses stochastic simulation and regret analysis to select a preferred alternative, then statistical cluster analysis to identify causes of system failure enabling further plan improvement. When applied iteratively with system planners this second approach is referred to as Robust Decision Making (RDM). The economic optimisation approach considers all plausible combinations of supply and conservation schemes and recommends the least-cost schedule of their implementation. Our RDM application considers a smaller number of options but makes a more detailed assessment of the effect of uncertainty (supply, Demand and energy price uncertainty were considered) on multiple criteria of system performance. The simulation-based approach also enables more realistic interaction amongst supply and Demand Management schemes. Both approaches recommended different plans which we explain by discussing the benefits and limitations of each. Joint application is recommended to produce least-cost plans that are robust considering multiple criteria of performance across a wide range of futures. Copyright Springer Science+Business Media B.V. 2013
Shengwei Wang - One of the best experts on this subject based on the ideXlab platform.
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a game theory based decentralized control strategy for power Demand Management of building cluster using thermal mass and energy storage
Applied Energy, 2019Co-Authors: Rui Tang, Hangxin Li, Shengwei WangAbstract:The development of smart grids requires more active and effective participation of buildings in power balance. However, most of building Demand Management and Demand response control strategies focus on single buildings only. For a group of buildings at cluster-level, which are often involved in an electricity charge account, such control strategies will not be effective. A game theory-based decentralized control strategy is therefore developed to address the Demand Management of cluster-level buildings. The indoor temperature set-point and the charging/discharging process of active cold storages in central air-conditioning systems are optimized simultaneously. Rather than optimizing the power Demand of all buildings on a central optimization system, the proposed strategy optimizes the power Demand of all buildings collectively in a decentralized manner. Using this strategy, buildings manage their own power Demands locally only using the aggregated power Demand of building cluster as the common reference for their Demand controls. This distributed computing allows the optimization of large systems or complex optimization problems to be divided into a few simple optimization tasks, providing enhanced applicability and robustness in practical applications. Case studies are conducted and results show that the proposed game theory-based decentralized control strategy can increase the aggregated peak Demand reduction and electricity cost saving more than two times compared with that when the Demand Management of building cluster is conducted in an uncoordinated manner. Meanwhile, the control performance of proposed decentralized strategy is close to that using a perfect Demand Management control strategy.
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model based optimal design of active cool thermal energy storage for maximal life cycle cost saving from Demand Management in commercial buildings
Applied Energy, 2017Co-Authors: Fu Xiao, Borui Cui, Diance Gao, Shengwei WangAbstract:This paper provides a method to evaluate the cost-saving potential of active cool thermal energy storage (CTES) integrated with HVAC system for Demand Management in commercial building. Active storage is capable of shifting peak Demand for peak load Management (PLM) as well as providing longer duration and larger capacity for Demand response (DR). In this research, a model-based optimal design method using genetic algorithm is developed to optimize the capacity of active CTES for maximizing the life-cycle cost saving including capital cost associated with storage capacity as well as incentives from both fast DR and PLM. In the method, the active CTES operates under a fast DR control strategy during DR events and under the storage-priority operation mode to shift peak Demand during normal days. The optimal storage capacities, maximum annual net cost saving and corresponding power reduction set-points during DR events are obtained by using the proposed optimal design method. This research provides guidance in comprehensive evaluation of the cost-saving potential of active CTES integrated with HVAC system for building Demand Management including both fast DR and PLM.
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an interactive building power Demand Management strategy for facilitating smart grid optimization
Applied Energy, 2014Co-Authors: Xue Xue, Yongjun Sun, Shengwei Wang, Fu XiaoAbstract:With increasing use and integration of renewable energies, power imbalance between supply and Demand sides has become one of the most critical issues in developing smart grid. As the major power consumers at Demand side, buildings can actually perform as distributed thermal storages to help relieving power imbalance of a grid. However, power Demand alteration potentials of buildings and energy information of grids might not be effectively predicted and communicated for interaction and optimization. This paper presents an interactive building power Demand Management strategy for the interaction of commercial buildings with a smart grid and facilitating the grid optimization. A simplified building thermal storage model is developed for predicting and characterizing power Demand alteration potentials of individual buildings together with a model for predicting the normal power Demand profiles of buildings. The simulation test results show that commercial buildings can contribute significantly and effectively in power Demand Management or alterations with building power Demand characteristics identified properly.
Khandker Nurul Habib - One of the best experts on this subject based on the ideXlab platform.
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stated preference survey pivoted on revealed preference survey for evaluating employer based travel Demand Management strategies
Transportation Research Record, 2017Co-Authors: Sami M Hasnine, Adam Weiss, Khandker Nurul HabibAbstract:This paper presents a study of commuters’ responses to various employer-based transportation Demand Management (TDM) strategies that was conducted in the Region of Peel, Ontario, Canada. The study involves design and implementation of a web-based survey of daily commuting mode choices and an efficient design-based stated preference (SP) experiment on the mode choice effects of potential employer-based TDM strategies. For the SP experiments, the survey also collected an elicited confidence rating from the respondents. The survey of 835 random commuters was conducted in fall 2014 and spring 2015. The paper uses empirical models of mode choices (revealed and stated) and an ordered probability model of the elicited confidence rating information to evaluate the data quality. The empirical models reveal that parking cost, monthly parking scheme, indoor parking facilities, emergency ride home, and bike share had higher impacts on commuting mode choices than did bike access facilities and a carshare strategy at t...
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development of an employer based transportation Demand Management strategy evaluation tool with an advanced discrete choice model in its core
Transportation Research Record, 2016Co-Authors: Sami M Hasnine, Adam Weiss, Khandker Nurul HabibAbstract:This paper presents a tool for the evaluation of employer-based transportation Demand Management (TDM) strategies. The conventional method of evaluating TDM strategies has typically been to conduct expensive before-and-after strategy implementation surveys. As an alternative approach, this research uses a joint revealed preference (RP) and stated preference (SP) survey (the RP–SP survey) administered before deployment of the TDM strategy, which is more cost-effective and efficient. The data collected from the RP–SP survey were used to estimate an advanced discrete choice model, which was packaged into a spreadsheet-based tool for TDM decision support. The tool adopted the concept of penetration rate, whereby only a subset of the target population could be targeted for any specific TDM strategy. The tool that was developed provides an alternative approach for the predeployment evaluation of any TDM strategy for efficient implementation. Moreover, the empirical model used in the tool reveals many behavioral...
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commuting mode choice in the context of travel Demand Management tdm policies an empirical investigation in edmonton alberta
Canadian Journal of Civil Engineering, 2011Co-Authors: Hamid Zaman, Khandker Nurul HabibAbstract:Travel Demand Management (TDM) for achieving sustainability is now considered one of the most important aspects of transportation planning and operation. It is now a well known fact that excessive use of private car results inefficient travel behaviour. So, from the TDM perspective, it is of great importance to analyze travel behaviour for improving our understanding on how to influence people to reduce car use and choose more sustainable modes such as carpool, public transit, park & ride, walk, bike etc. This study attempts an in-depth analysis of commuting mode choice behaviour using a week-long commuter survey data set collected in the City of Edmonton. Using error correlated nested logit model for panel data, this study investigates sensitivities of various factors including some specific TDM policies such as flexible office hours, compressed work week etc. Results of the investigation provide profound understanding and guidelines for designing effective TDM policies.