Review comments on manuscript HESS-2016-522 “Coupling urban drainage-wastewater system and electric smart grids during dry periods: A gain/loss framework using the relative economic value with ensemble flow forecasts to predict the switch between manage

2016 ◽  
Author(s):  
Anonymous
Keyword(s):  
Smart Grids ◽  
Economic Value ◽  
Urban Drainage ◽  
Gain Loss

scholarly journals Coupling urban drainage–wastewater systems and electric smart grids during dry periods: a gain/loss framework using the relative economic value with ensemble flow forecasts to predict the switch between management objectives

2016 ◽  
Author(s):  
Vianney Courdent ◽  
Morten Grum ◽  
Thomas Munk-Nielsen ◽  
Peter S. Mikkelsen
Keyword(s):  
Smart Grids ◽  
Weather Prediction ◽  
Economic Value ◽  
Decision Makers ◽  
Low Flow ◽  
Mitigation Measures ◽  
Ensemble Prediction ◽  
Urban Drainage ◽  
Wastewater Systems ◽  
Gain Loss

Abstract. Precipitation is the major perturbation to the flow in urban drainage and wastewater systems. Flow forecast, generated by coupling rainfall predictions with a hydrologic runoff model, can potentially be used to optimise the operation of Integrated Urban Drainage–Wastewater Systems (IUDWS) during both wet and dry weather periods. Numerical Weather Prediction (NWP) models have significantly improved in recent years; increasing their spatial and temporal resolution. Finer resolution NWP are suitable for urban catchment scale applications, providing longer lead time than radar extrapolation. However, forecasts are inevitably uncertain and fine resolution is especially challenging for NWP. This uncertainty is commonly addressed in meteorology with Ensemble Prediction Systems (EPS). Handling uncertainty is challenging for decision makers and hence tools are necessary to provide insight on ensemble forecast usage and to support the rationality of decisions (i.e. forecasts are uncertain therefore errors will be made, decision makers need tools to justify their choices, demonstrating that these choices are beneficial in the long run). This study presents an economic framework to support the decision making process by providing information on when acting on the forecast is beneficial and how to handle the EPS. The Relative Economic Value (REV) approach associates economic values to the potential outcomes and determines the preferential use of the EPS forecast. The envelope curve of the REV diagram combines the results from each probability forecast to provide the highest relative economic value for a given gain-loss ratio. This approach is traditionally used at larger scales to assess mitigation measures for adverse events (i.e. the actions are taken when events are forecasted). The specificity of this study is to optimise the energy consumption in IUDWS during low flow periods by exploiting the electrical smart grid market (i.e. the actions are taken when no events are forecasted). Furthermore, the results demonstrate the benefit of NWP neighbourhood post-processing methods to enhance the forecast skill and increase the range of beneficial use.

scholarly journals A gain–loss framework based on ensemble flow forecasts to switch the urban drainage–wastewater system management towards energy optimization during dry periods

2017 ◽  
Vol 21 (5) ◽  
pp. 2531-2544 ◽  
Author(s):  
Vianney Courdent ◽  
Morten Grum ◽  
Thomas Munk-Nielsen ◽  
Peter S. Mikkelsen
Keyword(s):  
Weather Prediction ◽  
Economic Value ◽  
Decision Makers ◽  
Low Flow ◽  
Mitigation Measures ◽  
Ensemble Prediction ◽  
Urban Drainage ◽  
Catchment Scale ◽  
Wastewater Systems ◽  
Gain Loss

Abstract. Precipitation is the cause of major perturbation to the flow in urban drainage and wastewater systems. Flow forecasts, generated by coupling rainfall predictions with a hydrologic runoff model, can potentially be used to optimize the operation of integrated urban drainage–wastewater systems (IUDWSs) during both wet and dry weather periods. Numerical weather prediction (NWP) models have significantly improved in recent years, having increased their spatial and temporal resolution. Finer resolution NWP are suitable for urban-catchment-scale applications, providing longer lead time than radar extrapolation. However, forecasts are inevitably uncertain, and fine resolution is especially challenging for NWP. This uncertainty is commonly addressed in meteorology with ensemble prediction systems (EPSs). Handling uncertainty is challenging for decision makers and hence tools are necessary to provide insight on ensemble forecast usage and to support the rationality of decisions (i.e. forecasts are uncertain and therefore errors will be made; decision makers need tools to justify their choices, demonstrating that these choices are beneficial in the long run). This study presents an economic framework to support the decision-making process by providing information on when acting on the forecast is beneficial and how to handle the EPS. The relative economic value (REV) approach associates economic values with the potential outcomes and determines the preferential use of the EPS forecast. The envelope curve of the REV diagram combines the results from each probability forecast to provide the highest relative economic value for a given gain–loss ratio. This approach is traditionally used at larger scales to assess mitigation measures for adverse events (i.e. the actions are taken when events are forecast). The specificity of this study is to optimize the energy consumption in IUDWS during low-flow periods by exploiting the electrical smart grid market (i.e. the actions are taken when no events are forecast). Furthermore, the results demonstrate the benefit of NWP neighbourhood post-processing methods to enhance the forecast skill and increase the range of beneficial uses.

scholarly journals Risk management reconceived: reconciling economic rationality with behavioural tendencies

2010 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Ruth Murray-Webster ◽  
Sergio Pellegrinelli
Keyword(s):  
Risk Management ◽  
Management Practices ◽  
Economic Value ◽  
Project Planning ◽  
Economic Rationality ◽  
Planning And Control ◽  
Gain Loss ◽  
Audit Activity ◽  
And Control ◽  
Biases And Heuristics

Risk management practices as described in many leading texts feel counterintuitive to many practitioners and are frequently ignored, despite their being evidently logical and potentially valuable. Such practices are often conceived as a remedial post-planning, audit activity. This paper proposes an approach for dealing with project uncertainty and risk, grounded in economics and taking into account behavioural biases and heuristics. The proposed approach is argued to be an enhancement to conventional risk management practices and one that can serve organisations better while also aligning to experienced practitioners’ intuitive approaches. In particular, we argue: that the focus should be on adding economic value rather than reducing risk per se; that opportunity gain/loss is a superior metric for gauging potential impacts of risky events; and that creation of real options should be emphasised as part of the repertoire of generic response actions to risk. The approach also supports the integration and handling of uncertainty and risk as part of holistic project planning and control.

scholarly journals Fair and Secure Multi-Party Computation with Cheater Detection

Cryptography ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 19
Author(s):  
Minhye Seo
Keyword(s):  
Smart Grids ◽  
Economic Value ◽  
Computational Cost ◽  
Cryptographic Protocol ◽  
Universal Composability ◽  
Critical Problem ◽  
Cheater Detection ◽  
Final Output ◽  
Real Time Information ◽  
Time Information

Secure multi-party computation (SMC) is a cryptographic protocol that allows participants to compute the desired output without revealing their inputs. A variety of results related to increasing the efficiency of SMC protocol have been reported, and thus, SMC can be used in various applications. With the SMC protocol in smart grids, it becomes possible to obtain information for load balancing and various statistics, without revealing sensitive user information. To prevent malicious users from tampering with input values, SMC requires cheater detection. Several studies have been conducted on SMC with cheater detection, but none of these has been able to guarantee the fairness of the protocol. In such cases, only a malicious user can obtain a correct output prior to detection. This can be a critical problem if the result of the computation is real-time information of considerable economic value. In this paper, we propose a fair and secure multi-party computation protocol, which detects malicious parties participating in the protocol before computing the final output and prevents them from obtaining it. The security of our protocol is proven in the universal composability framework. Furthermore, we develop an enhanced version of the protocol that is more efficient when computing an average after detecting cheaters. We apply the proposed protocols to a smart grid as an application and analyze their efficiency in terms of computational cost.

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