Creative User-Centered Visualization Design for Energy Analysts and Modelers

We enhance a user-centered design process with techniques that deliberately promote creativity to identify opportunities for the visualization of data generated by a major energy supplier. Visualization prototypes developed in this way prove effective in a situation whereby data sets are largely unknown and requirements open – enabling successful exploration of possibilities for visualization in Smart Home data analysis. The process gives rise to novel designs and design metaphors including data sculpting. It suggests: that the deliberate use of creativity techniques with data stakeholders is likely to contribute to successful, novel and effective solutions; that being explicit about creativity may contribute to designers developing creative solutions; that using creativity techniques early in the design process may result in a creative approach persisting throughout the process. The work constitutes the first systematic visualization design for a data rich source that will be increasingly important to energy suppliers and consumers as Smart Meter technology is widely deployed. It is novel in explicitly employing creativity techniques at the requirements stage of visualization design and development, paving the way for further use and study of creativity methods in visualization design

Potential Economic Consequences of Local Nonconformity to Regional Land Use and Transportation Plans Using a Spatial Economic Model

To achieve the greenhouse gas (GHG) reduction targets that are required by California’s global warming legislation (AB32), the state of California has determined that recent growth trends in vehicle miles traveled (VMT) must be curtailed. In recognition of this, Senate Bill 375 (SB375) requires regional governments to develop land use and transportation plans or Sustainable Community Strategies (SCSs) that will achieve regional GHG targets largely though reduced VMT. Although the bill requires such a plan, it does not require local governments to adopt general plans that conform to this plan. In California, it is local, not regional, governments that have authority over land development decisions. Instead, SB375 relies on democratic participatory processes and relatively modest financial and regulatory incentives for SCS implementation. As a result, it is quite possible that some local governments within a region may decide not to conform to their SCS. In this study, a spatial economic model (PECAS) is applied in the Sacramento region (California, U.S.) to understand what the economic and equity consequences might be to jurisdictions that do and do not implement SCS land use plans in a region. An understanding of these consequences provides insight into jurisdictions’ motivations for compliance and thus, strategies for more effective implementation of SB375

Li-BIM, an agent-based approach to simulate occupant-building interaction from the Building-Information Modelling

International audienceBuilding design involves many challenges and requires to take into account the interaction between the building and the users. Different occupant behaviour models implemented with building simulation tools (thermal, air quality, lighting) have been proposed. Among these, models based on the agent approach seem to be the most promising. However, existing models poorly describe human cognition and the social dimension. Moreover, they are often oriented towards a specific use (thermal simulation, waste management) without being transposable to another field, and they require a significant instantiation effort for each new case, making their use difficult. This article proposes an agent-based model called Li-BIM that simulates the behaviour of the occupants in a building and their indoor comfort. Li-BIM model is structured around the numerical modelling of the building-BIM-(with standard exchange format IFC), a high-resolution cognitive model, and the coupling with various physical models. Li-BIM simulates the reactive, deliberative and social behaviour of occupants in residential dwellings based on the Belief-Desire-Intention architecture. This model, thanks its ease of use and flexibility, is an operational and relevant tool to support building design process with a human-centred approach. An application of the model is presented, focusing on energy consumption and the inhabitants' comfort. In-situ data obtained from the instrumented house that served as case study have been compared with simulation results from Li-BIM and a standard energy simulation software, demonstrating the reliability of the proposed model

Simulating the Impact on the Local Economy of Alternative Management Scenarios for Natural Areas

This working paper estimates the impact on the local economy of the High Garda Natural Park of alternative management scenarios for the West Garda Regional Forest. The local economy is specialized in tourist services and strongly linked to the tourist presence and their level of expenditure. We wish to investigate the effects of the participative management strategy, which takes into account users preferences and the non-participative strategy, using the SAM multiplier analysis. The local SAM has been constructed considering three sectors: agriculture, tourism and a third aggregate sector including all the other activities. The resident population has been divided into two categories: residents employed in the tourist sector and the remaining resident population. The SAM analysis shows that the accounting representation of the local economy is meaningful and that the participative program, if chosen by the central regional management, would be the most desirable program also at the local level.Tourism, SAM, Multiplier analysis

Is undernutrition responsive to changes in incomes?

This paper discusses the effect that changes in individual incomes have on aggregate undernutrition. Undernutrition depends not only on nutrient intakes but on other factors, including nutrient requirements - which may differ widely amongst people. The author offers an approach to measuring the effects of shifts in budget constraints or other household parameters on undernutrition. Using household data on calorie consumption, income, prices, and other household characteristics, theaper illustrates how to: (a) estimate caloric intake functions for that data; and (b) use those functions to simulatethe effects of income changes on various measures of caloric undernutrition. The paper finds that the income elasticity of measured undernutrition is considerably higher than the income elasticity of individual caloric intakes. The reason is that the density of people tends to be high in a neighborhood of requirement norms, and intake responses tend to be highest amongst those who are least well nourished. Recent arguments that intakes are unresponsive to income changes should thus be interpreted with caution.Poverty Diagnostics,Environmental Economics&Policies,Economic Theory&Research,Inequality,Poverty Lines

Urban metabolism and land use modeling for urban designers and planners: A land use model for the Integrated Urban Metabolism Analysis Tool

Predicting the resource consumption in the built environment and its associated environmental consequences (urban metabolism analysis) is one of the core challenges facing policy-makers and planners seeking to increase the sustainability of urban areas. There is a critical need for a single integrated framework to analyze the consequences of urban growth and eventually predict the impacts of sustainable policies on the urbanscape. This dissertation presents the development of an Integrated Urban Metabolism Analysis Tool (IUMAT) – an analytical framework that simulates urban metabolism by integrating urban subsystems in a single comprehensive computational environment. It reviews the existing literature on urban sustainability, urban metabolism, as well as introducing the general framework for IUMAT. IUMAT uses three separate models for quantifying environmental impacts of land-use transition, consumption of resources, and transportation. This work outlines the development of IUMAT Land-Use Model that uses Remote Sensing, GIS, and Artificial Neural Networks (ANNs) to predict land use change patterns. By using Density-Based Spatial Clustering and normal equations, this dissertation introduces a method for generating building-form variables from Light Detection and Ranging (LIDAR) data, which can be used as a new determinant factor in land-use change modeling. The proposed Land-use Model, within IUMAT or other analytical models, can be useful to local planning officials in understanding the complexity of land-use change and developing enhanced land-use policies

An Economic and Life Cycle Analysis of Regional Land Use and Transportation Plans, Research Report 11-25

Travel and emissions models are commonly applied to evaluate the change in passenger and commercial travel and associated greenhouse gas (GHG) emissions from land use and transportation plans. Analyses conducted by the Sacramento Area Council of Governments predict a decline in such travel and emissions from their land use and transportation plan (the “Preferred Blueprint” or PRB scenario) relative to a “Business-As-Usual” scenario (BAU). However, the lifecycle GHG effects due to changes in production and consumption associated with transportation and land use plans are rarely, if ever, conducted. An earlier study conducted by the authors, applied a spatial economic model (Sacramento PECAS) to the PRB plan and found that lower labor, transport, and rental costs increased producer and consumer surplus and production and consumption relative to the BAU. As a result, lifecycle GHG emissions from these upstream economic activities may increase. At the same time, lifecycle GHG emissions associated with the manufacture of construction materials for housing may decline due to a shift in the plan from larger luxury homes to smaller multi-family homes in the plan. To explore the net impact of these opposing GHG impacts, the current study used the economic production and consumption data from the PRB and BAU scenarios as simulated with the Sacramento PECAS model as inputs to estimate the change in lifecycle GHG emissions. The economic input-output lifecycle assessment model is applied to evaluate effects related to changes in economic production and consumption as well as housing construction. This study also builds on the findings from two previous studies, which suggest potential economic incentives for jurisdictional non-compliance with Sustainable Communities Strategies (SCSs) under Senate Bill 375 (also known as the “anti-sprawl” bill). SB 375 does not require local governments to adopt general plans that are consistent with the land use plans included in SCSs, and thus such incentives could jeopardize implementation of SCSs and achievement of GHG goals. In this study, a set of scenarios is simulated with the Sacramento PECAS model, in which multiple jurisdictions partially pursue the BAU at differing rates. The PRB is treated as a straw or example SCS. The scenarios are evaluated to understand how non-conformity may influence the supply of housing by type, and holding other factors constant, the geographic and income distribution of rents, wages, commute costs, and consumer surplus

Remittances and Poverty Linkages in Pakistan: Evidence and Some Suggestions for Further Analysis

Global remittances experienced a dramatic increase over the years, particularly since 1990 wherein the developing world emerged to be the major beneficiary accounting for 60 percent of the total amount. Because of the sheer volume, and magnitude of the remittances, and pre-eminence of these flows compared to the FDIs, development assistance and in some cases the trade related transactions, the development practitioners tended to focus and investigate the importance of remittances which are generally regarded as a dependable source for growth, improved welfare and poverty alleviation in the developing world. Given the fact that remittances flows entail wide ranging ramifications both for sending as well as receiving countries, difficult to be generalised, hence empirical evidence has been mounted though lack of consensus is visible.

Data Mining to Uncover Heterogeneous Water Use Behaviors From Smart Meter Data

Knowledge on the determinants and patterns of water demand for different consumers supports the design of customized demand management strategies. Smart meters coupled with big data analytics tools create a unique opportunity to support such strategies. Yet, at present, the information content of smart meter data is not fully mined and usually needs to be complemented with water fixture inventory and survey data to achieve detailed customer segmentation based on end use water usage. In this paper, we developed a data‐driven approach that extracts information on heterogeneous water end use routines, main end use components, and temporal characteristics, only via data mining existing smart meter readings at the scale of individual households. We tested our approach on data from 327 households in Australia, each monitored with smart meters logging water use readings every 5 s. As part of the approach, we first disaggregated the household‐level water use time series into different end uses via Autoflow. We then adapted a customer segmentation based on eigenbehavior analysis to discriminate among heterogeneous water end use routines and identify clusters of consumers presenting similar routines. Results revealed three main water end use profile clusters, each characterized by a primary end use: shower, clothes washing, and irrigation. Time‐of‐use and intensity‐of‐use differences exist within each class, as well as different characteristics of regularity and periodicity over time. Our customer segmentation analysis approach provides utilities with a concise snapshot of recurrent water use routines from smart meter data and can be used to support customized demand management strategies.TU Berlin, Open-Access-Mittel - 201

Integrated models of transport and energy demand: A literature review and framework

Energy and transport demand can both be considered as being derived from an individual’s activity participation. As such, both energy and transport demand are inherently linked: completing activities inside the home generates residential energy demand, where completing activities outside the home generates transportation and non-residential energy demand. Whilst there are several works in the literature that focus on either energy or transportation demand, there remain very few studies which explicitly investigate their interaction. To address this need, in this paper we conduct in-depth literature review of transportation and energy demand modeling. The review analyses the methodologies employed within each domain in order to (a) establish the state-of-research for energy demand modeling and (b) identify the suitable opportunities for joining these two domains. Drawing on a review of the current papers, we identify four key areas of practice: (i) activity scheduling, (ii) building energy demand, (iii) transportation energy demand, and (iv) the integration of components. Finally, based on the findings from the review, we propose a new framework for joint building and transportation energy demand modeling at an urban scale