Domestic lighting: A high-resolution energy demand model

The use of electric lighting in the domestic sector depends mainly on the level of natural light coming in from outdoors, coupled with the activity of the household residents. This paper presents a detailed model of domestic lighting use that takes these two factors as its basic inputs. The operation of individual bulbs is represented within the model and is used to construct high-resolution lighting electricity demand profiles for individual dwellings. The model is computationally efficient and can easily provide data at 1-min resolution for large numbers of dwellings. As a primary input, the model uses a time-series representing the number of active occupants within a dwelling (people who are at home and awake). This allows it to represent the sharing of lighting between the occupants of a given dwelling and facilitates correlated linking to models of other energy use within the dwelling. Appropriate correlation between dwellings is achieved through the use of appropriate active occupancy data and outdoor ambient light data. An example implementation of the model in Microsoft Excel is available for free download.     

A high-resolution domestic building occupancy model for energy demand simulations

Energy use in the home is a major source of carbon emissions and is highly dependent on the activities of the residents. More specifically, the timing of energy use, particularly electricity, is highly dependent on the timing of the occupants’ activities. Thus, in order to model domestic demand profiles with high temporal resolution, for example, in the context of designing and assessing demand side management systems (including the time-shifting of demand), it is of great benefit to take account of residents’ behaviour in terms of when they are likely to be using household appliances, lighting and heating. This paper presents a thorough and detailed method for generating realistic occupancy data for UK households, based upon surveyed time-use data describing what people do and when. The approach presented generates statistical occupancy time-series data at a ten-minute resolution and takes account of differences between weekdays and weekends. The model also indicates the number of occupants that are active within a house at a given time, which is important for example in order to model the sharing of energy use (shared use of appliances, etc.) The data from the model can be used as input to any domestic energy model that uses occupancy time-series as a base variable, or any other application that requires detailed occupancy data. The model has been implemented in Excel and is available for free download.     

Time-based pricing and electricity demand response: Existing barriers and next steps

Interest in Demand Response (DR) is increasing due to its potential to improve reliability and save costs for electricity systems. DR can provide a sustainable and cost-effective option for supply balancing, especially in a scenario with more volatile inflows from renewable energy sources. End-users can be incentivized to provide DR through time-based pricing in general and dynamic pricing in particular. This paper provides a theoretic framework and practice-oriented review of the status of DR in Europe, outlining the major challenges currently hampering further DR development. Important challenges involve the split-incentive issue for investments in enabling technologies, traditional market rules for flexibility that favor large generation units and the need for electricity market and network operation coordination.     

Revenue decoupling,energy demand,and energy efficiency: Empirical evidence from the U.S. electricity sector

This paper investigates the relationship between the regulatory policy revenue decoupling, which separates utilities’ revenue from sales fluctuations, and electricity customers’ energy demand and efficiency in the U.S. electricity sector. To this end, we use recent Stochastic Frontier Analysis estimation techniques that account for both persistent and transient energy efficiency. The results show a significant negative correlation between decoupling and electricity consumption. However, the implementation year, which serves as a reference for price adjustments, is associated with increasing electricity demand and decreasing transient energy efficiency. Therefore, utilities seem to anticipate the implementation of decoupling, which partially offsets the benefits.     

The significance of occupancy steadiness in residential consumer response to Time-of-Use pricing: Evidence from a stochastic adjustment model

The recent roll-out of smart metering technologies in several developed countries has intensified research on the impacts of Time-of-Use (TOU) pricing on consumption. This paper analyses a TOU dataset from the Province of Trento in Northern Italy using a stochastic adjustment model. Findings highlight the non-steadiness of the relationship between consumption and TOU price. Weather and active occupancy can partly explain future consumption in relation to price.     

Heterogeneity in own-price residential customer demand elasticities for electricity under time-of-use rates: Evidence from a randomized-control trial in the United States

Regulators, policymakers, and stakeholders in several states have raised concerns about the price elasticity of residential customers’ electricity demand, especially as related to different customer subpopulations, management of critical end-uses, and enrollment approaches. This analysis sought to quantify the diversity of residential customer price elasticity in a time-of-use rate across these different dimensions using data generated from a utility pricing experiment. Customers were found to be more elastic during the peak period of critical peak days, who were predicted to own and use air conditioning, and who volunteered for time-of-use (TOU) rates (but those defaulted on were 25% as elastic).     

Improvement of customer baselines for the evaluation of demand response through the use of physically-based load models

Demand Response (DR) is an opportunity and a concern for markets as well as power system flexibility. The deployment of DR depends on both knowledge on its performance and how to measure it effectively to provide adequate economic feedback. DR verification requires a baseline reference. This paper introduces a new baseline that provides an evaluation of response based on simple adjustment factors through physically-based models, tools which are also used in DR. The approach includes the detection of licit and gaming responses before and after DR. Results show that errors decrease by 10–15% with respect to conventional approaches.     

Rooftop photovoltaic (PV) systems for industrial halls: Achieving economic benefit via lowering energy demand

Industrial halls are characterized with their relatively high roof-to-floor ratio, which facilitates ready deployment of renewable energy generation, such as photovoltaic (PV) systems, on the rooftop. To promote deployment of renewable energy generation, feed-in tariff (FIT) higher than the electricity rate is available in many countries to subsidize the capital investment. FIT comes in different forms. For net FIT, in order to maximize the economic benefit, surplus electricity generation at each hour is desirable.One way to achieve surplus electricity generation is by increasing generation capacity, which is synonymous to higher capital investment. In fact, surplus electricity generation can also be achieved by lowering the energy demand of the building. This particularly the case for industrial halls, which are usually subject to high energy demand for space conditioning in order to remove the excess heat gain due to the many power-intensive processes.Building energy performance simulation tools can be used to explore the different building design options that could lower the energy demand. In this paper, single-objective optimization on investment return will be deployed to study the cost effectiveness among different options in lowering energy demand. It will be demonstrated with a case study of a warehouse.     

Urban Physics: Effect of the micro-climate on comfort,health and energy demand

The global trend towards urbanisation explains the growing interest in the study of the modification of the urban climate due to the heat island effect and global warming, and its impact on energy use of buildings. Also urban comfort, health and durability, referring respectively to pedestrian wind/thermal comfort, pollutant dispersion and wind-driven rain are of interest. Urban Physics is a well-established discipline, incorporating relevant branches of physics, environmental chemistry, aerodynamics, meteorology and statistics. Therefore, Urban Physics is well positioned to provide key-contributions to the current urban problems and challenges. The present paper addresses the role of Urban Physics in the study of wind comfort, thermal comfort, energy demand, pollutant dispersion and wind-driven rain. Furthermore, the three major research methods applied in Urban Physics, namely field experiments, wind tunnel experiments and numerical simulations are discussed. Case studies illustrate the current challenges and the relevant contributions of Urban Physics.     

A future bamboo-structure residential building prototype in China: Life cycle assessment of energy use and carbon emission

In this study, the material-based energy use and carbon emission over the life cycle of a bamboo-structure residential building prototype with innovative insulation technologies are analyzed. In comparison with a typical brick-concrete building, the bamboo-structure building requires less energy and emits less carbon dioxide to meet the identical functional requirements, i.e., envelope insulation and structure supporting. In order to systematically assess the energy use and carbon emission, several scenarios are designed based on the LEED standard and the technical potentials. The results indicate that there is a potential to reduce 11.0% (18.5%) of the embodied energy (carbon) for the use of recycled-content building materials and 51.3% (69.2%) for the recycling of construction and demolition waste, respectively. However, the practical effect of the potentials varies significantly depending on project management levels and available technologies in the current market. The analysis provides an insight into the assessment of the material-based energy use and carbon emission over the life cycle of a building.     

The use of a double heat pipe heat exchanger system for reducing energy consumption of treating ventilation air in an operating theatre—A full year energy consumption model simulation

In two earlier papers [Y.H. Yau, Application of a heat pipe heat exchanger to dehumidification enhancement in tropical HVAC systems—a baseline performance characteristics study, International Journal of Thermal Sciences 46 (2) (2007) 164–171; Y.H. Yau, The analysis of enthalpy change with and without a heat pipe heat exchanger in a tropical air conditioning system, International Journal of Energy Research 30 (15) (2006) 1251–1263], two series of experiments were conducted under controlled conditions to establish the baseline performance characteristics of the heat pipe heat exchanger (HPHX). In the present paper, a complete empirical transient systems simulation program model is assembled to estimate the air states as well as the entire typical meteorological year energy consumption of an operating theatre located in Kuala Lumpur, Malaysia.     

Spatial and temporal dynamics of land use pattern in Turkey: A case study in İnegöl

Recognition and understanding of landscape dynamics as a historical legacy of disturbances are necessary for sustainable management of forest ecosystems. This study analyzed forest dynamics and spatial–temporal changes in land use/land cover pattern in a sub-temperate like alluvial forest land with 1778 km² area along the Eagan Sea coast of Turkey (İnegöl). This area is studied by comparing Landsat images from 1987 to 2001 and evaluated with spatial analyses of forest cover type maps from 1972, 1983, 1993 to 2004 using GIS. The study investigated temporal changes of spatial structure of forest conditions over the period using Fragstats™.The results showed that the forested areas increased both in between 1972 and 1993 years (3.3%) and between 1987 and 2001 years (6.7%). In terms of spatial configuration, İnegöl forests are generally fragmented in the latter periods due to intensive forest utilization, illegal use, expansion of settlements and infrastructural development in the lowlands. Land use pattern significantly changed over time depending on a few factors such as unregulated management actions, social pressure and demographic movements. In conclusion, land use changes have developed in favor of forestry over time between 1972–1993 and 1987–2001. The study revealed that demographic movements have a minor effect on landscape dynamics. Both spatial and temporal changes and the factors affecting these changes should be determined for developing sustainable management of forest resources.     

Analytical frameworks to incorporate demand response in long-term resource planning

Many utilities are obligated by state regulatory or legislative requirements to consider demand response (DR) as part of their resource planning process. There are several ways to incorporate DR into resource planning modeling and each has its advantages and disadvantages. We explore the current analytical frameworks for incorporating DR into long-term resource planning. We also consider whether current approaches accurately and realistically model DR resources in capacity expansion and production cost models and whether barriers exist to incorporating DR into resource planning models in a more robust fashion. We identify 10 specific recommendations for enhancing and expanding the current approaches.