This paper examines two environmental impacts for which population has a substantial demonstrated influence: transport carbon emissions and residential electricity consumption. It takes as its starting point the STIRPAT framework and disaggregates population into four key age groups: 20-34, 35-49, 50-69, and 70 and older. Population age structure’s influence was significant and varied across co...

-The design of wholesale electricity markets through deregulation has focused almost exclusively on the development of competitive supply (generation). The demand side of the market has been virtually ignored. Mostly, this is due to the assumption that electricity demand is almost completely inelastic. As a result, deregulated wholesale markets universally fail to pass price signals down to the...

Energy consumption in buildings accounts for about 40% of total energy consumption [1]. The residential sector alone has seen a rise in electricity consumption by 54% since 1991 [2]. To a large extend, this increase can be traced back to the growing number of electrical appliances. While most large appliances (e.g., dishwashers, washing machines, etc.) have become more efficient over the years,...

The recent rapid uptake of residential solar photovoltaic (PV) installations provides many challenges for electricity distribution networks designed for one-way power flow from the distribution company to the residential customer. In particular, for grid-connected installations, intermittent generation as well as large amounts of generation during low load periods can lead to a degradation of p...

Electricity provisioning has historically satisfied demand by centralized generation and pervasive distribution through an extensive transmission and distribution network. Once demand increases beyond a fixed threshold, however, the capacity of the generation, transmission and distribution can become crippled and the mal-effects of periodic brownouts and skyrocketing prices may ripple through t...

In this study several Artificial Neural Network (ANN) models were experimented to predict electricity consumption for a residential house in New Zealand. The effect of number of users in the house, day of the week and weather variables on electricity consumption was analyzed. Each model has been constructed using different structures, learning algorithms and transfer functions in order to come ...

Smart meters are increasingly being deployed to measure electricity consumption of residential as well as non-residential consumers. The readings reported by these meters form a time series, which is stored at electric utility servers for billing purposes. Invalid readings may be reported because of malicious compromise of the smart meters themselves, or of the network infrastructure that suppo...

In order to meet ambitious emission reduction goals in California, greenhouse gas emissions from direct combustion of fossil fuels for residential space and water heating will need to be largely eliminated. If those emission reductions come from fuel switching (natural gas to electricity) then the electricity grid needs to be prepared for the additional load. This paper presents a new method fo...

This paper takes advantage of a natural experiment in the state of Indiana to estimate the effect of Daylight Saving Time (DST) on residential electricity consumption. Our main finding is that—contrary to the policy’s intent—DST increases residential electricity demand. Estimates of the overall increase are approximately 1 percent, but DST causes the greatest increase in electricity consumption...

There is growing interest in reducing energy use and emissions of carbon dioxide from the residential sector by deploying cost-effectiveness energy efficiency measures. However, there is still large uncertainty about the magnitude of the reductions that could be achieved by pursuing different energy efficiency measures across the nation. Using detailed estimates of the current inventory and per...