Kazunori Nagasawa

Data management for a large-scale smart grid demonstration project in Austin, Texas

This paper presents a data management scheme for the Pecan Street smart grid demonstration project in Austin, Texas. In this project, highly granular data with 15-second resolution on resource generation and consumption, including total consumption of electricity, water, and natural gas and solar generation, are collected for more than 100 homes. Furthermore, this testbed, see Figure 1, of homes represents the nation’s highest density of rooftop solar PV and electric vehicles, and includes a substantial subset of homes that are highly instrumented with meters on up to 6 sub-circuits in addition to the whole-home meter. Consequently, this demonstration project generates a one-of-a-kind dataset with excellent temporal and geographic fidelity.One consequence of this extensive dataset is that there are hundreds of parallel data streams that need to be remotely (wirelessly) collected, filtered, processed, managed, stored and analyzed to be useful for researchers. Cumulatively, they represent 100s of gigabytes of data after just a few months of collection, which represents a formidable barrier to conducting research.In partnership with the Texas Advanced Computing Center (TACC), which is an NSF-sponsored cluster of supercomputers at UT-Austin, a data collection and management scheme has been developed. For storing the data, we have built a single column oriented database that so far has shown tremendous performance benefits. This paper shows the data schema, an example of MySQL query, and a developed program for rapid and automated data extraction, analysis and display. We expect that the findings of this work will be beneficial to researchers interested in grid-scale data management.© 2012 ASME

The Net Impact of Wind Energy Generation on Emissions of Carbon Dioxide in Texas

This analysis will examine the relationship between increased levels of wind energy generation and emissions per unit of electricity produced using historical data for electricity output and CO2, SO2 and NOx emissions in the Electric Reliability Council of Texas (ERCOT). Renewable Portfolio Standards (RPS) are generally seen in part as a policy tool for reducing overall system CO2 emissions, although renewable energy goals do not directly regulate such emissions. Limiting this analysis to ERCOT provides two important advantages: transmission of wind energy output is constrained by the physical boundaries of the ERCOT grid, simplifying the analysis and avoiding associated ‘leakage issues’; and ERCOT has the highest level of wind generation as a percentage of total system demand of any grid in the continental U.S.The intermittent nature of wind generation has resulted in the need to ramp conventional thermal generation up and down to compensate for variability in wind output. Such ramping leads to inefficiencies in many fossil-fueled power plants that increase emissions of CO2, SO2, and NOx relative to a respective unit’s peak efficiency emissions rate.Using EPA’s Clean Air Markets hourly emissions data, we calculate the total combustion emissions of CO2, SO2 and NOx per MWh of electricity output for the ERCOT system from 2003–2011. The EPA database includes CO2, SO2 and NOx emissions reported by facility owner and operators on an hourly basis in a manner that incorporates facility inefficiencies during ramping periods, allowing us to fully evaluate the CO2 emissions reductions achieved in ERCOT as a result of increased wind generation. The study is ongoing as we wait for emissions statistics from the final quarter of 2011 to be released by the EPA in early 2012.Copyright

The Role of Small Distributed Natural Gas Fuel Cell Technologies in the Smart Energy Grid

As the utility grid evolves to transmit information along with energy and water to the end-user, the traditional grid model is changing. The Pecan Street Smart Grid Demonstration Project in Austin, TX is at the leading edge of the evolution of the smart grid. Currently, over 100 homes, soon to be 1,000, have electricity demand information being measured on a 15 second interval. Using the highly granular energy use and solar generation data from Pecan Street, we attempt to estimate the potential for small natural gas fuel cells as distributed firming power for intermittent renewables in the built environment. Micro-grids have traditionally relied on the macro-grid for stabilization in the event of local interruptions in generation. In this paper we analyze the utility, economic, and system efficiency impacts of small distributed natural gas fuel cells as an alternative to the macro-grid for stabilization. Using our unique dataset, we have determined that the average home could utilize a 5.5 kW fuel cell either for total generation or backup, and the average home could operate as its own micro-grid while not sacrificing core functionality. We also explore the utility of matching the thermal output of a possibly smaller fuel cell, used in combined heat and power mode (CHP), to an absorption refrigeration system in place of traditional space cooling. With these types of energy assets, homes could possibly participate with local electricity markets, or the grid at large, in a highly dynamic way. A home energy network could, given homeowner set-points, adjust home uses of energy and sell high priced electricity back to the grid, possibly from both solar PV and fuel cell production, possibly eliminating energy bills. Lastly, we estimate that the system efficiency could possibly double by transporting natural gas to the end user to be converted into electricity and hot water as compared with traditional methods of using natural gas for power generation followed by electricity delivery.Copyright

Development of a Sustainable System Emulator for Sustainable Environment Design

Several interdisciplinary research projects of renewable energy-driven residential environment have been actively conducted at College of Engineering, Nihon University. However, most of renewable energy such as solar energy is strongly affected by atmospheric conditions so that predicting its generated power is relatively difficult in practical. This means that renewable energy should be used under adequate energy management especially to realize sustainable systems.

Development of a Sustainable System Emulator for Living Environments Powered by Renewable Energy

In the present paper, a sustainable system emulator (SSE) for living environments powered by renewable energy sources is addressed. The main purpose of the SSE is to emulate the various factors that influence sustainability using a simple engineering approach. The main goal is to realize a useful mixed-reality platform for designing living environments with overall energy self-sufficiency as well as adequate habitability. The SSE design concept is based on the combination of an outer-system emulator (OSE) and an inner-system emulator (ISE). The OSE uses artificial lights and air blowers to emulate the sunshine and wind conditions in the Fukushima area of Japan. The ISE emulates the interior of a residential environment, based on renewable energy sources and power storage facilities, and consists of reduced-scale models powered by solar cells and a wind turbine. The ISE also includes DC appliances, which emulate domestic power usage, and electrochemical batteries for power storage. Control algorithms for energy management can also be implemented in the SSE. An experimental study was carried out using the SSE to emulate both the natural environment and living environments, and the relationship among the different emulation parameters was investigated. Furthermore, the experimental results indicated that accelerated testing using SSE may be effective for improving the design efficiency of renewable-energy powered systems.Copyright