Category Archives: energy

Thoughts on ENERGY 2013 conference

rbrewer-ENERGY-2013

I just finished attending the ENERGY 2013 conference in Lisbon. The conference was a part of InfoSys 2013, which consists of several smaller conference all bundled together. Each day had one keynote and on panel discussion drawn from all the different conferences/tracks,  making for an interesting, and eclectic experience. There were perhaps 30 attendees for the ENERGY subconference, so I got to know several of the presenters.

I was presenting our paper on lessons learned from designing energy feedback visualizations for the Kukui Cup. Our three lessons about feedback visualizations is that they should be actionable, that domain knowledge must go hand in hand with energy feedback systems, and that this feedback must be “sticky” to lead to changes in behaviors and attitudes. While I was probably the only attendee focused on feedback visualizations and behavior, I got some interesting feedback from other energy attendees, such as finding additional ways to connect to undergraduates (e.g., beer :))

Below are my notes on some of the presentations I found noteworthy. So nice to be at a conference with open access to the proceedings so I can link to them directly!

Energy Aware Scheduling

Kanad Ghose presented on Dynamic Classification of Repetitive Jobs In Linux For Energy-Aware Scheduling: A Feasibility Study. 2.8% of electricity in the US is used by datacenters, and their research is on trying to find ways to reduce energy use in the datacenter environment. The basic idea is that some jobs are CPU-bound and others are I/O bound, so on a server with multiple CPUs, some CPUs can downshifted in voltage and frequency for I/O bound tasks (which spend most of their time waiting for I/O requests) with a consequent savings in energy. The other CPUs are kept at the highest performance level for the CPU-bound jobs. Each type of job (identified by the executable image) is classified, and jobs are scheduled by the kernel on the properly tuned CPU. Interesting work, and they are seeing about 5-10% reductions in energy use with small increases in latency. In the future they foresee servers in the data center communicating data about their loads (and predicted loads) to the HVAC system to further reduce energy use by preventing overcooling.

Voltage Sensors for Smart Grids

Chris Yakymyshyn from FieldMetrics presented on his work on Sensors for Smart Grids, which focused on the complexities of designing voltage and current sensors for the medium-voltage environment that are highly accurate. Utilities are typically required to provide electrical power within certain bounds of voltage and frequency. In the past, utilities had usually just targeted the center of the range for safety, but they have now realized that by reducing the provided voltage to the bottom of the regulated range they can save huge amounts of energy, avoiding the need to construct additional power plants! However, to skirt the edge of the regulated range, utilities need to actually measure the voltage they are providing so they can avoid fines for being outside the range.

One neat thing is that the sensors they have designed work optically,  taking advantage of the Pockels effect whereby an electric field changes the index of refraction of certain crystals. Their sensor produces polarized light, which is guided through multiple crystals, and a sensor at the other end measures the angle by which the polarization light has been rotated.

The results from their field trials with BC Hydro are equally interesting. One major application by BC Hydro is detecting energy theft. To detect theft, a power sensor is installed on the medium-voltage transmission line before a group of customers, and then after the group. Combined with smart meter data from the customers, the utility can determine how much power should have been drawn off the medium-voltage line compared to what the smart meters reported. In one neighborhood, approximately 27% of the delivered electricity was being stolen, and the majority of that was coming from (illegal) marijuana grow operations! This leads me to ponder how much energy we could save if growing marijuana was legal, which would allow for more outdoor growing, or at least energy audits of facilities. 🙂

Energy Storage & Vehicle-to-Grid (V2G)

Mark Apperley from the University of Waikato, New Zealand brought a wonderful discussion on energy storage and specifically vehicle-to-grid (V2G) storage. One of the conference panel discussions focused on energy storage. The discussion was quite wide-ranging, and I found the following points interesting

  • Mark pointed out that we all have a storage system in our homes for a different resource: toilets. Toilets store water, dispensing it at 140 l/m, but refill at 30 l/m. The water storage provides two benefits to water-providing utility: it smooths out the load generated when people flush, and it also provides an “infrastructure improvement” since the water pipe coming to homes is not sized to provide water at the rate needed to flush. Electricity storage would also provide these same two qualities. For example, as electric vehicles become more widely used, the distribution lines to neighborhoods may become overburdened as adding an electric vehicle roughly doubles the electricity use of a home. In a neighborhood with many EVs, some vehicles may discharge to provide their neighbors with power which the utility is not able to provide with the existing distribution lines.
  • In talking about the growth of renewable energy, Chris Yakymyshyn pointed out that fossil fuel power plants need to run a certain percentage of the time in order to make a profit. If they are only being used a small percentage of the time to support intermittent renewable energy sources, they will shut down and go bankrupt.
  • I shared point made by Mark Duda, a founder of residential-solar installing company RevoluSun in Hawaii. He pointed out that since electricity prices are very high in Hawaii, PV is quite cost-effective for many homeowners, some of whom also install a battery storage system so they can go completely off the grid. Hawaiian Electric (like all utilities) has large fixed costs (power plants are expensive!) that it has to pay regardless of how much electricity they actually generate. Thus as more people are able to switch to solar, Hawaiian Electric will have to spread the fixed costs over fewer customers, leading to higher rates. This makes solar cost effective for even more homeowners, who then disconnect from the grid, which could lead to a spiral when the utility can no longer afford to pay its fixed costs.

Mark also gave a keynote talk on his research into V2G in New Zealand. The concept of using electric vehicles as a storage system for the grid is not new, as it was first suggested by Kempton and Letendre in 1997. Two important issues for V2G are that the electric vehicles need to be plugged in to be a resource for the grid, and that the decision on whether to charge from the grid or discharge to the grid requires knowledge of the planned usage of the vehicle (e.g., when will the owner be driving home?).

The promise of V2G is that vehicles are only used a small portion of the time. In NZ, vehicles are estimated to be used only 4% of the time, providing a lot of potential time for grid backup. Mark has created a fine-grained simulation of electric vehicle use for grid storage in NZ, with a 1 minute time scale, individual vehicle simulation, and real utility load data (we can only dream of this level of data in Hawaii!). The simulation also takes into account the gradual adoption of electric vehicles.

Based on the simulation results, with 400,000 EVs, V2G reduced peak energy generation requirements, and flattens out the demand curve. Unfortunately, it did not actually reduce the height of the peak load: while EVs can be helpful for storage, they also increase demand for electricity for their use as transportation. As an amusing aside, Mark said that one of his student’s had computed that if all the laptops in NZ could be linked to the grid, they would be able to handle the national load for a few minutes 🙂

It would be great to see a simulation of how V2G would work (or not) for Hawaii, but it would require a lot of data that is not available outside of Hawaiian Electric.

Mahalo to all the participants and organizers of ENERGY 2013!

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Thoughts on HICSS 44 (2011)

I just got back from the Hawaii International Conference on System Sciences, aka HICSS. This conference has been running for 44 years. General information about this year’s HICSS can be found here, and the proceedings will eventually be here.

This was my first HICSS, which is kinda strange seeing how long I have been in Hawai`i. It was held this year at the Grand Hyatt Kauai, which is pretty luxurious. I guess the idea is to hold it at resort that will be a draw for participants, and provide enough amenities that attendees don’t feel the need to wander off.

The first thing that struck me about HICSS is the incredible diversity of sessions going on. The conference is organized in as a bunch of tracks (high-level topics), which are then broken into about 60 minitracks. The minitracks can last a whole day (4 sessions) or be as short as a single session.

The result is a huge smorgasbord of papers. Each day, there are 15 parallel tracks, ranging all over the place: education, social networks, cyber security, location-based marketing, power systems, and many more. This can be good if you want to check out a diverse set of presentations, but to me it makes HICSS feel more like a conference of mini-conferences than a unified whole. This is quite different from a conference like Ubicomp, which is vociferously single-track so that every attendee can attend every session if they want to. Naturally, Ubicomp accepts far fewer papers than HICSS.

The minitrack I was attending (Information Systems and Decision Technologies for Sustainable Development) didn’t start until the second day, so on the first day I just went to sessions that looked interesting. Just deciding which sessions to attend is quite a task: 15 rooms * 4 sessions a day = 60 paper titles to look at!

I started with the Future Electric Power Systems (smart grid, more or less) minitrack. This minitrack was located in a standalone building at the Hyatt that is used as a nightclub. So the attendee chairs were set up in a sunken dance floor, and the presentation slides were shown on one large TV embedded in the wall, as well as 16 smaller TVs distributed around the ceiling (like one might find in a sports bar). This was kinda bizarre, but amusing.

The power systems minitrack has been running for 15 years, so the attendees seemed quite familiar with each other, and had their conference process down pat. The papers I saw were interesting, though more traditionally smart-grid-oriented compared to our Kukui Cup work. Unfortunately, the proceedings (which will be freely available) are not yet online, so I cannot link directly to papers.

  • A case study on the expected impact of PHEV vehicles on electricity consumption, using a new community in South Korea (A Case Study on the Grid Impact of PHEVs to Sample Distribution Power System by Dong Joo Kang and Sunju Park)
  • An algorithm for detecting “load pockets”, which are areas on the grid that are constrained by transmission such that generation facilities could raise their prices and electricity users would have no option but to pay the higher prices (Clustering of Power System Data and its use in Load Pocket Identification by Katherine Rogers and Thomas Overbye).
  • An analysis of locational marginal carbon intensity of generation (how much additional carbon will be emitted by increasing demand by 1 kWh in a particular location at a particular time) on the eastern part of the US. The results are somewhat surprising, in that areas that are heavy coal users might actually have lower marginal carbon intensity because if they had additional demand they would import power from generation facilities with lower carbon intensity. The presenter related the marginal intensity to Renewable Portfolio Standards, which provide subsidies for production of renewable energy. Currently subsidies are independent of carbon intensity, but the authors argue that they should be higher (pay more for renewable energy) in places where the marginal carbon intensity is high, and lower where marginal intensity is low. This would encourage the buildout of renewable generation in places where it would reduce carbon emissions the most (Locational Carbon Footprint and Renewable Portfolio Policies: A Theory and its Implications for the Eastern Interconnection of the US by Aleksandr Rudkevich, Pablo A. Ruiz and Rebecca C. Carroll).
  • An investigation into what is really happening in loads, starting with hot water heaters. The presenter argued that there has been a lot of research into the dynamics of generation, but very little in the dynamics of loads, which will be critical for any type of demand response program. In the ensuing discussion, I learned a new term: demand subscription. This is the idea that rather than being metered for use, customers subscribe to a certain amount of electricity (not sure if it is measured as power, energy, or both) and then it is up to the customer to figure out how to live within that subscription. So the utility would only communicate with a smart meter, not reaching beyond the meter to smart appliances.

I also had time to attend some talks in the social networking track by members of LILT (my former research group): Dan Suthers, Kar-Hai Chu, and Devan Rosen. I was familiar with some of the outlines of the Traces work, but it was good to see it discussed in a public forum.

The minitrack I presented in was called Information Systems for Sustainable Development. I presented our paper describing the design of the Kukui Cup. It seemed well received, with most of the questions revolving around how to get students involved and how to keep them aware after the competition in order to sustain behavior changes. Eric Paulos suggested we should provide Kill-A-Watt meters to some residents in May 2012 before they move out of the first-year dorms, and then follow up with them on whether and how they used them in their next living situation.

Two other presentations in our track that I found interesting:

  • Hendrik Hilpert, a PhD student from Göttingen University presented work on computing products’ carbon footprints automatically using vehicle mass airflow data (obtained via OBD2) fused with GPS data. This combination allows one to compute how much carbon is being emitted, while the GPS data allows the carbon to be allocated to different products that might be on the same delivery vehicle as it makes a series of stops. They even cited my older literature review in their paper, würd! (Real-Time Data Collection for Product Carbon Footprints in Transportation Processes Based on OBD2 and Smartphones, by Hendrik Hilpert, Lars Thoroe and Matthias Schumann).
  • Eric Paulos, assistant professor at CMU presented work on Citizen Energy. Citizen Energy is the idea of changing people from just being energy consumers into more active participants in the generation and use of energy. They have made a bunch of cool devices, like a Seasonal Energy Lamp. The lamp is connected both to grid power and to solar and wind turbines, and it changes the color of the emitted light depending on the source (orange for solar, blue for wind, etc), making people more aware of where their energy is coming from. These design experiments seem really complementary to the Kukui Cup, possibly providing additional ways for participants to become more energy literate. (Citizen Energy: Towards Populist Interactive Micro-Energy Production by Eric Paulos and James Pierce).

Unfortunately, our minitrack had fairly low attendance (perhaps 8 attendees at peak, of whom half were presenting in the minitrack), so I don’t know how it will fare next year. All in all, it was a worthwhile experience, but was a bit of a comedown after BECC 2010.

Notes from SmartGridComm 2010

Last week I attended the first Smart Grid Communications conference. I was presenting our paper on WattDepot. The presentation went well and there were several questions afterward. One point that I got several questions about was our requirement to support rapid data collection (sub-minute), since that is much faster than most commercial meters support. In retrospect, I should have emphasized our application domain (the Kukui Cup) more in the presentation, which might have helped to explain that requirement.

The following are some of my notes from the conference:

  • There were 102 papers accepted at the conference (40% acceptance rate), and 441 registrations. The mix was roughly 44% academic, 31% industry, 20% R&D, and 5% government.
  • The conference was held at NIST, and throughout the building were NIST clocks that presumably were very accurate. 🙂
  • There is a Smart Grid Consumer Collective, which sounds like an organization we should keep an eye on.
  • There are apparently standard power network topologies that can be used for analysis and research, such as the IEEE 300 bus power flow test case.
  • Some power industry slang I was not aware of: “big wire” relating to electricity distribution, “little wire” relating to communication networks. As in “the Smart Grid is all about the little wire people working with the big wire people.”
  • Georgios Kalogridis presented work on “Privacy for Smart Meters: Towards Undetectable Appliance Load Signatures”. The basic idea being that if the utility has fine-grained data about energy usage, they can determine a lot about what the consumers are doing. Kalogridis et. al. propose a system where a rechargeable battery is located in the home, and can be used to mask the signatures of energy use by charging and discharging at appropriate times. They cite this interesting paper by Elias Quinn that lays out all the potential privacy issues related to fine-grained energy usage data.
  • Came across a reference to Stanford’s PowerNet project, which aims to measure the “energy consumption of enterprise-style computing infrastructures”. Looks cool, paper here.
  • Hironori Nakanishi from the Japanese government reported on the Japanese perspective on the smart grid. Apparently Japanese utilities were not that eager to pursue smart grid upgrades because on average a Japanese consumer has 16 min/year of power outage, compared to the US average of 162 min/year. However, the Japanese government set the target of 25% CO2 reduction by 2020, which will require 28 GW of new solar power.
  • I also had not heard about the Hawaii-Okinawa partnership on clean energy.
  • One of the reasons that demand-side management is being pursued is for “peak shaving” by shifting some appliance loads to off-peak periods. Unfortunately, if all the smart appliances decide to shift their loads to the start of the off-peak pricing period, then you get a rebound peak. This seems like a challenging problem, barring real-time pricing that takes the rebound peak into account.
  • Jay Taneja presented work from UCB on shifting appliance loads to make maximal use of fluctuating renewable energy.The idea is that certain thermostatically-controlled loads like a refrigerator store electrical energy as thermal energy, so they can be scheduled based on the availability of renewable energy (in their study, wind energy). So if there is excess wind energy available, the fridge compressor could run more frequently, and vice versa. Bringing data about grid renewable energy production is something we have been thinking about from the consumer human interface perspective (the carbon “traffic light” concept), but they are working on making actual appliances sensitive to renewable production. Very cool.
  • In total, I gave out 11 business cards, and 2 REIS brochures.

Next year the conference is in Brussels. Paper deadline is April 4, 2011.

Rebuild Hawaii Consortium March 2010 meeting

I attended the Rebuild Hawaii Consortium quarterly meeting last week. I had never attended any of their meetings before, and I was somewhat surprised at the sizable number of people in attendance (40? 50?). It was held in a large stadium-style conference room at the Hawaii Convention Center. I had checked the agenda in advance, and thought I could arrive at 10 AM and still see everything I wanted to, but apparently the agenda changed since it was posted on the website.

The talk I missed that I wish I had seen was by Luis Vega on the Hawaii National Marine Renewable Energy Center. His slides look very interesting, lots of hard-nosed cost comparisons of wave and OTEC electricity generation.

Paul Norton have a talk on Zero Energy Buildings, which was interesting. I attended his REIS seminar where he covered some of the same things, but this was focused on ZEB. Some points I found particularly interesting:

  • The introduction of air conditioning leads to a 70% increase in electricity use
  • The key conceptual shift is thinking about the monthly cost of a home being the mortgage + utility bill.
  • The efficiency / photovoltaic balance point is the point at which adding generation via PV is the same cost as additional efficiency measures
  • A cost neutral design (monthly cost is same as a home built to code) that uses efficiency and PV results in an 85% reduction in home electricity usage
  • Once major efficiency measures are in place (solar water heating, efficient lighting & air conditioning, insulation), the major remaining load is appliance plug loads
  • In one military housing complex on Oahu, there is a 4x difference in electricity usage between houses with identical efficiency measures. Presumably the differences are due to appliance purchases and behavior.
  • In a group of homes in Las Vegas, the difference was 5x
  • Further, the differences were fairly continuous: there is no nice average plateau
  • PV inverters on the neighbor islands have been causing problems because the utility frequency can sag during periods of high usage. By default, the inverters are set to disconnect from the grid when the frequency drops below 59.3 Hz, so inverters all over turn off, which puts additional strain on the utility, exacerbating the problem. Reducing that threshold frequency to 57 Hz can help. Thus there is a lot of research still to be done on renewable integration.

Another presentation was on HCEI and smart grid initiatives at PACOM. They are working on a project called SPIDERS that is trying to address the fact that access to electricity is a critical need for the military. One thing I was stunned to learn was that people living in military housing don’t pay for electricity! Thus they have no financial incentive at all to reduce their energy usage. Slide 8 shows an actual graph of HECO’s demand and generation for one particular day. Our work on OSCAR was all based on vague outlines of what the demand curve looks like, so it was great to see it “in the flesh”.

There was a lot of good information at the meeting, so I’m planning to attend in the future. Next meeting is June 2.

Using XPath to pick data out of XML

This week I wrote a WattDepot sensor for the TED 5000 home energy meter. The TED 5000 gateway (a small Internet-connected embedded computer) provides a URI that generates XML showing the current power data. First, I needed to figure out what the XML meant. Once that was done, I wanted a quick and simple way to pick out the 2 pieces of data from the XML that I care about using Java.

WattDepot uses JAXB extensively for XML processing, but that was kinda heavyweight for my needs here. I had heard about XPath, and it sounded like the right type of tool for just grabbing a little data from XML. Turns out that Java 1.5 and later have XPath built-in, so there’s no additional dependencies.

IBM has a good tutorial on using XPath from Java by Elliotte Rusty Harold. Unfortunately, I was confused initially because all the XPath examples in the tutorial are for finding all XML nodes in a document that meet certain criteria, whereas I knew exactly where in the XML tree my data was lurking. Luckily, it turns out that XPath is really a lot like a path in a filesystem (duh), so traversing the tree is easy.

Say you have the following XML from TED (some parts elided):

<LiveData>
  ...
  <Power>
    <Total>
      <PowerNow>2995</PowerNow>
      ...
      <PowerMTD>515227</PowerMTD>
      ...
    </Total>
  ...
  </Power>
</LiveData>

The XPath that would pull out the value from PowerNow is /LiveData/Power/Total/PowerNow/text(), and for PowerMTD it is /LiveData/Power/Total/PowerMTD/text(). Simple!

Here a code fragment that extracts those two values from an XML file (stealing liberally from the XPath tutorial linked above):

public class XPathTest {

  public static void main(String[] args) throws ParserConfigurationException, SAXException,
      IOException, XPathExpressionException {
    if (args.length != 1) {
      System.out.println("Need XML filename arg.");
      return;
    }
    DocumentBuilderFactory domFactory = DocumentBuilderFactory.newInstance();
    domFactory.setNamespaceAware(true);
    DocumentBuilder builder = domFactory.newDocumentBuilder();
    Document doc = builder.parse(args[0]);

    XPathFactory factory = XPathFactory.newInstance();
    XPath powerXpath = factory.newXPath();
    XPath energyXpath = factory.newXPath();
    XPathExpression exprPower = powerXpath.compile("/LiveData/Power/Total/PowerNow/text()");
    XPathExpression exprEnergy = energyXpath.compile("/LiveData/Power/Total/PowerMTD/text()");
    Object powerResult = exprPower.evaluate(doc, XPathConstants.NUMBER);
    Object energyResult = exprEnergy.evaluate(doc, XPathConstants.NUMBER);

    Double power = (Double) powerResult;
    Double energy = (Double) energyResult;
    System.out.println("Power from TED 5K: " + power + "W");
    System.out.println("Energy from TED 5K month to date: " + energy + "Wh");
  }
}

It’s nice to have a quick and easy way to make use of XML from Java in my toolbox.

it’s electric: TED data storage and plotting

I was checking on the website for The Energy Detective the other day looking for API info, and found that their page of 3rd-party applications had been updated, and included an application called it’s electric. it’s electric is a Java web application that queries the TED gateway frequently for the 1 second resolution power data, and stores it in a Berkeley DB. That alone is useful, as the TED has a segmented data storage system, keeping the 1 second resolution data only for an hour (and so on for coarser grained data).

It also provides a graphing system based on Google’s Annotated Timeline visualization, with some enhancements like automatically changing the resolution of the displayed data depending on the time interval displayed. Here’s a screenshot:

Screenshot of graph produced by it's electric

There’s a Google group for support and discussion, and the author Robert Tupelo-Schneck seems quite responsive. A jar file is provided on the group page (which I won’t link to since you should download the latest version), which includes the Java bytecode as well as the source, which is released under the AGPL license. The application is not large, consisting of 5 class files.

Compared to WattDepot, it’s electric seems considerably snappier. Presumably this is due in part to using Berkeley DB for persistence instead of an SQL database. The code also stores data in byte form, rather than higher-level Java objects and XML. Also, it’s electric occupies a clear functionality niche: it provides long-term storage of the finest-grained TED data (which is otherwise lost every hour), and provides graphing of that data from locations outside the home network.

I experienced some problems when scrolling around the data on the live it’s electric website, sometimes the graph would not update, or I was unable to scroll to where I wanted to apparently because new data was being loaded in for the current location.

Overall it’s electric looks like it could be useful for TED owners that want to hold on to that fine grained data, and want more options for displaying that data outside the home.

WattDepot going “real-time”

In the past week I have added a new REST API method to support near-real-time queries in WattDepot. The goal is to support user interface widgets that display the latest sensor data from a source, such as a smart meter in a home or dormitory. I have also written a command line monitoring client that shows how to use the new functionality. Both of these will be released as part of WattDepot 1.2 in the near future, hopefully with the addition of a sensor that collects data from TED 5000 home smart meters.

Speaking of sensors, I created a wiki page that explains how to write a WattDepot sensor. This should be helpful for anyone planning to write a sensor to support a new type of meter.

In other WattDepot news, there are three projects in ICS414 this semester that are related to WattDepot. The WattDepot Apps team are working on demonstration web applications for WattDepot. The first application is a visualizer that makes use of the Google Visualization API to make graphs of WattDepot data. It should be ready for a 1.0 release very soon. Next they will be moving on to create a web application that monitors the latest sensor data from a source using the new API method. In the future, hopefully they will be working on a browsing application that lets users look over the users and sources in a WattDepot repository.

The Stoplight Gadget team is working on a Google Visualization gadget that checks a data source for a value, and based on user-settable thresholds displays a traffic light as either red, yellow, or green. While this is a general-purpose visualization gadget, we expect to use it with WattDepot data as part of the UH dorm energy competition, though precisely how is yet to be determined.

Finally, the Energy Meter team is surveying power meters that can be used for the UH dorm energy competition. While they have been in a data gathering phase so far, they are now switching to implement a Modbus/TCP sensor for WattDepot. This sensor will be used to collect data from the floors of the dorms in the energy competition.