Weather Forecast

Home>Topics>Weather Forecast
Refine Results
  1. All
  2. Articles
  3. Online Articles
  4. Magazine Articles
  5. Videos
  1. Q&A with Steve Nguyen, senior director of marketing at BuildingIQ

    At the end of July, a report from the Association for the Conservation of Energy (ACE) found that over a third of non-domestic buildings in London have the worst energy ratings under Energy Performance Certificate (EPC) standards. London is not alone and is in good company with other global cities in its failure to address chronically bad efficiency standards in buildings. Building IQ is well-established in assisting urban planners in this area and it released its new cloud-based platform, Predictive Energy Optimization (PEO), also in July. Decentralized Energy spoke to Steve Nguyen, senior director of marketing at BuildingIQ about how his firm’s technology is incrementally improving energy efficiency in the cities in which it operates. Decentralized Energy (DE) : Does the platform benefit buildings through the use of combined heat and power , onsite power, onsite solar , or district energy? Steve Nguyen (SN): BuildingIQ is all about using data to optimize energy usage. Therefore, from the perspective of our newly launched 5i platform , it’s somewhat irrelevant as to where the energy comes from – grid, local generation (solar, community solar, on-site generation) or storage. To us, clean energy sources such as solar and cogeneration are simply more data streams to be incorporated into our optimization algorithms. While we are in the early stages of working with customers to incorporate local power sources, our platform and optimization engine is capable of providing signals that could help sophisticated buildings determine when, and from which source, they should get power. A key element that’s already incorporated into our platform is utility tariff structures and demand ceilings. The hourly cost of electricity is a huge factor in determining the appropriate energy source at the appropriate time. At this point, we greatly anticipate continuing our work with customers to hone this particular part of the technology as those sources increase in popularity and their data streams become more accurate and consistent in the near future. DE: Are there any particular projects ongoing or completed that make use of BuildingIQ and the above systems? SN: BuildingIQ’s Predictive Energy Advisory Services are being utilized at the Women’s and Children’s Hospital Precinct in Adelaide , South Australia. This is an approximately 1.1 million sq. ft. precinct with a complex central plant. The plant encompasses a combination of a CHP-driven trigeneration plant and the electric chiller based plant. The trigeneration plant is used to generate electricity, chilled water and hot water, 80 percent of which gets used for heating, ventilating and air conditioning (HVAC) purposes followed by domestic purposes. The electric Chillers are utilized for the HVAC purposes only. The plant is powered by gas and is utilized for providing the base HVAC Systems with necessary chilled and hot water. The electric chillers come on top to work in accordance with the capacity. BuildingIQ’s Predictive Advisor uses a mathematical model, generated through the analysis of internal data (occupancy comfort, building characteristics and meter data) and external data (demand response signals, energy tariffs and weather forecasts), to understand the relevance of the trigen generated electric power along with the utility generated grid power. The platform then provides a power prediction forecast for the next 24 hours from 4pm onwards every day. This Power Prediction gets utilized by the building team to see what aspects of the grid-utilized HVAC Plant can be tweaked to manage power use and demand. This strategy is mainly used to observe the potential KWH draw that can be used, based on the weather forecast, followed by the ability to see what was predicted over the last 3 days vs. the actual KWH used by the building, with the goal of dropping the peak demand for the facility on hotter days. DE: What sort of obstacles have been overcome to achieve energy efficiency in cities as a result of this platform and what obstacles remain? SN: There are many city-wide efforts around the world designed to achieve carbon or energy reductions. For instance, we have an ongoing project with the Washington D.C. Department of General Services that is designed to limit resource consumption, reduce environmental impacts, lower costs, extend the life of capital assets, optimize operations, and increase occupant engagement and education. A lot of the obstacles come down to the actual state of the Building Management System (BMS) itself. While predictive control is absolutely beneficial in terms of energy savings, operational efficiency, and tenant comfort, getting the BMS to the point where it can respond to the intelligent system is an entirely different breed of animal. We’ve had many instances where our team arrives on site only to find out that the BMS that the owner thought they had performs NOTHING like the BMS that’s actually in place. For instance, it’s common to have systems with inoperable thermostats, defective heating coils, stuck paddles in the VAVs, and so on. What this means is that the first step is often a retro-commissioning project that is not only unexpected, but could take months. While necessary, such projects slow the overall roll-out and impact actual expenditures. At the actual building level, this is perhaps the biggest obstacle.   DE: Do you think the technology can be rolled out globally? I’m thinking of Europe which is identifying serious inefficiencies in how it heats and powers its buildings and cities generally. SN: Yes. Our technology is BMS agnostic and open ended in terms of the data streams that it can ingest. Often solutions from BMS vendors will only solve/impact their own systems, but the reality is that cities and portfolio holders have to deal with massive complexity in their holdings due to the individual nature of buildings. Solutions like those provided by BuildingIQ sit atop any BMS – from rudimentary to state-of-the-art – to deliver on the goals that are typically set forth by regulatory agencies.

    Online Articles

    Online Articles

    Thu, 25 Aug 2016

  2. NGSA forecasts record winter gas demand, matched by adequate supplies

    Colder weather forecasts and greater demand for natural gas than last winter are expected to place upward pressure on gas prices this winter compared with last winter’s unusually low prices, the Natural Gas Supply Association said in its 2016-17 Winter Outlook assessment of the wholesale gas ...

    Online Articles

    Online Articles

    Wed, 5 Oct 2016

  3. Liberty Utilities picks Schneider Electric for weather forecasting

    Ninety percent of load forecasting errors in the industry are attributed to inaccurate weather predictions

    Online Articles

    Online Articles

    Tue, 7 May 2013

  4. Oil Pirces: US consumers should feel muted impact from rising oil price

    OPEC's decision to cut production gave an immediate boost to oil prices, but the impact on consumers and the U.S. economy is likely to be more modest and gradual.

    Online Articles

    Online Articles

    Fri, 2 Dec 2016

  1. MARKET WATCH: Cold weather forecasts lift oil, gas prices

    Online Articles

    Online Articles

    Tue, 15 Jan 2013

  2. Expert: National transmission network could slash CO2 at modest costs

    The plan has been described as 'The Energy Interstate'

    Online Articles

    Online Articles

    Mon, 21 Nov 2016

  3. EIA: US natural gas storage builds

    The Energy Information Administration estimated US natural gas in underground storage across the Lower 48 at 3.836 tcf as of Oct. 14, marking a net increase of 77 bcf from the previous week.

    Online Articles

    Online Articles

    Thu, 20 Oct 2016

  4. Safety products: Weather forecasting services keep communities safe

    Utility safety: Schneider Electric and PlanetRisk recently joined forces to better protect communities from the effects of unpredictable and severe weather by now offering improved weather forecasting services through collaboration and shared resources.

    Online Articles

    Online Articles

    Thu, 13 Oct 2016

  5. IBM unveils advanced renewable energy forecasting system

    IBM solution combines big data analytics and weather modeling technology to predict output of renewable energy resources.

    Online Articles

    Online Articles

    Mon, 12 Aug 2013

  6. Neural Networks: A better forecast for renewable energy

    Siemens has created a neural network-based forecasting software that predicts fluctuations, thus helping to increase the efficiency of electricity markets.

    Online Articles

    Online Articles

    Tue, 30 Sep 2014

  7. More than $5MM granted in support of wind energy developments from DOE

    The Department of Energy has announced it is awarding more than $5 million in funds toward short-term wind forecasting and to accelerate midsize wind turbine development in the U.S.

    Online Articles

    Online Articles

    Mon, 13 Sep 2010

  8. MARKET WATCH: Cold weather predictions push up gas price

    Crude oil futures prices continued to make modest gains while the front-month natural gas contract maintained a five-session rally, escalating 5% Oct. 1 in the New York market on forecasts for cold weather in the central US in coming weeks.

    Online Articles

    Online Articles

    Tue, 2 Oct 2012

Get More Results