Renewables

As utilities move toward 20 to 30% of their energy coming from renewable sources, the level of uncertainty regarding grid reliability and energy costs increases dramatically. There is no foolproof way to pre-determine and adequately plan for the timing and extent of renewable energy sources’ contribution to the grid. Since wind tends to pick up and generate the most energy at night and since peak energy demands typically occur in daytime hours, energy from wind turbines is usually out of synch with peak energy demand. Similarly, sand and dust blowing at night can cover and dramatically reduce the efficiency of solar panels. A sudden increase in wind can create problematic energy spikes, worsen congestion conditions and create overloads. A sudden drop in generation due to unexpected cloud cover or a lack of wind can play havoc with grid stability and cause overwhelming cost overruns – as more expensive, fast-ramping conventional energy sources, such as peaker plants, must be tapped to meet demand. Perfect, energy storage solutions have not yet been invented or adopted to rectify these problems. In the past, many utilities have managed this unpredictability and reduced their risk by limiting their reliance on renewable energy sources. Government and social pressure to increase renewable energy have eliminated that option.

Features

  • Siting: Geo-Spatial Visualization tools for preliminary screening of renewable sites for wind and solar farms with rich analytics to examine and analyze operability, Costs, emissions, Transmission Constraints, Terrain Feasibility, Forecasting and etc.
  • Renewable Energy Integration: Visualization tools to enable higher levels of renewable generation integration into the grid with monitoring tools to manage intermittency and variability of renewable energy generation. Improved forecasting ability and situational awareness helps in higher levels of renewable energy penetration into the grid. Sophisticated and advance tools for effective management of ramp times, frequency droop, dynamic rating and overload management ensuring grid reliability and stability.
  • Offshore O & M: High-resolution remote monitoring of renewable assets
    • Wind power fluctuations (daily, hourly, minute-by-minute, second-by-second changes) and their corresponding statistical properties (max. and mean values, standard deviations, etc.).
    • Frequency distribution of wind farm output variations.
    • Spatial and Temporal correlation of wind farm output. - Comparing outputs from individual turbines and the entire wind farm to investigate the spatial and temporal diversity.
    • Coincidence with system peak and utility incremental cost.

Benefits:

Intuitive and rich geographical user interface with context sensitive dashboards and geo-links for informed, confident decision making.

  • Make increased use of renewable energy sources a practical and economical reality and
  • Enable electric utilities to meet government mandates to dramatically increase energy from renewable sources.
  • Visualization of forecast confidence metrics along with what-if analysis for variable wind and congestion conditions for analysis
  • A cockpit for operators to align renewable generation with load and the overall generation portfolio
  • Impact assessment for generation intermittency
  • Visual impact analytics for integration of renewable and distributed systems
  • Comparative visualization of alternatives: DERs, storage, & demand response (DR)
  • Visual what-if analysis for DR scenarios
  • Analytics of DR schedule options with many factors like time of use and prepaid

Next Steps

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