AI Powered Forecast
Advanced resource analytics and continuous machine learning based statistical models and Artificial Intelligence to deliver consistent forecast accuracy for Wind and Solar for day ahead and intra-day schedules.
Wind Forecasting
and Scheduling
Wind power as a renewable resource is particularly difficult to predict. This complicates the work of grid operators, power traders and forecasters. An incorrectly forecasted schedule of renewable power can have economic repercussions for all stakeholders. Manikaran offers a complete solution in wind power forecasting and scheduling on intra-day, day ahead and week ahead basis depending on the requirement of DSM regulation of CERC for ISTS-connected projects and SERC’s for respective state grid-connected projects..
MAL produces wind power forecasts, for wind farms across the country, of various portfolio sizes on which we schedule the forecasts for each 15 minutes Time block on concerned RLDC / SLDC portals. With our industry-leading range weather models from top global meteorological agencies, combined with our cutting-edge statistical, physical and machine learning models trained for various terrains, we are able to offer consistent and reliable forecasts..
Solar Forecasting
and Scheduling
Solar power forecasting is simpler compared to Wind as the maximum output feasible over a day is known due to the sun’s set path but it becomes very challenging during incoming and receding monsoon, when the moving clouds lead to drastic generation fluctuations; and also in winters when foggy conditions may cause a variable impact on generation curve depending on its intensity. To add to the challenge is a higher DC (MWp) to AC (MW) ratio prevalent in newer installations to ensure higher CUF to mimic a pattern similar to mechanical tracker-based plants but leading to high fluctuation of generation pattern.
MAL understands the unique conditions prevailing in each region and applies its advanced statistical models accordingly, taking into multiple weather sources and real-time data to reduce the deviation of actual generation from submitted forecasts (schedules) to the extent possible to minimize the DSM (deviation penalties) of the Solar generators.
Hybrid Forecasting
and Scheduling
Studies show, in terms of power generation, solar and wind resources are complementary to each other. Hence if operated in Hybrid, these two technologies would help in minimizing the variability besides optimally utilizing the infrastructure. Adding battery storage to the mix can provide close to round-the-clock (RTC) uninterrupted power.
Going forward, hybridization of these technologies is inevitable, at MAL we are already performing F&S for India’s 1st large-scale Hybrid project and we are ready to accept new technology like Battery Energy Storage System (BESS) in the mix to make the system viable by applying multiple use cases such as energy arbitrage, reduction in deviation of actual generation over scheduled one by not only exchanging the state of charge status but also send signals to the EMS of BESS to operate the charging or discharging based on expected generation, given schedule and dispatch commitments.
Qualified Coordinating Agency
A typical pooling substation will have multiple wind and solar generators connected to it. These renewable generators have different owners with varied off-take arrangements. Hence, an institutional structure in the form of ‘QCA’ requires positioning to coordinate F&S and commercial settlement of deviations with renewable (Wind/Solar) generators and the State Load Dispatch Centres (SLDCs).
Qualified Coordinating Agency or commonly known as QCA is a designated state entity that coordinates on behalf of all the wind/solar generators connected to the pooling station in a State with relevant entities such as SLDC as per State Regulations and is responsible for forecast, submission of schedules, coordination, undertake the commercial settlement with SLDC and de-pooling of the applicable charges with all the relevant wind/solar generators.