Unrivalled Electricity Trading & Bidding Optimization Solution Boasting Staggering Profit Increases

  • Real-time intraday and day-ahead trading and bidding optimization
  • Maximize profit from trading, bidding, generation and selling to ISOs & RTOs
  • Trade automation, scheduling, and intraday and post-trade performance analysis
  • Seamless integration of QR AI Forecaster for load and price forecasts

Bidding Optimizer overcomes complex challenges by computing optimal bids that maximize the plants’ gross margin or P&L across all forward (5-60 minutes) trading periods of the day. This 24/7 automated trading bot runs at each trading period with a runtime of just a few minutes each round

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Challenges

Clients’ profile. Merchant and load serving generators operating in real-time intraday and day-ahead (5 - 60 mins interval) ISO and RTO markets.

Target. Maximize trading profit by dynamically adjusting bidding every trading period to extract the maximum value from instantaneous changes (price and offer stack) in the market.

Implement real-time 24/7 trading in a web-platform allowing multiple traders and plants’ operators to login and manage & monitor, in specialized web-dashboards, the plants’ generation, scheduling, RTD, fuel, the bids to the ISO and their electronic submission, and send and receive data via APIs.

A full-feature, ready-for-use, standalone cloud solution that can be easily integrated with in-house ETRMs and ISOs via flexible APIs.

Extract maximum value from the spot market. Static bids solely driven by generation cost miss out on market opportunities:
a) Bids, priced unnecessarily higher than the marginal price, won’t be cleared for dispatch.
b) Bidding is a nonlinear path-dependent decision-making process. Bids of previous periods must be priced properly to allow ramping up or down to achieve optimal (max or min) dispatch at some later periods to fully capture any opportunity offered by price movements.
c) Modifying a plant’s bids in price or quantity can move the intersection of the system demand with the offer stack, and change the spot price and the plant’s dispatch. Sometimes the offer stack allows sizable jump opportunities near the intersection, and adjusting the bids judiciously can increase the spot price, while maintaining sufficient dispatch to increase profit.

Why QR Bidding Optimizer Solution

The outputs are computed at the resolution of the market, 5, 15, 30 or 60 mins.

Execution frequency of this automated trading bot can be every 15 to 60 mins, 24/7, with a runtime of just a few minutes each round.

The solution computes, for a portfolio of power plants, optimal bids that maximize their collective gross margin or P&L, across every forward (5-60 minutes) trading period, in intraday and day-ahead energy and reserve markets. The solution also computes the expected RTD and MQ for each plant and the spot market price resulting from the optimizer.

How it works. The system automatically fetches all necessary data. Then QR AI Forecaster computes accurate AI forecasts of system price, demand and the stack of bids & offers. Next, QR Optimizer uses these forecasts as input, along with generation costs, constraints, and outages to compute the optimal bids for each trading period whose expected cleared RTD maximize the P&L. The cycle is automated and runs every 15 to 30 mins, 24/7.

Trading Optimization Case Studies & Video Demos

QR Bidding Optimizer Benefits & Features

We offer flexible delivery options:
Optimization Service where our expert team and platform do everything and you receive, via API and electronic means, intraday and DA bidding signals every 10 minutes, 24/7.
Software as a Service (SaaS) where we implement QR Bidding Optimizer on a private cloud of your choosing, or on-site, and you control the data and the optimization models.

You pay one single annual subscription fee comprising license, maintenance and upgrade releases.

QR Bidding Optimizer increases trading P&L, or asset valuation by 20 to 30%. In no case it will cost you anything. It is a source of revenue and can make 10x its cost, as extra profit it generates.

Advanced bidding optimization platform with 2 algorithms (genetic computing and pattern search), linear and nonlinear constraint modeling, 30+ parameters and extensive data preprocessing routines.

A user-friendly web dashboard allows the configuration of a custom bidding/trading optimization model by its technical parameters, input data, each plant’s fuel, OPX costs, physical characteristics, and trading constraints.

QR Power Plant Manager allows the modeling of different asset types, data (capacity, RTD, meter, contracted capacity), physical characteristics and operational constraints, ramp, outages, heat-rate and power conversion. Detailed cash flow modeling capability for the cost, revenue, and gross margin of each asset, which is the optimization objective function. These also include multiple currencies, miscellaneous charges, and the plant’s commitments in terms of bilateral contracted capacity, reserves, and joint bidding provisions with a partner owner. The cash flow modeling is configurable to handle thermal, renewable, storage, and hydropower plants.

All output data of bidding optimization, e.g., optimal bids, expected clearance dispatch, detailed P&L, simulations and forecasts of prices, and offer stack are available via API for real-time integration with your internal systems.

Risk management can be applied by controlling bid pricing strategies from conservative (taking less risk and acting as price-taker) to aggressive (taking more risk and attempting to set prices), or dynamically switching strategy depending on the spot price level through peak and off-peak periods.

Nonlinear constraints such as generation level-dependent ramp rates, heat rate, and spot price are inherent to bidding optimization. These are part of the core architecture of the optimizer.

The model incorporates outages, the bids of multiple partners jointly owning a plant, know-bids of other plants in the offer stack, and quantities sold in ancillary or day-ahead markets.

Our expert (MSc and PhD) optimization team configures, fine-tunes and deploys your bidding optimization models in record time and helps you maintain and calibrate them in time.

QR Trading Performance Analysis. Detailed real-time and post-trade trading analysis dashboard compares the gross margin or P&L of the actual versus optimal scenarios: expected clearing dispatch and meter quantity resulting from the bids, and the corresponding generation cost and revenue from sale in the spot market.

QR Bidding & Scheduler is seamlessly integrated with the optimizer to allow traders to load optimal bids, modify, validate and submit them electronically with a few mouse clicks to the ISO, in intraday and day-ahead trading of energy and reserves.

QR AI Forecaster is seamlessly integrated to provide forecasts of system demand, spot price and the offer stack for each forward trading period, while applying adjustments for outages, available capacity, holidays, quantities sold in the ancillary and DA market. narios: expected clearing dispatch and meter quantity resulting from the bids, and the corresponding generation cost and revenue from sale in the spot market.

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Our Clients Say

QuantRisk’s single platform provides our utility distribution companies with a highly adaptable enterprise web-system, excellent business modeling capability, internal controls and audit, advanced analytics tools, all of which will enhance the overall performance of our daily operations, as well as long term strategic decision making.
System Solutions VP Utility Group