Power Generation Portfolio Optimization Software
- Real-time intraday & day-ahead power portfolio generation optimization
- Maximize generation revenue including buy-sell in bilateral spot markets
- Unit commitment portfolio to minimize generation cost
- Trade automation, scheduling, and intraday and post-trade performance analysis
- Seamless integration of QR AI Forecaster for load and price forecasting
Power Generation Portfolio Optimization Software
- Real-time intraday & day-ahead power portfolio generation optimization
- Maximize generation revenue including buy-sell in bilateral spot markets
- Unit commitment portfolio to minimize generation cost
- Trade automation, scheduling, and intraday and post-trade performance analysis
- Seamless integration of QR AI Forecaster for load and price forecasting
Unrivaled real-time Electricity Generation Optimization solution for bilateral power markets boasting staggering profit increases
Challenges
Clients’ profile. Traders, and portfolio and asset managers of generation companies with a diverse fleet of merchant or load-serving assets with increasing numbers of aging and renewables plants, within bilateral spot markets.
Target. Maximize profit by dynamically adjusting for every (5-60 minutes) trading period, generation across a portfolio of generation assets versus buy-sell in bilateral spot market, while taking into account availability, constraints, outages, maintenance, existing ancillary and the bilateral contractual obligations, and external constraints such as grid maintenance, in day-ahead and real-time intraday (5-60 mins) markets as well as long term planning.
A full-feature, ready-for-use, standalone cloud solution that can be easily integrated with in-house ETRMs and ISOs via flexible APIs.
Why QR Generation Optimizer Solution
To overcome the listed challenges, this economic generation optimization model offers 2 perspectives:
a) Bilateral market. This model allows buy-sell opportunities in a given intraday or DA bilateral spot market. In this case, the optimal generation path maximize the net gross margin of the plant while fulfilling all demand contracts by generation or purchase from the spot market, whichever is more economical.
b) Unit commitment. This model does not allow buy-sell in bilateral markets and the optimal generation schedule minimizes total generation cost to fulfill all demand obligations, subject to all constraints.
For a portfolio of power plants, the outputs are optimal 5-60 minutes dispatch levels. In bilateral markets, the corresponding buy-sell schedules in the spot market are also computed. In all cases, detailed P&L data are also computed.
These outputs are computed at the granularity of the market, 5, 15, 30, or 60 mins. Execution can be every 15 to 60 mins, 24/7.
This 24/7 automated trading bot runs at each trading period with a runtime of just a few minutes each round. The execution schedule is automated to immediately follow load and price forecast, as these are required inputs.
QR Generation 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 generation 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.
Flexible and advanced optimization platform which offers 2 optimization algorithms (genetic and pattern search), linear and nonlinear constraint modeling, and many parameters which allow you to configure, in a user-friendly web interface, suitable for each power plant in your portfolio across various trading horizons.
You pay one single annual subscription fee comprising license, maintenance and upgrade releases.
Our expert (MSc and PhD) optimization team configures, fine-tunes and deploys your generation optimization models in record time and helps you maintain and calibrate them in time.
QR Generation 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.
The economic optimization model offers 2 perspectives: a) incorporate buy-sell opportunities in the spot market and maximize the net gross margin of the plant. The contracted load can be generated or purchased from the spot market whichever is more economical. b) Alternatively, the model can be configured as a unit commitment optimization model to minimize generation cost, without buy-sell capabilities in a spot market.
All optimization models take into account all constraints and contracted capacity and reserves.
QR AI Forecaster forecasts contracted demand, and the spot price for short and long term horizons. These are key inputs to the optimizer.
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.
Recommended models for short term horizons are to optimize generation dispatch across real-time intraday, day-ahead and ancillaries markets to maximize net profit. For longer horizons, optimize maintenance and outage planning via unit commitment and minimization of cost.
Nonlinear constraints such as generation level-dependent ramp rates, heat-rate, and spot price are inherent to generation optimization. These are part of the core architecture of the optimizer.
QR Trading performance analysis. Detailed real-time and post-trade analysis dashboard computes expected clearing dispatch and meter quantity, generation cost, revenue from sale in the spot market, and gross margin or P&L. Actual versus optimal scenarios are computed and compared automatically. In one glance, traders and management can compare the different dispatch scenarios.
QR Scheduler is seamlessly integrated to allow traders to load optimal dispatch schedules, modify, validate and submit them electronically with a few mouse clicks to suppliers and the spot market operator.
All output data of optimization, e.g., optimal dispatch, expected clearance dispatch h, detailed P&L, simulations, and forecasts of prices and demand are available via API for real-time integration with your internal systems.
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