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Power Sourcing Portfolio Trading Optimization

  • Real-time intraday and day-ahead power portfolio procurement trading optimization.
  • Minimize total energy sourcing cost.
  • Trade automation, scheduling, and intraday & post-trade performance analysis.
  • Seamless integration of QR AI Forecaster for load and price forecasting.
Contact us to explore a free POC trial.

Unrivaled real-time Electricity Sourcing Portfolio Optimization solution boasting a staggering 20% savings on energy sourcing costs.


Clients’ profile. Traders, portfolio and asset managers of any load-serving entity: utilities, electric cooperatives, munis and energy retail marketers with a diverse power sourcing portfolio composed of bilateral physical PPA and callable contracts, together with the possibility of buying (respectively selling) the shortfall (respectively excess) capacity in real-time intraday and day-ahead bilateral (5 - 60 minutes) spot electricity markets.

1. Minimize total energy sourcing cost by dynamically adjusting for every (5–60 minutes) trading period, buying from the bilateral contracts, along with the corresponding buy-sell in the spot market, while meeting demand, contractual and regulatory constraints.
2. Implement real-time 24/7 automation trading in a web-platform to enable multiple traders to login and manage demand, energy sourcing and all contractual constraints; and the electronic submission of dispatch and buy-sale orders to each bilateral supplier and scheduling to ISOs.
3. A full-featured, ready-for-use, standalone cloud solution that can be easily integrated with in-house ETRMs via flexible APIs.
4. Minimize energy procurement cost. Bilateral contract nomination or scheduling solely driven by cost considerations, as in-unit commitment, misses out on opportunities created in the spot markets. The challenge is to implement dynamic trading strategies that can take full advantage of arbitrage opportunities arising from price movements in volatile spot markets by adjusting the nomination of each bilateral procurement contract up or down and compensating with buy-sell from the spot market to minimize total energy sourcing cost.

Client Profile- Thermal Power Generation

QR Sourcing Advanced Ecosystem

  • Microservice architecture enables accelerated custom configuration of energy portfolio trading and dispatch optimization solutions.
  • API-friendly ecosystem allows flexible integration and data exchange with third party & in-house systems. Functionalities are constantly enhanced and extended to meet clients requirements.
Contact us to explore a free POC trial.

QR Sourcing Optimizer Solution

  • For a procurement portfolio of supply contracts (PPA, bilateral contracted capacity and callable contracts) and spot buy-sell, the solution computes optimal 5-60 minutes dispatch nominations to each bilateral suppliers, taking all constraints into account, and the resulting buy-sell in the spot market, across every forward (5-60 minutes) trading periods, intraday and day-ahead. These outputs are computed at the granularity 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 objective of this optimization model is to minimize total energy procurement costs. This is achieved in two ways:
    • Trimming down-side losses. When forecasted spot prices are lower than the cost of some bilateral procurement contracts, optimization reduces scheduling from these bilateral contracts, subject to contractual constraints, and increases buying from the spot markets to satisfy total load requirements.
    • Capturing upside gains. When forecasted spot prices are higher than the cost of some bilateral procurements, optimization increases buying from these bilaterals to the maximum allowed under contractual terms, to satisfy load requirements first, then sells the excess imbalance to the spot market for profit.
  • How it works. The system fetches around the clock all necessary data, including cost of each bilateral contract building the supply side, the consumption meter quantities of the demand side, SCADA, weather etc. Then within minutes QR AI Forecaster computes accurate price and demand forecasts for every dispatch period. Then the optimizer uses these forecasts to compute the optimal dispatch nomination across the bilateral contracts subject to all constraints, to meet demand at the lowest cost, and deduces the corresponding buy-sell in the spot market. The cycle is automated and runs every 10-15 minutes to produce new dispatch signals, 24/7.

QR Sourcing 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 buy-sell and dispatch signals for every bilateral sourcing contract, every 10 minutes, 24/7.
Software as a Service (SaaS) where we implement QR 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.

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

QR Optimizer minimizes energy procurement cost by 20 to 30%. In no case it will cost you anything. It is a source of revenue and can make 10x its cost, in terms of lower energy cost.

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

A user-friendly web dashboard to configure a custom portfolio buy-sell nomination or dispatch optimization model that matches the type and constraints of each bilateral and callable contract in your procurement portfolio as well as buy-sell in the spot market. This included detailed complex cash flow formulas and constraints for each bilateral procurement contract in the portfolio, the revenue from buy-sell in the spot market, and the net procurement portfolio’s P&L which is the optimization objective function to minimize. Any contract type, e.g., fixed, float, fuel index, pool index, TOU, off/peak, load following, etc.; multiple currencies, and transmission line charges can be easily modeled.

The model incorporates level dependent ramp and spot price modeling, as well as many parameters to control the convergence and accuracy of the model while managing server resources.

QR AI Forecaster forecasts the utility’s demand and the spot price for every forward trading period. These are key inputs to the optimizer. Demand forecast acts as the optimization global constraint: the sum of the optimal bilateral nominations and buy-sales in the spot market must equal the demand forecast for every trading period.

Management of constraints is built in the optimizer architecture : PPA and bilateral contracts can have complex constraints, e.g., (sub)-hourly, daily or monthly must take quantities. These can vary instantly in case of suppliers’ outages. The sum of the optimal bilateral nominations and buy-sales in the spot market must equal the demand forecast for every trading period.

QR Trading performance analysis. Detailed real-time forecast and post-trade nodal analysis dashboard: expected clearing dispatch and meter quantity, bilateral procurement cost, revenue from sale in the spot market, and gross margin or P&L. Actual versus optimal scenarios are computed and compared automatically per bilateral contract nodes and trading period. In one glance, traders and management can compare the different dispatch scenarios.

QR Scheduler is seamlessly integrated with the optimizer to allow traders to load optimal bilateral nominations, modify, validate and submit them electronically with a click of the mouse to suppliers and the spot market operator.

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


  • You can always start with a POC Trial where we back-test some of your trades against the optimal scenarios, and deduce how much QR Trading Optimizer can improve your P&L.
  • License what you need. You can license each component separately, depending on your needs, e.g., price forecasting, bidding & trading optimization, back-office settlement & billing or risk management.
  • Two flexible delivery options:
    • Trading Optimization as a Service. Our cloud platform and expert team do everything, and you receive, via API and in web dashboards, the desired outputs, e.g., price forecasts, optimal bidding & trading schedules every 10 minutes, 24/7. No software installation, hardware and IT resources are needed.
    • Software as a Service (SaaS) where we implement the system on a private cloud of your choosing, or on-site, and you control the data and the models.
  • Ready-to use platform. We offer a large number of especially designed algorithms and models for bidding gas, coal and diesel power plants. These can be used on your assets and markets with minor configuration.
  • Cost-effective pricing. Whether you use QR Trading Optimizer as a service or as SaaS, you pay one single annual subscription fee. The fee comprises the license, maintenance and upgrade releases. In no case will this solution cost anything, it can generate profits worth 10x its license cost.
  • P&L enhancement. QR Trading Optimizer considerably improves the trading P&L, or asset valuation.
    • Maximize profit from bidding, generation and selling in a power market or ISO. Maximize profit from bidding into reserve markets versus selling in the spot market.
    • Minimize plants ware and tear.
  • Expert team. In-house trading optimization models require extensive expert resources. Models are sensitive to myriads of constraints in assets & operations. QR Trading Optimizer was created as a universal optimization platform that could be configured for various operations. Our team of mathematician PhD experts closely work with clients to customize and maintain the optimization model that suits their asset portfolio.

Trading Optimization Case Studies & Video Demos

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Let's talk about your needs

We look forward to exploring the range of options for your projects. Please write to us and one of our project managers will get back to you at once.