Non-Linear Hydro Plant Efficiency Modeling
We are pleased to introduce a major enhancement in NCP 5.29: a flexible and accurate methodology for modeling hydro plant efficiency. Representing a plant’s production function is a complex task, as efficiency is typically an unknown non-linear relationship between head, flow, and generated power. Previous versions of NCP addressed this challenge with approximations at the penstock and generator levels.
With this new release, efficiency can now be modeled directly at the plant level, offering a simple yet powerful approach. By inputting observed data of gross head, turbined flow, and output power, NCP automatically builds a precise linear approximation of the non-linear function. This enables users to capture the real operational performance of hydro plants across different heads, flows, and operating modes—ensuring both usability and high accuracy in energy production modeling.
Key enhancements in efficiency modeling
This new methodology in NCP provides a robust way to approximate the inherently non-linear efficiency of hydro plants with high accuracy while keeping the model linear and computationally efficient. By relying on observed operational data, users can now capture complex head–flow–power relationships, enabling a more realistic representation of plant performance across different operating conditions.
Minimal data input
Streamlines the modeling process by requiring only observed plant-level data (gross head, turbined flow, and output power), avoiding the need for extensive parameter calibration.
Ease of use
Delivers a flexible and intuitive framework that translates real operational data into accurate linear approximations, ensuring fast adoption without compromising modeling detail.
Precision
Provides a faithful representation of the plant’s actual production efficiency, ensuring accurate simulation of operating modes across a wide range of heads and flows.
Energy bid model
This version introduces a powerful energy bid model for hydro, thermal, renewable, and battery assets. Unlike the traditional cost-based approach, this new formulation allows generators to participate in the market through price–quantity bids, enabling more realistic bidding strategies. Asset owners can now choose whether to minimize operational costs or maximize revenues, with enhanced flexibility for different technologies.
From costs to bids
Move beyond fundamental cost-based modeling by representing bids directly as energy–price pairs with minimum accepted quantities.
Detailed thermal representation
Capture idle operational costs and improve market participation of thermal units with realistic bidding options.
Advanced storage participation
Model simultaneous charge and discharge bids, unlocking accurate and profitable strategies for batteries in competitive markets.
New developments
Alongside major refactoring tasks (thermal ramping limits, wave propagation factors, revenue maximization, hydraulic friction losses, target generation, and combined cycle modeling), the latest version of NCP delivers a set of advanced modeling features:
Renewable curtailment
Define a clear curtailment precedence order, ensuring transparent and optimized dispatch when reductions are required. For stricter strategies, users can also block curtailment entirely.
Generic interpolation constraints
Introduce non-linear relationships directly into the optimization with flexible interpolation between decision variables. This innovation broadens the scope of modeling, enabling realistic representations of asset performance, efficiency curves, and complex market strategies.
General enhancements
Benefit from a wide range of improvements: target turbined water, generic integral constraints and variables, refined rolling horizon scheme, tighter bounds on non-controllable spillage, and hydro storage smoothing for more robust and reliable operations.
Documentation
Review all NCP's powerful capabilities in the documents below.
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NCP 5.29
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