LOS ANGELES, CA, Neel Somani is making complex energy market concepts more accessible, offering a practical walkthrough of how to build a simplified power pricing model, drawing from his experience working on power systems at Citadel.
In a recent video, Neel Somani addresses one of the most common questions he receives: how to construct a power pricing model from scratch. While noting that he cannot replicate proprietary systems used at firms like Citadel, he demonstrates a streamlined version that captures the core mechanics of real-world energy markets.
A Simple Model with Real-World Relevance
Neel Somani introduces a scenario involving three interconnected locations, each with its own electricity demand and generation capabilities. The model assumes:
- Two primary demand centers (500 MW and 700 MW)
- Transmission constraints limiting flow between locations (200 MW max)
- Generators at each location with varying cost structures
Despite its simplicity, the framework mirrors real grid dynamics, where electricity must be efficiently distributed across constrained infrastructure while balancing cost and demand.
“This is simple enough that you could solve it by hand,” Somani explains, emphasizing that the goal is clarity and adaptability rather than complexity.
Building the Model: Optimization at the Core
At the heart of the system is a production cost model, a foundational concept in energy economics. Using the optimization tool AMPL, Somani walks through how to structure the problem:
- Objective: Minimize total generation cost across all locations
- Constraints:
- Supply must equal demand plus net transmission flows
- Generators have production limits (capped at 1 GW)
- Transmission lines have capacity limits
He illustrates how energy flows between nodes using directional variables, where positive or negative values indicate exports or imports between locations.
Introducing Realistic Cost Structures
To make the model more dynamic, Neel Somani assigns different cost profiles to each generator:
- Generator A: Flat $20/MWh
- Generator B: Tiered pricing ($10/MWh for first 200 MW, then $30/MWh)
- Generator C: Flat $25/MWh
This layered approach reflects how real energy markets often operate, where marginal costs increase as capacity is pushed.
From Code to Market Prices
After defining the model and inputting demand data, Somani demonstrates how to run the system using AMPL. The output reveals:
- Generation levels at each location
- Power flows across transmission lines
- Locational prices, derived using dual variables in optimization theory
These prices represent the marginal cost of delivering electricity at each node, one of the most important concepts in modern power markets.
Bridging Technical Depth and Accessibility
While the example is intentionally simplified, Somani highlights its flexibility. The model can be expanded to include:
- More locations and transmission lines
- Time-based demand fluctuations
- Renewable energy inputs and intermittency
- More complex cost functions
By starting with a clear, solvable framework, he provides a foundation that students, engineers, and analysts can build upon.
A Technologist Focused on Education and Impact
Beyond this tutorial, Somani is widely recognized for his work at the intersection of blockchain and high-performance systems. As the founder of Eclipse, he is developing one of the fastest Layer 2 solutions powered by the Solana Virtual Machine, backed by $50 million in Series A funding.
A graduate of University of California, Berkeley with a triple major in computer science, mathematics, and business administration, Neel Somani combines deep technical expertise with a strong commitment to mentorship. He has supported more than 20 students through scholarships and academic guidance, reinforcing his belief in accessible education.
Making Complex Systems Understandable
Neel Somani’s approach reflects a broader mission: demystifying complex systems without oversimplifying them. By breaking down power pricing into an intuitive, hands-on model, he not only educates but empowers others to explore and innovate within critical infrastructure systems.
As interest in energy markets, optimization, and decentralized systems continues to grow, voices like Somani’s are helping bridge the gap between advanced theory
