Dean Shabi
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Case Study

Exempt Supply Matching

Optimizing energy distribution with ML algorithms

Industry
Energy
Partner
Confidential Utility Partner

Capabilities & tooling

Neural NetworksOptimizationGraph AlgorithmsPythonPyTorchEnergy TradingMatch-making
Exempt Supply Matching

Project Overview

Created a matching platform that keeps SME demand within Great Britain's Supplier Exempt Class A limits, capping exports at 5 MW (2.5 MW for domestic loads), while leveraging BSC Modification P442's February 2025 reforms to strip licence-exempt volumes out of EMR levies via an accredited Exempt Supply Notification Agent. This innovative solution optimally pairs SME energy consumers with local sub–5 MW generators, unlocking approximately £50/MWh in non-commodity cost savings.

In Plain English

  • Small generators can legally sell power without a full supply license if they stay below 5 MW overall and send no more than 2.5 MW to homes.
  • P442 makes sure those exempt deals are recorded separately, so they do not trigger the big government levies that drive up bills.
  • An Exempt Supply Notification Agent handles the settlement admin, letting SMEs buy cleaner local power without drowning in paperwork.

How the Non-Commodity Savings Land

The biggest “non-commodity” line items on a UK business power bill are policy levies such as the Contracts for Difference Supplier Obligation and Capacity Market charges. Together, these can add £40–£60 per MWh during a typical settlement year.

By routing sub-5 MW generation through a Supplier Exempt Class A structure and registering it with an Exempt Supply Notification Agent, P442 keeps that energy out of the levy calculations. Every exempt MWh avoids those policy surcharges, which flows straight through as savings for the matched SME buyer while still compensating the local generator at an agreed strike price.

This algorithm has generated millions in new revenue streams and savings for businesses, while promoting more sustainable, localized energy consumption patterns.

Benefits

£50/MWh

Cost Savings

in non-commodity costs

£3M+

Value Generated

Unprecedented revenue stream for SMEs and utilities

60+

Successful Pairings

35% match success rate achieved

Annual Savings Calculation

7 GWh

Annual Generation

×
£50/MWh

Cost Savings

£350,000

Total Annual Benefit

The Challenge

UK renewable energy regulations offer significant cost-saving opportunities through "exempt supply" arrangements, but establishing these partnerships presents complex challenges:

Regulatory Complexity

UK energy regulations permit exemptions from certain non-commodity costs when generators supply nearby businesses directly, but navigating these regulations requires specialized expertise and careful compliance management.

Matching Difficulty

Finding viable generator-consumer pairs requires analyzing multiple complex factors: compatibility criteria, load profiles, suitable connection points, and technical feasibility.

Scale & Efficiency

Manually identifying and evaluating potential matches across thousands of sites is prohibitively time-consuming and prone to missed opportunities.

Data Integration

Combining and analyzing fragmented data from generation profiles, consumption records, grid infrastructure, and regulatory requirements presents significant technical challenges.

Solution

I developed a comprehensive solution to address the complex challenge of matching exempt renewable generators with nearby businesses, creating efficient and cost-effective energy partnerships that leverage UK electricity regulations.

Technical Approach

  • Advanced matching algorithm to identify optimal generator-consumer pairings
  • Real-time regulatory compliance verification system
  • Advanced load profiling to match generation and consumption patterns

Key Innovations

  • Proprietary scoring algorithm for optimal matching
  • Dynamic regulatory compliance engine with real-time updates
  • AI-powered consumption forecasting for maximizing exemption value
  • Automated contractual agreement generation with legal validation

Regulatory Framework

Supplier Exempt Class A

Regulatory classification that allows for certain exemptions from standard energy supply obligations when specific conditions are met between generators and consumers.

BSC Modification P442

Balancing and Settlement Code modification that enables specific matching arrangements between small-scale generators and consumers, supporting localized energy markets.

Key Regulatory Requirements

  • Generators must be sub-5 MW capacity to qualify for exemptions
  • Supply must meet regulatory requirements for direct supply
  • Matching must be documented and reported to regulatory authorities
  • Balancing responsibilities must be properly assigned and managed

System Architecture

Data Inputs

Consumer Profiles
Generator Output
Location Data

Processing Layer

Matching Algorithm
Optimization Engine
Forecast Models

Output Systems

Match Reports
Regulatory Docs
Billing Integration

Continuous Optimization Loop

Application Scenario

Example Pairing

Solar Installation

~4.8 MW capacity solar farm with 7 GWh annual generation

Business Complex

A collection of 20-25 SMEs with varied energy needs

Cost Calculation

Annual generation: 7 GWh × £50/MWh savings = £350,000 potential annual benefit

Key Benefits

  • Cost Reduction

    Annual savings of £350,000 based on 7 GWh generation

  • Efficient Energy Use

    Up to 85% of generated power consumed locally

  • Revenue Stability

    More stable revenue streams for renewable generators

  • Environmental Impact

    Carbon footprint reduction equivalent to removing 150-200 cars from roads

Business Impact

1

Cost Savings

Unlocked approximately £50/MWh in non-commodity cost savings for participating businesses.

2

Revenue Generation

Generated millions in new revenue streams through this innovative matching service.

3

Sustainability

Promoted more sustainable, localized energy consumption patterns, reducing transmission losses.

4

Market Advantage

Provided significant competitive advantage in the energy supply market with this unique offering.

Future Developments

Platform Scaling

Expanding the platform to handle larger volumes of participants and more complex matching scenarios.

Enhanced AI

Implementing more advanced machine learning algorithms to improve matching efficiency and forecast accuracy.

Marketplace Expansion

Developing a broader marketplace model that supports additional energy services and participant types.