Consultancy in AI,Generative AI and Quantum Computacional in
Pricing in Electricity and Gas
Objective of Consultancy Services: Enhance pricing accuracy, generate synthetic data, and explore quantum computing applications in electricity and natural gas markets
Benefits of Consultancy of Generative AI and QC in
Pricing in Electricity and Gas
Machine Learning for Pricing Analysis:
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Develop machine learning models, such as regression, time series analysis, or ensemble methods, to analyze historical pricing data and identify patterns in electricity and natural gas markets.
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Incorporate external factors like weather conditions, market indicators, and demand patterns to build comprehensive pricing models.
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Utilize advanced AI techniques like deep learning or reinforcement learning to capture complex pricing dynamics and optimize pricing strategies.
Generative AI for Synthetic Data Generation:
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Use generative models, including Variational Autoencoders (VAEs) or Generative Adversarial Networks (GANs), to generate synthetic data that mimics the distribution of real-world energy market data.
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Generate synthetic data to augment the historical dataset, increasing the diversity and size of the training data and improving the robustness of pricing models.
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Apply generative models for scenario generation and sensitivity analysis to assess pricing risks under various market conditions.
Compare Consultancy Packages
Package
Description
Scripts (1) in Python or R
Load Consumption model
Feature Engineering
ML models
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Support Vector Machine Regression
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Neural Networks Feed Forward
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Convolutional Neural Network CNN
Quantum ML models
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Quantum k means
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Support Vector Quantum Machine
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Quantum Neural Networks
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Variational Quantum Regressor (VQR)
Forecasting prices and Load Consumption
Multivariate Models
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Autoregressive Vector VAR Models
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Vector Error Correction VEC models
Machine Learning
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Random Forest
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Xgboost
Deep Learning
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Long short term memory LSTM
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Gated Recurrent Units GRU
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CNN + LSTM
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TCN + LSTM/GRU
Advanced Forecasting
Bayesian Deep Learning
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Bayesian Long short term memory LSTM
Generative AI
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DeepAR
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Transformer Model
Quantum Machine Learning
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Quantum Neural Network
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Quantum Long short term memory LSTM
Simulation Models of Prices
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Ornstein–Uhlenbeck process with mean reversion and diffusion jumps
Load Consumption
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SARIMAX
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GAN Sintethyc data
Electricity and Gas Pricing in Generative AI
Hours
Lite
We offer a script that can be used to model Lifetime PD based on our data
Python
Our data: Load Consumption with 5 explanatory variables, electricity prices, futures prices and other values
3
Immediately
10.000 EUR
Standard
We offer a script that can be used to model Lifetime PD based on your data
Python
You can input your data Load Consumption with 5 explanatory variables, electricity prices, futures prices and other values
6
5 Days
14.000 EUR
Pro
We offer a script that can be used to model Lifetime PD based on your data
Python
You can input your data Load Consumption with 10 explanatory variables, electricity prices, futures prices and other values
10
10 Days
18.000 EUR
Premium
We offer a script that can be used to model Lifetime PD based on your data
Python
You can input your data Load Consumption with 20 explanatory variables, electricity and gas prices, futures prices and other values
15
15 Days
24.000 EUR
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Profit at Risk
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Mitigation Risk with Futures
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Risk Premium
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Volume Risk
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Price Risk
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RAROC
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Hurdle Rate
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Pricing Analysis
1. The scripts are delivered as Jupyter Notebook files.
2. You can input your data of Load Consumption with explanatory variables per hour, electricity prices per hour, futures prices and other values. The same for gas prices and consumption in the premium plan.
Important: Firstly, we will perform an audit of the model. If the audit is positive, we will proceed with the model development. Otherwise, we will charge a fee of 5% of the contracted package value.
Important: The number of account operations exceeding a certain limit may result in additional charges.
Please remember the following message regarding the Generative AI Model data we need to discuss with you.
Clients
