endorsedCompleted

AI Forecasting Tool Implementation for Virtual Power Plant

Services Covered:

AI and Machine Learning

Industry

Energy & Natural Resources

Duration

2 months

Budget

Confidential

Start Date

1 May 2024

Team Size

1-5 Employees

Engagement Model

Nearshore

Project Capability Score (PCS)

73/100

Good

Project Capability Score (PCS) estimates how capable Innowise is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

Confidential

Switzerland

Project Summary

Innowise developed and implemented an AI forecasting tool for a virtual power plant to predict power consumption using past consumption, weather conditions, and customer behavior. The model improved prediction quality and reduced errors by around 10%. The team was responsive, professional, delivered outcomes on time, and presented results clearly throughout the engagement.

Key Challenges

Implementing a forecast model for energy consumption.
Integrating multiple data sources (past consumption, weather conditions, customer behaviour) to improve prediction accuracy.

Project Deliverables

Forecast tool to predict consumption in a 4-days horizon
Detailed analysis of the model's performance
Report on feature importance
Modified approach for a 2-days horizon
Deployment of the model in a pre-production system
Configuration and use of a dedicated AWS service to deploy the model to production

Project Solution

Innowise implemented an AI-based forecast tool to predict power consumption for a pool of electrical devices using historical consumption, weather data, and customer behavior. Deliverables included a 4-day forecast model, performance analysis, feature-importance reporting, a modified 2-day approach, deployment to a pre-production environment, and configuration of an AWS service for production deployment.

Project Outcome

Reduced prediction errors by around 10%.
Demonstrated significant improvement in prediction quality versus previous implementations.
Delivered outcomes on time and consistently presented requested results in regular meetings.

Platforms

Cloud

Tech Stack

Amazon Web Services (AWS)

Client Endorsement

Overall Review Rating

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“Innowise's work improved the client's prediction quality and reduced errors by 10%. The team was responsive to requests, professional, and responsible, delivered timely outcomes, clearly presented concepts, and exceeded the client's expectations. Innowise's customer service was impressive.”
Anonymous
Head of People Operations
Date: 07/22/2024