EnergyX360

EnergyX360 is a real-time decision-support solution for plant-wide energy and utility network optimization. It combines real-time plant data, process engineering models, equipment operating constraints, and MINLP-based optimization to determine the most energy-efficient operating strategy across utility systems.

By continuously evaluating equipment availability, operating conditions, process loads, and utility demand, EnergyX360 provides actionable recommendations for boilers, turbines, motors, compressors, and utility networks. This enables process and operations teams to reduce energy consumption and emissions while maintaining reliable plant operation.

Salient Features

Plant-Wide Utility Network Optimization

Model and optimize interconnected steam, boiler, turbine, rotating equipment, and utility systems while accounting for equipment relationships, operating limits, and plant demand.

MINLP-Based Optimization Engine

Use Mixed-Integer Nonlinear Programming (MINLP) to evaluate operating conditions, equipment status, process loads, and utility demand and determine the optimal operating strategy.

Equipment & Utility Optimization

Optimize steam generation and consumption, turbine and motor-driven equipment selection, boiler loading, air compressor routing, BFW and DMW generation, and cooling-water operation based on actual plant requirements.

Real-Time Optimization & Operator Actions

Continuously identify optimization opportunities and provide actionable recommendations for equipment changeovers, utility allocation, boiler loading, cooling-water pumps, air compressors, and other energy-intensive operations.

Customizable Limits, Priorities, etc.

a. Engineers can manipulate configured KPI limits based on plant priorities.

Sensitivity Analysis

Optimax provides feature to run multiple cases simultaneously with different limit ranges to enhance the actionable insights.

Role-Based Access and Security

Provides access control to ensure only authorized personnel can view or edit monitoring configurations.

Result Analysis Tool

Offers diagnostic tools to help engineers quickly investigate and resolve performance issues with different configurations

Client Benefits

Reduce Energy Bills by 2–3%

Optimize the operation of compressors, BFW systems, steam turbines, cooling-water networks, and other rotating equipment to reduce overall energy costs.

Reduce CO₂ Emissions by 3–4%

Improve plant-wide energy and utility operation to reduce emissions associated with inefficient energy consumption.

Achieve 3–5% Energy Savings

Optimize steam and power generation, distribution, and consumption based on actual operating requirements and equipment constraints.

Improve Utility Allocation

Match steam, power, cooling water, compressed air, and other utility generation and distribution with actual plant demand to reduce inefficiencies.

Support Real-Time Operating Decisions

Provide operators with current operating conditions, optimization recommendations, impact, and estimated savings to support faster, data-driven energy management decisions.

Dashboard & Snapshots

Configure all tags related to specific Equipment:

Solution configuration [Defining the Objective: Maximize Production, Minimize Utility]:

Solution configuration [Defining cases of interest – Multiple cases can also be added]:

Result Tag Configuration: Identify the potential actionable insights.

Sensitivity Analysis: Supporting engineers to evaluate appropriate configurations

Case Studies

Development of Soft Sensor to predict the C5 contents in Debutaniser column Overhead:

Background

In modern petrochemical operations, maintaining product specifications within tight limits is critical for both quality assurance and process efficiency. One of the key challenges faced by a leading chemical plant was the need for real-time prediction and monitoring of C5 content in the overhead stream of the debutanizer column — a crucial step to ensure product specification compliance and optimize operations.

Challenge

Traditional laboratory testing methods for measuring C5 content introduced significant time delays, making real-time adjustments difficult. The plant required a fast, accurate, and reliable solution to continuously monitor C5 levels, allowing operators to take timely corrective actions and avoid off-spec products.

Solution with AnalyticX

Using AnalyticX, the engineering team was able to develop a soft sensor — a machine learning-based predictive model — specifically designed to estimate the C5 content in the debutanizer overhead stream in real time.

Key steps included:

Seamless ingestion of historical operational data into AnalyticX without any coding requirements.
Applying statistical analysis to identify key process variables influencing C5 concentrations.
Rapid development and training of a machine learning model tailored to predict C5 content with high accuracy.
Deployment of the predictive model into live operations for real-time product spec monitoring.

Results

Enhanced Product Monitoring:
Operators now have a real-time view of the predicted C5 content, significantly reducing reliance on delayed lab measurements.
Improved Process Control:
By closely tracking C5 levels, the plant was able to make timely adjustments to operational parameters, ensuring consistent product quality.
Reduced Off-Spec Production:
Real-time insights helped minimize off-spec batches, leading to material savings and reduced reprocessing costs.

Key Takeaways

AnalyticX enabled the rapid development of a soft sensor customized for critical KPI monitoring.

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