Central Plant Control with Maintenance Cost Optimization
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Solution Overview
Problem
Existing energy cost optimization systems struggle to incorporate maintenance contracts with complex cost structures into economic optimization algorithms for energy facilities, particularly when maintenance costs vary based on equipment usage, leading to inefficiencies in operational cost management.
Innovation Solution
A control system that includes a controller capable of modifying the cost function to account for maintenance costs, simulating different operational scenarios, and optimizing energy facility operations by selecting setpoints that minimize costs based on maintenance contracts, using a rate variable to adjust for hourly or unit-based maintenance costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If maintenance contracts with complex cost structures are incorporated into economic optimization algorithms, then cost management capability is improved, but system complexity increases
Solution Approach 1:
The maintenance cost function is segmented into base cost and marginal cost components. The base cost covers a base number of run hours, while the marginal cost applies to each hour exceeding the base. This segmentation allows the complex maintenance contract to be broken down into manageable mathematical components that can be integrated into the optimization algorithm.
Solution Approach 2:
The system changes parameters by introducing a maintenance cost function with variable parameters (base cost, base run hours, marginal cost) that can be adjusted based on different maintenance contracts. This allows the optimization algorithm to adapt to various maintenance contract structures without requiring fundamental changes to the system architecture.
2Measurement precision
If piecewise-defined maintenance cost functions are used to accurately represent contracts, then cost accuracy is improved, but computational difficulty increases
Solution Approach 1:
The system performs preliminary simulation of the cost function at multiple different values of a rate variable before final optimization. This preliminary action allows the system to evaluate the piecewise-defined maintenance cost function under various scenarios, ensuring accurate cost representation while managing computational complexity through structured simulation steps.
Data Source
AI summary
A control system for cost optimal operation of an energy facility including equipment covered by a maintenance contract includes equipment configured to operate during an optimization period and a controller. The controller modifies a cost function to include a maintenance cost term that defines a maintenance cost as a function of a rate variable and an equipment usage variable. The controller simulates a cost of operating the energy facility over the optimization period at each of a plurality of different values of the rate variable, selects a value of the rate variable that results in a lowest cost of operating the energy facility over the optimization period, performs an online optimization of the cost function with the rate variable set to the selected value to generate one or more setpoints for the equipment, and operates the equipment during the optimization period in accordance with the generated setpoints.