Central Energy Facility Cost Optimization via Block-and-Index Rate Allocation
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Solution Overview
Problem
Central energy facilities face challenges in optimizing costs under block-and-index rate structures or load-following-block rate structures, as existing systems lack efficient methods to allocate energy resources effectively across sub-periods to minimize costs.
Innovation Solution
A system that includes processors and non-transitory computer-readable media to obtain a block-and-index rate profile for a future time period, applying it to an optimization process to determine energy resource allocation at each time step, and allocate energy resources accordingly, using graphical user interfaces, spreadsheet files, or predictive methods to input and display the rate profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional energy allocation methods are used, then system simplicity is maintained, but cost optimization under block-and-index rate structures cannot be achieved
Solution Approach 1:
The system performs preliminary actions by obtaining the block-and-index rate profile for the future time period before optimization. The rate profile including block rates and block sizes for multiple sub-periods is acquired in advance and stored for use in the optimization process, enabling proactive cost management rather than reactive adjustments
Solution Approach 2:
The future time period is segmented into multiple sub-periods, each with its own block rate and block size parameters. The optimization process divides the allocation decision into discrete time steps within each sub-period, allowing granular control of energy resource allocation to match the segmented rate structure and achieve cost optimization
2Productivity
If energy resources are allocated without optimization, then operational simplicity is maintained, but operational expenses cannot be minimized
Solution Approach 1:
The energy resource allocation is made dynamic through the optimization process that determines the amount of energy resources to be consumed or produced at each time step based on the block-and-index rate profile. The system dynamically adjusts allocation decisions across multiple time steps within sub-periods to respond to varying block rates and block sizes, transforming static allocation into adaptive optimization
Solution Approach 2:
The system changes key parameters including block rate, block size, and time step allocations through the optimization process. By varying these parameters across different sub-periods and time steps according to the rate profile, the system achieves improved energy management efficiency while adapting to the specific block-and-index rate structure
Data Source
AI summary
A method includes operating equipment to consume energy resources including energy or power purchased from a utility, and obtaining a block-and-index rate profile for a future time period. The block-and-index rate profile includes a block rate and a block size for each of a plurality of sub-periods in the future time period. The block size for a sub-period identifies an amount of energy or power priced at the block rate for the sub-period. The method also includes applying the block-and-index rate profile in an optimization process for the equipment over the time period, running the optimization process, and allocating energy resources to the equipment over the time period in accordance with a result of the optimization process.