Demand Setpoint Reset Around Meter Reads to Cut Peak Charges
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Solution Overview
Problem
The challenge lies in efficiently managing peak demand charges in electrical systems, particularly in remote or congested areas, where existing technologies struggle to optimize energy usage due to uncertainty in meter read times and infrequent utilization of transmission and distribution infrastructure, leading to higher electricity supply and delivery costs.
Innovation Solution
An automatic controller is introduced that resets the demand setpoint multiple times around anticipated meter read occurrences to minimize peak power consumption, utilizing historical data and battery ratings to adjust the setpoint values, ensuring optimal energy usage and reducing demand charges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If additional T&D systems are constructed to satisfy peak demand, then power delivery capability is improved, but construction costs and infrastructure utilization efficiency worsen
Solution Approach 1:
The controller performs preliminary actions by resetting the demand setpoint before the anticipated meter read occurrence, proactively preparing the system to minimize peak power measurements. This advance preparation allows the system to optimize energy usage patterns ahead of time, avoiding the need for additional T&D infrastructure to handle peak demands that could have been prevented through predictive control.
2Loss of energy
If demand setpoint is reset frequently, then peak power consumption is reduced, but control system complexity increases
Solution Approach 1:
The controller performs preliminary actions by resetting the demand setpoint before the anticipated meter read occurrence, proactively preparing the system to minimize peak power measurements. This advance preparation allows the system to optimize energy usage patterns ahead of time, avoiding the need for additional T&D infrastructure to handle peak demands that could have been prevented through predictive control.
Solution Approach 2:
The controller utilizes feedback from historical data and battery ratings to dynamically adjust the demand setpoint. By continuously monitoring system performance and comparing actual power consumption against the demand setpoint, the controller refines its control strategy, reducing peak power consumption while maintaining manageable system complexity through adaptive rather than purely predetermined control actions.
3Measurement precision
If meter read timing is uncertain, then demand charge optimization is reduced, but system adaptability requirements increase
Solution Approach 1:
The controller performs preliminary actions by resetting the demand setpoint before the anticipated meter read occurrence, proactively preparing the system to minimize peak power measurements. This advance preparation allows the system to optimize energy usage patterns ahead of time, avoiding the need for additional T&D infrastructure to handle peak demands that could have been prevented through predictive control.
Solution Approach 2:
The controller employs dynamic control by adjusting the demand setpoint based on multiple factors including historical data, battery ratings, and anticipated meter read occurrences. Rather than using a fixed control strategy, the system adapts its control parameters in real-time, enhancing measurement precision for demand charge optimization while maintaining the flexibility to handle uncertain meter read timing through dynamic rather than static control mechanisms.
Data Source
AI summary
The present disclosure is directed to systems, apparatuses, and methods for controlling an electrical system using setpoints. Some embodiments include systems that receive a meter read schedule comprising anticipated meter read occurrences. The systems may set a demand setpoint representing a desired upper limit of demand of the electrical power system and adjust the demand setpoint during a billing period. The system may also reset the demand setpoint multiple times at different reset points around each of the anticipated meter read occurrences.