Electricity Meter Demand Forecasting for Peak Load Control
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Solution Overview
Problem
Managing electricity demand effectively for utility customers with varying power sources like photovoltaic solar cells and wind turbine generators is challenging, as these sources can fluctuate, leading to unpredictable peak demand charges.
Innovation Solution
An electricity meter with a Demand Manager application that monitors and adjusts electricity usage by issuing commands to load control devices such as thermostats and switches, shedding or restoring load based on forecasted demand to maintain customer-configured limits, taking into account both utility-provided and additional power sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If customers use additional power sources like photovoltaic solar cells and wind turbine generators, then energy independence is improved, but demand predictability deteriorates
Solution Approach 1:
The system performs preliminary actions by forecasting demand before the demand interval ends and proactively adjusting loads beforehand. The Demand Manager calculates forecasted demand values and issues load adjustment commands in advance to ensure the actual demand will not exceed the target value, resolving the unpredictability caused by variable renewable power sources.
Solution Approach 2:
The system implements continuous feedback by monitoring actual power consumption, comparing it against forecasted values and target demand levels, and automatically adjusting loads based on the deviation. This closed-loop control ensures that despite variable inputs from solar and wind sources, the demand remains predictable and within targets.
2Productivity
If the Demand Manager actively adjusts loads to stay within target values, then demand control is improved, but device complexity increases
Solution Approach 1:
The Demand Manager application performs self-service by automatically forecasting demand, comparing it against targets, and adjusting loads without requiring external intervention or complex external control systems. The meter itself executes the control logic, simplifying the overall system architecture while maintaining effective demand control.
Solution Approach 2:
The patent merges the demand forecasting, target comparison, and load control functions into a single integrated Demand Manager application running on the meter. This consolidation reduces device complexity by eliminating the need for separate forecasting systems, control systems, and communication interfaces.
3Productivity
If forecasted demand is used to proactively manage electricity usage, then peak demand reduction is improved, but measurement precision requirements increase
Solution Approach 1:
The system applies partial action by adjusting only the portion of load necessary to meet the target demand value, rather than controlling all loads. The Demand Manager selectively manages specific electrical loads based on their impact on demand, reducing the measurement precision requirements compared to controlling the entire system.
Data Source
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AI summary
A system for managing electrical consumption of a load device is disclosed. A demand management module may determine a demand interval that is associated with an electrical utility provider. In addition, the demand management module may determine a threshold amount of electricity received by an electrical meter during the demand interval. In some cases, the demand management module may determine a forecasted consumption during the demand interval, for load devices that receive electricity via the meter. Based on a comparison of the forecasted consumption and the threshold, the demand management module may determine whether to control electrical consumption of one or more of the load devices during the demand interval. For example, the demand management module may issue a command to a load managing device to increase or decrease the consumption of the load device.