Grid Demand Management Using Wind-Load Period Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current power grid systems lack an effective method for users to assess environmental conditions and electricity consumption demands in relation to electricity availability and cost, leading to inefficient energy usage and potential grid overload.
Innovation Solution
A power management system that receives total wind power and load forecasts, classifies time periods based on their relationship, and transmits this characterization to subscribers, allowing them to determine optimal power consumption times and plan electricity usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users consume electricity during high demand periods, then immediate power needs are met, but electricity cost increases and grid overload risk increases
Solution Approach 1:
The system performs preliminary classification of time periods into favorable and unfavorable periods based on forecasted wind power and load data before users make consumption decisions. This allows users to plan ahead and shift loads to favorable periods, avoiding peak demand charges and reducing grid stress during high-demand periods.
Solution Approach 2:
The system continuously monitors actual wind power generation and load consumption, comparing them against forecasts, and uses this feedback to refine future classifications and forecasts. This feedback loop enables dynamic adjustment of load management strategies to optimize cost savings and grid stability over time.
2Ease of operation
If users consume electricity during high demand periods, then immediate power needs are met, but grid overload risk increases
Solution Approach 1:
The system classifies time periods in advance based on forecasted conditions, identifying favorable periods for load consumption before the grid becomes overloaded. This proactive approach allows users to shift loads to off-peak periods, preventing demand surges that could cause grid collapse while ensuring power availability during classified favorable periods.
Solution Approach 2:
The system uses feedback from actual grid performance and consumption patterns to continuously improve its forecasting and classification accuracy, enabling better prediction of grid stress conditions and more effective load management strategies to maintain grid reliability.
3Productivity
If the system classifies time periods based on wind power and load forecasts, then users can optimize energy consumption timing, but system complexity increases
Solution Approach 1:
The system segments the time period into discrete favorable and unfavorable periods based on forecasted wind power and load characteristics. This segmentation simplifies user decision-making by providing clear, actionable classifications rather than requiring users to analyze complex continuous data, thereby improving energy efficiency without significantly increasing perceived system complexity.
Solution Approach 2:
The system changes the parameter representation from raw forecast data to simplified classifications (favorable/unfavorable periods) that are easier for users to understand and act upon. This parameter transformation maintains the analytical depth needed for optimization while presenting information in a user-friendly format that reduces operational complexity.
Data Source
AI summary
This invention describes a power management system that may receive a total wind power forecast that can be provided to an electric grid that supplies power to a load. A power management system may receive a first total load forecast for the electric grid corresponding to a load. A power management system may classify time periods with a first characterization based on a relationship between the total wind power forecast and the first total load forecast. A power management system may transmit the first characterization with a corresponding period for the first characterization to a subscriber thereby allowing a subscriber to determine timing of power consumption based on a load plan. A power management system may receive the load plan from the subscriber, wherein each load plan includes a planned electricity consumption from the electric grid and at least one of the plurality of periods.