Energy Pricing System Using Preconfigured Profiles
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Solution Overview
Problem
Current energy pricing systems are inefficient and inaccessible, requiring manual collection and tracking of prices, often taking weeks, and are limited in providing accurate, simultaneous current and historical prices for supply, distribution, and taxes, especially for non-metered consumers and peripheral market participants.
Innovation Solution
A computer-implemented system that uses preconfigured facility profiles and time-dependent inputs, tables, and algorithms with effective dates to quickly calculate and present energy prices, allowing users to select profiles and apportion energy volumes across predetermined time periods, thereby enabling rapid and accurate pricing for all market participants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual collection and tracking of energy prices is performed, then price information can be obtained, but the process takes weeks and is inefficient
Solution Approach 1:
The system pre-calculates and stores energy prices for multiple future start dates and term lengths in advance. When a pricing request is received, the system simply retrieves the pre-calculated price from storage, eliminating the need for time-consuming manual calculations and data collection while maintaining accurate pricing information.
Solution Approach 2:
The system creates standardized price templates and models for different facility types and energy scenarios. These price models are reused across multiple pricing requests, allowing the system to quickly generate accurate price estimates without repeating the entire calculation process for each request.
2Adaptability or versatility
If custom pricing systems are used, then specific account pricing can be provided, but the systems are limited to actively bidding consumers and exclude peripheral market participants
Solution Approach 1:
The system is designed to serve multiple types of market participants including consumers, brokers, sustainability consultants, financial analysts, legal advisors, and other peripheral participants. The same pricing engine and methodology are used for all user types, providing consistent and accurate pricing information regardless of the requester's role in the energy market.
Solution Approach 2:
The system segments pricing information by facility type, energy source, geographic region, and time parameters, allowing different user groups to access the specific pricing data they need through standardized interfaces. This segmentation enables the system to handle diverse pricing requests without requiring separate complex systems for each market participant type.
3Speed
If rack/matrix pricing is used, then quick price reference is available, but the pricing is inaccurate and does not consider specific facility load profiles
Solution Approach 1:
The system dynamically adjusts pricing calculations based on the specific facility load profile selected by the user. Instead of using static rack/matrix prices, the system applies time-dependent variables and apportionment factors that reflect the actual energy consumption patterns of the specific facility type, maintaining both speed and accuracy.
Solution Approach 2:
The system applies different pricing parameters and apportionment factors specific to each facility type and load profile. Rather than using a uniform pricing approach, the system tailors the pricing calculation to the local characteristics of the specific facility being priced, ensuring accuracy while maintaining quick computation through pre-configured profiles.
4Reliability
If iterative bid solicitation is performed, then current prices can be locked in, but the process is cumbersome and requires repeated recalculations
Solution Approach 1:
The system pre-calculates prices for multiple future start dates and term lengths, allowing users to immediately see and compare pricing options without iterative solicitation. The prices are locked in with effective dates, providing reliability while eliminating the need for repeated manual bid processes.
Solution Approach 2:
The system provides immediate feedback by presenting multiple pricing scenarios simultaneously based on the facility profile and energy volume selected. Users can review different start dates, term lengths, and facility types in one query, eliminating the need for iterative back-and-forth bid solicitation while maintaining reliable pricing information.
Data Source
AI summary
A system for calculating energy pricing includes a variety of categories and subcategories of user-selectable preconfigured profiles to derive a detailed, accurate energy profile based on minimal price request information. This profile defines the energy load being priced and its accuracy approaches that which is obtainable through using meter data, but without the need for obtaining and managing such data. The system quickly and accurately calculates both current day and historical pricing based on a single price request by processing the effective dates of time dependent variables, inputs, algorithms, and/or parameters. Managing these effective dates ensures the price output takes into account ongoing market changes in supply, distribution, and/or tax price factors that are known as of the date of the price request and take effect during the future contract term defined by the price request.