Aggregation Management Apparatus Spatial Correlation Error Evaluation
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Solution Overview
Problem
Conventional methods for evaluating photovoltaic power generation plants struggle to accurately predict the total generated energy and its predictive error, leading to reduced profitability due to errors in energy supply schedules, which result in financial losses for aggregation businesses.
Innovation Solution
An aggregation management apparatus that acquires position and performance information of photovoltaic power generation facilities, calculates an evaluation value for predictive error based on correlation levels of solar radiation errors between locations, and adjusts buying prices accordingly to improve prediction accuracy and business profitability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional evaluation methods are used based on solar radiation data and facility capacity, then the evaluation process is simple, but the predictive error of total generated energy cannot be accurately evaluated
Solution Approach 1:
The patent introduces a new evaluation parameter (predictive error evaluation value) that combines solar radiation predictive errors with spatial correlation coefficients. This transforms the conventional simple evaluation into a more comprehensive assessment that accounts for both individual facility prediction accuracy and the statistical relationships between multiple facilities, thereby resolving the contradiction between measurement precision and method complexity.
Solution Approach 2:
The patent uses spatial correlation coefficients as an intermediary element to connect individual facility predictive errors with the total generated energy prediction. By introducing this intermediate statistical parameter that quantifies the relationship between solar radiation errors at different locations, the system can evaluate the predictive error of aggregated energy without requiring complex direct measurement of total energy predictions.
2Productivity
If the aggregator increases total generated energy aggregation, then the scale of business increases, but the predictive error of total generated energy also increases leading to higher settlement costs
Solution Approach 1:
The patent changes the evaluation approach by introducing a diversity assessment parameter that measures how solar radiation errors vary across different facilities. By evaluating both the magnitude of predictive errors and the diversity (low correlation) of errors across facilities, the system can identify combinations of facilities that aggregate to higher total energy with better overall prediction accuracy, thus resolving the contradiction between aggregation scale and reliability.
Solution Approach 2:
The patent applies the principle of merging by combining multiple photovoltaic facilities into an aggregation portfolio. The key insight is that when facilities are geographically dispersed, their solar radiation errors become less correlated, and the aggregation effect reduces the overall predictive error of total generated energy. This merging strategy allows the aggregator to increase total energy aggregation while maintaining or even improving prediction accuracy.
3Measurement precision
If facilities are selected without considering spatial correlation of solar radiation errors, then the selection process is straightforward, but the predictive error reduction effect is insufficient
Solution Approach 1:
The patent introduces a spatial correlation coefficient parameter that quantifies the relationship between solar radiation errors at different locations. By calculating this parameter for pairs of facilities and using it in the predictive error evaluation, the system transforms the facility selection process from a simple capacity-based approach to a statistically-informed selection that explicitly accounts for spatial relationships, thereby achieving better predictive error reduction.
Data Source
AI summary
According to one embodiment, an aggregation management apparatus includes processing circuitry configured to acquire position information and performance information of each photovoltaic power generation facility in a set of photovoltaic power generation facilities from a storage; and calculate an evaluation value of a predictive error of a total generated energy of the set of photovoltaic power generation facilities, based on the position information, the performance information, and a correlation level of the predictive errors of solar radiation information depending on a distance between two locations.