Virtual Power Plant Scheduler for Grid Dispatch Optimization
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Solution Overview
Problem
The electric power grid faces inefficiencies and instability due to limited energy storage, reliance on peak power, and integration of intermittent renewable sources, necessitating improved methods for dispatching and managing energy distribution, particularly for peak demand and renewable resource integration.
Innovation Solution
A comprehensive operating plan using after-the-fact analysis for performance evaluation and root-cause impact analysis, coupled with a scheduler engine that processes actual system and resource conditions from a relational database to optimize energy dispatch and scheduling, incorporating tools for renewable resource management and demand response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed electric resources are aggregated to meet medium- and large-scale needs, then productivity and resource utilization improve, but device complexity and system provisioning requirements increase
Solution Approach 1:
The patent introduces a virtual power plant (VPP) as an intermediary layer between distributed electric resources and the utility grid. The VPP aggregation software creates a virtual entity that consolidates control and management of multiple small-scale resources (HVAC systems, water heaters, EV batteries) without requiring physical aggregation infrastructure. This intermediary handles provisioning, coordination, and grid interaction, reducing the complexity burden on individual components while enabling large-scale resource aggregation.
2Measurement precision
If after-the-fact analysis is implemented for performance evaluation, then measurement precision and operational insight improve, but loss of time for data processing and analysis increases
Solution Approach 1:
The patent implements preliminary action by continuously collecting, validating, and preprocessing operational data from distributed resources and grid systems in real-time as events occur. Data is normalized, stored in structured formats, and pre-aggregated into meaningful metrics before analysis is needed. This preliminary data preparation eliminates the need for time-consuming data gathering and cleaning during after-the-fact analysis, enabling rapid generation of performance evaluations and root-cause insights.
3Productivity
If real-time dispatch optimization is implemented, then productivity and cost efficiency improve, but device complexity and computational requirements increase
Solution Approach 1:
The patent implements dynamic scheduling through the VPP dispatch software that continuously adapts dispatch decisions based on real-time changing conditions including grid demand, resource availability, weather patterns, and pricing signals. The system uses dynamic optimization algorithms that recalculate optimal dispatch strategies as conditions change, rather than relying on static pre-planned schedules. This dynamic approach enables real-time efficiency improvements while the modular software architecture manages computational complexity through incremental optimization.
Data Source
AI summary
A method is provided for evaluating operational and financial performance for dispatchers in power grid control centers associated with utility systems. A comprehensive operating plan is provided that applies after the fact analysis for performance metrics, root-cause impacts and process re-engineering. after the fact analysis of past events and practices is performed. Actual system and resource conditions are captured. the system and resource conditions are supplied to a relational database. A scheduler engine receives the actual system and resource conditions from the relational database and processes it to calculate system performance. At least one of the following is displayed, transmission evaluation application displays, reference and scenario cases and associations between them, results presented with a graphical or tabular displays, comparison results between scenario cases and a reference case, a family of curves where each curve is a performance metric, comparison of scenario input data, study results and statistical analysis and historical data.


