Dual Optimizer for Flexible Reserve Power Scheduling
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Solution Overview
Problem
The integration of renewable generation in the power grid poses challenges in predicting and providing flexible reserve power while maintaining economic and reliable solutions, as conventional power plants are no longer sufficient to meet the unpredictable demands for ancillary services like spinning and non-spinning reserves and ramping reserves.
Innovation Solution
A method and system that utilize distributed flexible resources, such as commercial buildings with their own power generation units, to optimize short-term and medium-term schedules for loads and energy resources, employing a dual optimizer unit to determine reserve power schedules and manage power requirements, thereby providing flexible reserve power to the grid while minimizing costs and maintaining load quality-of-service constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional power plants are used to provide ancillary services, then grid stability is maintained through fixed demand, but the system cannot adapt to unpredictable renewable generation demands
Solution Approach 1:
The patent transforms the static, fixed-demand model of conventional power plants into a dynamic system where distributed flexible resources can adapt their power consumption and generation in real-time. The dual optimizer continuously adjusts reserve power schedules based on changing renewable generation patterns, enabling the system to dynamically respond to unpredictable conditions while maintaining grid stability through coordinated control of multiple flexible resources.
2Adaptability or versatility
If distributed flexible resources are used to provide reserve power, then adaptability to renewable generation is improved, but predicting economic and reliable solutions becomes more difficult
Solution Approach 1:
The patent merges multiple distributed flexible resources (loads and distributed energy resources) into an aggregated system managed by a dual optimizer. This consolidation transforms numerous independent, complex optimization problems into a coordinated system-level optimization, reducing overall complexity while maintaining the flexibility benefits of distributed resources.
Solution Approach 2:
The dual optimizer acts as an intermediary between distributed flexible resources and the power grid, managing the complexity of predicting economic and reliable solutions. It receives inputs from multiple resources, processes them through a unified optimization framework, and generates coordinated reserve power schedules, thereby simplifying the prediction task while maintaining adaptability.
3Reliability
If reserve power schedules are optimized for grid stability, then ancillary services are provided, but power requirements of distributed flexible resources may be compromised
Solution Approach 1:
The dual optimizer performs preliminary optimization to determine reserve power schedules that simultaneously satisfy both grid stability requirements and distributed resource power needs. By pre-calculating schedules that account for both objectives, the system avoids conflicts during operation and ensures that distributed resources can meet their power requirements while providing ancillary services.
Solution Approach 2:
The system incorporates feedback mechanisms where the dual optimizer continuously monitors both grid conditions and distributed resource power requirements, adjusting reserve power schedules to maintain balance. This feedback loop ensures that grid stability is maintained while preventing compromise of distributed resource power needs through real-time coordination.
Data Source
AI summary
An optimization-based method and system is disclosed to enable heterogeneous loads and distributed energy resources (DERs) to participate in grid ancillary services, such as spinning and non-spinning reserves, and ramping reserves. The method includes receiving inputs for decision parameters for optimizing an objective for obtaining flexible reserve power, solving the objective for obtaining flexible reserve power, determining a reserve power schedule for a prediction horizon for providing flexible reserve power based on the objective, generating a service bid based on the reserve power schedule for the power grid; and when the service bid is accepted, providing flexible reserve power to the power grid based on the service bid.