Virtual Power Plant Dispatch for Cost-Aware DER Allocation
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Solution Overview
Problem
Existing power grids face challenges in optimizing the use of distributed energy resources (DERs) due to economic and storage costs, leading to inefficiencies in responding to energy demands and fluctuations.
Innovation Solution
A dispatch optimization system that determines subgroups of DERs based on economic and storage costs to efficiently meet energy needs, using a virtual power plant (VPP) for centralized control and energy adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed energy resources are used to respond to energy needs, then energy supply efficiency is improved, but economic cost and storage cost increase
Solution Approach 1:
The system segments the DER fleet into different subgroups based on their operational characteristics, storage capacities, and cost structures. This segmentation allows the optimization system to selectively dispatch appropriate subgroups for different energy needs, minimizing overall costs while maintaining high supply efficiency.
Solution Approach 2:
The optimization system dynamically adjusts dispatch parameters including the amount of energy dispatched, timing of dispatch, and selection of specific DERs based on real-time conditions. By changing these parameters optimally, the system achieves high energy supply efficiency while minimizing economic and storage costs.
2Productivity
If distributed energy resources dispatch energy to meet energy needs, then energy demand response is improved, but deviation from ideal storage level increases
Solution Approach 1:
The system performs preliminary assessments of DER storage levels and ideal storage levels before dispatch decisions. By anticipating the impact of dispatch actions on storage levels, the system can pre-plan dispatch strategies that meet energy demands while minimizing deviation from ideal storage levels, thus maintaining storage stability.
Solution Approach 2:
The optimization system continuously monitors actual storage levels of DERs and compares them against ideal storage levels. This feedback mechanism allows the system to adjust subsequent dispatch decisions to correct any deviations, ensuring that energy demand response is met while maintaining storage level stability over time.
3Productivity
If multiple distributed energy resources are coordinated for energy dispatch, then overall energy efficiency is improved, but system complexity increases
Solution Approach 1:
The patent introduces an optimization system as an intermediary between multiple DERs and the energy market. This intermediary coordinates dispatch decisions across the DER fleet, achieving high overall energy efficiency through centralized optimization while shielding individual DER operators from the complexity of multi-resource coordination.
Solution Approach 2:
The optimization system performs multiple functions including economic cost calculation, storage cost calculation, DER selection, and dispatch coordination. By consolidating these diverse functions into a single universal system, the patent achieves high energy efficiency while managing complexity through functional integration rather than proliferation of separate systems.
Data Source
AI summary
A dispatch optimization system and virtual power plant can be utilized and controlled in order to support the operations of a power distribution system. For example, upon determining an electrical need, the dispatch optimization system and/or virtual power plant may make an energy adjustment by allocating the energy adjustment among distributed energy resources of a fleet of distributed energy resources in order to achieve the energy adjustment. The dispatch optimization system and/or virtual power plant may determine the allocation among the distributed energy resources based on the economic costs and storage costs to use each distributed energy resource.