Intraday DER Scheduling With Price-Volume Dynamics and Network Constraints
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Solution Overview
Problem
Existing intraday DER trading techniques fail to effectively manage heterogeneous Distributed Energy Resources (DERs) due to assumptions of single DER types, neglect of continuous price fluctuations, and lack of network constraints, leading to inefficient market participation and revenue maximization.
Innovation Solution
A method for optimal intraday scheduling of aggregated DERs that models joint price-volume dynamics, allows energy exchanges within the DER pool, and optimizes basic operation schedules using iterative calculations to determine final price and volume parameters, ensuring compliance with market and network constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If existing intraday DER trading techniques are used, then the cost of energy procurement is reduced or revenue is maximized, but the techniques fail to model continuous price fluctuations and do not consider network constraints
Solution Approach 1:
The patent transforms the static pricing assumption into a dynamic model that captures continuous price fluctuations throughout the intraday period. The joint price-volume dynamics distribution is updated iteratively as new market data becomes available, allowing the scheduling to adapt to changing market conditions rather than relying on constant price assumptions.
Solution Approach 2:
The patent implements a feedback mechanism where the scheduling model continuously receives updated market price signals and network constraint information, then adjusts the DER scheduling decisions accordingly. This iterative updating process allows the system to learn from market outcomes and improve scheduling accuracy over time.
2Productivity
If existing intraday DER trading techniques are used, then trading decisions are made, but the techniques do not consider network constraints for injecting or withdrawing power at network buses
Solution Approach 1:
The patent integrates multiple functions into a unified scheduling framework that simultaneously optimizes for revenue while respecting network constraints. The model handles both market trading objectives and physical network limitations within a single optimization problem, ensuring that scheduling decisions are both economically optimal and physically feasible.
Solution Approach 2:
The patent incorporates network constraints as explicit parameters in the optimization model, including power injection/withdrawal limits at network buses and energy exchange constraints within the DER pool. These parameters dynamically shape the feasible scheduling space based on current network conditions.
3Device complexity
If existing intraday DER trading techniques are used, then single DER types are analyzed, but the heterogeneity of DERs is not considered
Solution Approach 1:
The patent segments the heterogeneous DER portfolio into distinct categories (generation assets, storage systems, flexible loads) while maintaining the ability to model unique characteristics of each type. This segmentation allows the model to capture the diverse behaviors and constraints of different DER technologies without overwhelming complexity.
Solution Approach 2:
The patent creates a composite scheduling model that integrates multiple DER types with different technical characteristics into a unified framework. The model treats the DER portfolio as a composite system where each asset type contributes its unique properties to the overall scheduling optimization.
4Ease of operation
If existing intraday DER trading techniques are used, then trading schedules are generated, but energy exchanges within the DER pool are not permitted
Solution Approach 1:
The patent introduces an internal energy exchange mechanism that acts as an intermediary between DER assets within the pool. This internal market allows DERs to trade energy with each other before participating in the external intraday market, optimizing resource allocation and reducing the need for expensive external transactions.
Data Source
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AI summary
This disclosure relates generally to optimal intraday scheduling of aggregated Distributed Energy Resources (DERs). Owing to their stochastic nature, DERs aggregators are more suited to participate in intraday electricity markets. The current works on DER aggregators trading in intraday markets do not satisfactorily model the different aspects. The disclosure is an optimal trading strategy for aggregators managing heterogeneous DERs to participate in intraday markets. The intraday market is modelled using a joint price-volume dynamics distribution and an optimal bidding strategy is disclosed for the trades/bids placed earlier to be corrected based on the revised forecasts of demand and generation while allowing for energy exchanges within the DER pool. Further the optimal bidding strategy of aggregators in an intraday market is a MINLP problem, which is solved by converting the complex non-linearities in the problem into a coupled MILP - simple maximization set-up, which is then solved in an iterative fashion.