Aggregated DER Intraday Scheduling Under Price 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 suboptimal scheduling and revenue maximization.
Innovation Solution
A method for optimal intraday scheduling of aggregated DERs that involves creating a basic operation schedule using historical market and network data, optimizing price and volume parameters, and allowing energy exchanges within the DER pool, modeled using joint price-volume dynamics and solved through iterative mixed-integer linear programming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
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 account for heterogeneous DER types, continuous price fluctuations, and network constraints
Solution Approach 1:
The patent transforms the non-linear intraday scheduling problem into a linear programming framework by changing the mathematical parameters and constraints. This allows the system to handle heterogeneous DER types, continuous price fluctuations, and network constraints simultaneously, improving both revenue generation and scheduling accuracy through optimized linear objective functions and constraints
Solution Approach 2:
The patent introduces dynamic pricing mechanisms that continuously update price parameters based on real-time market conditions and DER performance. The linear programming model dynamically adjusts scheduling decisions across multiple time intervals, allowing the system to adapt to changing market prices and DER availability while maintaining computational efficiency
2Measurement precision
If a comprehensive model considering heterogeneous DERs, continuous price fluctuations, and network constraints is created, then scheduling accuracy is improved, but the computational complexity increases
Solution Approach 1:
The patent reduces computational complexity by transforming the problem from a non-linear optimization framework to a linear programming framework. This parameter change simplifies the mathematical computations while preserving the ability to model heterogeneous DERs, continuous price fluctuations, and network constraints, achieving high scheduling precision without excessive computational burden
Solution Approach 2:
The patent divides the intraday scheduling problem into discrete time intervals and separate linear programming sub-problems. Each time interval is optimized independently using linear constraints, allowing the complex comprehensive model to be solved through multiple simpler computations rather than one overwhelming non-linear optimization
Data Source
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.