Power Dispatch Scheduling Integrating Demand Response and Distributed Energy Resources
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Solution Overview
Problem
Current economic dispatch systems in the energy industry fail to incorporate Demand Response (DR) and Distributed Energy Resources (DER) into their scheduling processes, leading to inefficiencies in power resource management and increased operating costs.
Innovation Solution
The development of systems and methods that compute day-ahead, day-of, and real-time schedules for power resources, including DR and DER, while considering bilateral contracts and market-based trade opportunities, using computer algorithms to optimize dispatch and minimize operating costs and imbalances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional economic dispatch systems are used, then scheduling of power resources is simplified, but Demand Response and Distributed Energy Resources are excluded from the scheduling process
Solution Approach 1:
The scheduling system is divided into separate functional modules: a data collection module that gathers information from multiple sources (DR resources, DER resources, conventional generation), a processing module that handles optimization calculations, and a dispatch module that executes schedules. This segmentation allows the system to incorporate diverse resource types without overwhelming complexity.
Solution Approach 2:
The economic dispatch system is designed as a universal platform that can handle multiple types of power resources simultaneously - conventional generation units, demand response resources, and distributed energy resources. The system uses a unified optimization framework that accommodates different resource characteristics through configurable parameters and constraints.
2Productivity
If DR and DER resources are integrated into economic dispatch, then power resource management efficiency improves, but system complexity increases
Solution Approach 1:
An intermediary optimization layer is introduced between data collection and dispatch execution. This layer aggregates data from diverse DR and DER resources, performs unified economic optimization considering all resource types and market conditions, and translates optimization results into actionable dispatch schedules. The intermediary handles the complexity of multi-resource integration while presenting simplified interfaces to both data sources and execution systems.
Solution Approach 2:
The system manages complexity by dynamically adjusting operational parameters such as resource availability coefficients, cost functions, and constraint weights based on real-time conditions. DR and DER resources are integrated through parameter-based modeling that allows their unique characteristics (intermittency, controllability, cost structures) to be incorporated without fundamental system redesign.
3Loss of energy
If comprehensive power resource scheduling is implemented, then operating costs are reduced, but computational requirements increase
Solution Approach 1:
The system performs preliminary optimization calculations in advance to generate base dispatch schedules. Day-ahead and real-time schedules are computed using comprehensive optimization that considers all available DR, DER, and conventional resources. By performing these calculations preliminarily rather than reactively, the system achieves cost optimization without requiring excessive real-time computational power during actual dispatch operations.
Solution Approach 2:
The optimization system uses dynamic time horizons and computational granularity. Comprehensive optimization is applied at strategic planning levels where cost savings are most significant, while operational adjustments use simplified models. The system adapts computational depth based on time scale (day-ahead vs. real-time) and resource criticality, balancing computational requirements against operating cost reduction opportunities.
Data Source
AI summary
A system and process/method is provided, which economically optimizes the dispatch of various electrical energy resources. The disclosed process/method is linked to and communicates with various sources of input data, including but not limited to, EMS/SCADA legacy Energy Management Systems (EMS), legacy Supervisory Control and Data Acquisition (SCADA) Systems, Demand Response (DR) and Distributed Energy Resources (DER) monitor, control, schedule, and lifecycle management systems (DR/DER Management System), and Energy Markets, electrical energy commodity trading systems (Trading Systems), and Operations System (OPS) in order to compute optimal day-ahead, day-of, and real-time schedules of various durational length for generation, demand response and storage resources while taking into account bilateral contracts and market-based trade opportunities.