Energy Management Server Pre-calculated Schedules for Demand Response
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Solution Overview
Problem
Existing energy management systems face challenges in quickly responding to demand response signals due to lengthy operation schedule calculations, leading to disadvantageous energy storage and system activation scenarios, especially with energy-related systems like heat storage devices that rise slowly.
Innovation Solution
An energy management server with an estimation unit, condition setting unit, calculator, receiver, and controller that estimates energy demand, sets suppression conditions, calculates optimized operation schedules, and controls apparatuses based on demand response signals, allowing for immediate activation of systems under advantageous conditions by pre-calculating multiple scenarios using virtual DR signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If operation schedule calculation is performed using existing methods, then energy or cost savings can be achieved in a building or facility, but the calculation time becomes too long (1-2 hours) to respond immediately to demand response signals
Solution Approach 1:
The system performs preliminary calculation of operation schedules in advance, before demand response signals are received. Multiple candidate schedules are pre-calculated and stored, so when a demand response signal arrives, the system can immediately select and execute an appropriate pre-calculated schedule without performing time-consuming real-time calculations.
Solution Approach 2:
The system dynamically adapts pre-calculated operation schedules based on received demand response signals. Instead of using fixed static schedules, the system selects and adjusts from multiple pre-calculated candidate schedules to match the actual demand response conditions, achieving both speed and optimality.
2Manufacturing precision
If operation schedule calculation takes 1-2 hours, then thorough optimization can be achieved, but the time available for energy storage in advance becomes too short, especially for slow-rising energy related systems
Solution Approach 1:
The system pre-calculates operation schedules that include optimal timing for energy storage operations. By performing calculations in advance rather than in real-time, the system provides sufficient lead time for slow-rising energy related systems to complete energy storage operations before peak demand periods, while still achieving thorough optimization.
Solution Approach 2:
The system dynamically adjusts the timing and amount of energy storage operations within pre-calculated schedules based on actual system conditions and demand response signals, optimizing both the quality of optimization and the timing of energy storage operations for slow-rising systems.
3Productivity
If existing methods are used to create operation schedules, then single building or facility optimization is achieved, but the system cannot immediately activate multiple energy related systems under advantageous scenarios when demand response signals are received
Solution Approach 1:
The system pre-calculates and stores multiple candidate operation schedules for coordinating various energy related systems (heat storage devices, chillers, air conditioners, etc.) under different scenarios. When demand response signals are received, the system can immediately activate appropriate pre-calculated schedules, enabling fast multi-system coordination without lengthy real-time calculations.
Solution Approach 2:
The system creates operation schedules that can be applied to multiple different energy related systems and various demand response scenarios. The pre-calculated schedules serve multiple functions: they optimize single facilities, coordinate multiple systems, and adapt to different demand response signal types, providing universal applicability across diverse situations.
Data Source
AI summary
According to an embodiment, server includes estimator, condition setter, calculator, receiver, and controller. Estimator estimates an energy demand in building where electrical apparatuses are equipped based on apparatus data. Condition setter sets energy consumption suppression conditions. Calculator calculates operation schedule of apparatuses which can optimize an energy balance in building based on the demand and condition. Receiver receives DR signal including energy consumption suppression condition. Controller controls the apparatuses based on operation schedule calculated based on the condition corresponding to that included in the DR signal.