Dynamic Energy Converter Control for Cost-Optimal Heating And Cooling
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Solution Overview
Problem
Current heating systems operate energy converters in an ON/OFF mode, leading to inefficient energy use and uneven wear on machines, as they prioritize certain generators over others, resulting in suboptimal efficiency and increased costs.
Innovation Solution
A method for controlling multiple energy converters to select the most favorable combination of heating or cooling outputs based on current electricity prices and weather forecasts, using a system manager that queries power requirements, determines available offerings, and adjusts setpoints to optimize energy usage and reduce wear on generators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If energy converters are operated in ON/OFF mode with fixed output, then the system is simple to operate, but energy efficiency deteriorates and wear on machines increases
Solution Approach 1:
The patent implements dynamic operation of energy converters by continuously adjusting the output power of individual converters based on real-time system requirements and efficiency characteristics. Instead of fixed ON/OFF modes, the system dynamically modulates converter output to match actual heating or cooling demands, thereby improving energy efficiency while maintaining operational simplicity through automated control.
Solution Approach 2:
The system changes operating parameters by adjusting the output power levels of energy converters continuously rather than in fixed steps. The control system monitors system state and modifies converter parameters (power output, operational status) in real-time to optimize energy efficiency, allowing smooth transitions between different operating conditions without manual intervention.
2Device complexity
If certain machines are switched on preferentially, then the control system is simple, but uneven wear on machines occurs and reliability deteriorates
Solution Approach 1:
The patent incorporates feedback mechanisms that monitor the operational status, efficiency characteristics, and wear indicators of multiple energy converters. The control system uses this feedback information to dynamically adjust the distribution of load among converters, ensuring more uniform utilization and wear patterns. This automated feedback-based load balancing improves reliability while keeping control complexity manageable through algorithmic decision-making.
Solution Approach 2:
The system dynamically redistributes operational load among energy converters based on real-time conditions and historical performance data. Rather than statically preferring certain machines, the control system adaptively adjusts which converters operate and at what power levels, promoting more equitable wear distribution and enhancing overall system reliability through dynamic load management.
3Power
If maximum output is provided when switched on, then power availability is ensured, but energy consumption increases and cost optimality deteriorates
Solution Approach 1:
The patent applies parameter changes by continuously adjusting the output power levels of energy converters to match actual system requirements. Instead of operating at maximum output when switched on, the system dynamically modulates power levels based on real-time heating or cooling demands and efficiency characteristics, thereby ensuring adequate power availability while minimizing electrical power consumption and operational costs.
Solution Approach 2:
The system implements partial action by operating energy converters at optimized power levels rather than always at maximum capacity. The control algorithm determines the appropriate degree of converter activation based on actual needs, avoiding excessive power generation that would waste energy and increase costs, while still ensuring sufficient power availability to meet system requirements.
4Loss of energy
If weather forecasts and flexible energy tariffs are used for prediction, then cost optimality improves, but system complexity and measurement precision requirements increase
Solution Approach 1:
The patent applies preliminary action by using weather forecasts and flexible energy tariff information to predict future system requirements and cost conditions. The control system processes this forecast data in advance to pre-optimize the operational schedule of energy converters, anticipating periods of low cost or favorable weather conditions and planning converter operation accordingly, thereby reducing operational costs while managing the complexity of forecast data processing through predictive algorithms.
Data Source
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AI summary
The method involves determining a heating or cooling power demand for distribution system. The heat-or cold offerings for energy converter are determined. The favorable possible combination (K) for heating or cooling power demand of the distribution system is selected from heat-or cold offerings of energy converter. The energy converter is adjusted depending on the selected offerings and desired value of the energy converter according to the combination.