Refrigeration Power Flexibility Estimation for Smart-Grid Control
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Solution Overview
Problem
Existing methods for managing refrigeration systems in smart-grids are inadequate as they primarily focus on reducing energy losses due to ripples, failing to provide improved power consumption information beyond nominal and zero values, which limits their flexibility in responding to short-term power fluctuations.
Innovation Solution
A method for operating refrigeration systems that estimates and communicates power consumption parameters such as maximum and minimum power consumption, and change in power consumption to a smart-grid setup, allowing for more precise control and flexibility in power management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If existing methods for managing refrigeration systems in smart-grids are used, then energy losses due to ripples are reduced, but power consumption information flexibility is limited
Solution Approach 1:
The patent changes the parameters of power consumption information from simple nominal and zero values to a comprehensive set including maximum power consumption, minimum power consumption, and change in power consumption. This allows the refrigeration system to provide flexible power management information to the smart-grid while maintaining energy efficiency.
2Device complexity
If nominal and zero power consumption values are provided to smart-grid, then communication is simplified, but flexibility in responding to short-term power fluctuations is limited
Solution Approach 1:
The patent introduces dynamic power consumption parameters that can change based on system state and grid requirements. The maximum, minimum, and change in power consumption values are dynamically determined to reflect the refrigeration system's actual capabilities, enabling flexible response to short-term power fluctuations while maintaining clear communication protocols.
3Adaptability or versatility
If detailed power consumption parameters are communicated to smart-grid, then power control flexibility is improved, but information processing complexity increases
Solution Approach 1:
The patent segments power consumption information into distinct, manageable parameters: maximum power consumption, minimum power consumption, and change in power consumption. Each parameter serves a specific function in power control, making the information processing systematic and reducing overall complexity despite the increased detail.
Data Source
AI summary
The invention relates to a method of operating at least one distributed energy resource comprising a refrigeration system (1) with a number of cooling entities, whereina power consumption information is communicated to a smart-grid setup (SG). According to the invention the method comprises the steps of: requesting (S0) a power consumption information from the refrigeration system; transmitting (S1) the power consumption information from the refrigeration system (1), wherein a total amount of power consumption (Pmin, Pmax) of the refrigeration system (1) is provided; wherein: a cooling capacity (dQ/dt_i) of at least one cooling entity is determined wherein an entity operation condition (CE) of the cooling entity (E1, E2) is taken into account (D1); a power consumption (W_i) of at least one cooling entity (E1, E2) is determined from the cooling capacity (dQ/dt_i) wherein a performance estimation (COP) of a refrigeration cycle for the cooling entity (E1, E2) is taken into account (D2); providing (D3) the total amount of power consumption (Pmin, Pmax) as a sum of power consumptions (W_i) of at least the one cooling entity of the number of cooling entities (E1, E2), in particular as a sum of relevant power consumptions of the number of cooling entities (E1, E2); receiving (S2) at the refrigeration system (1) a power reference (Wref) from the smart-grid setup (SG). The method presented enables power control of a centralized refrigeration system in a smart-grid setup where an aggregator provides the power reference. In addition, the method also enables the refrigeration system to improve determining flexibility margins beyond absolute max./min values of nominal and zero.