Heating Network Thermal Inertia for Grid Flexibility
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Solution Overview
Problem
The integration of renewable energy sources like wind and photovoltaic power into the power grid is hindered by their unpredictability and volatility, leading to challenges in maintaining safe and stable grid operations, while conventional thermal power generation is decreasing, necessitating the development of new controllable resources to enhance grid flexibility.
Innovation Solution
A method for calculating control parameters of a heating supply power in a heating network is developed, involving the establishment of a thermal dynamic simulation model to simulate upward and downward adjustments in heating supply power, allowing for the determination of adjustable capability models that can be used to flexibly manage heating supply power in response to grid demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If renewable energy (wind and photovoltaic) is integrated into the power grid, then energy supply diversity is improved, but grid stability deteriorates due to randomness and volatility
Solution Approach 1:
The heating network acts as an intermediary system between the power grid and renewable energy sources. By coupling the heating network with the power grid through electric-heating coupled multi-energy flow systems, the patent creates a buffer that absorbs the volatility of renewable energy. The thermal storage capacity of the heating network mediates the mismatch between variable renewable energy supply and stable grid requirements, allowing renewable energy to be integrated without directly impacting grid stability.
Solution Approach 2:
The patent changes the operational parameters of the heating network to enable flexibility in power consumption. By adjusting parameters such as heating supply temperature, flow rate, and thermal storage levels, the system can dynamically respond to renewable energy availability. This parameter adjustment allows the heating network to absorb excess renewable energy when available and maintain stable operation when renewable input varies, thus resolving the contradiction between energy diversity and grid stability.
2Adaptability or versatility
If heating supply power is adjusted to provide flexibility for power grid operation, then grid flexibility is improved, but heating load satisfaction may deteriorate
Solution Approach 1:
The patent implements preliminary action by pre-charging thermal storage facilities in the heating network before periods of high renewable energy availability or grid flexibility needs. By storing thermal energy in advance during periods of excess supply or low demand, the system can later adjust heating supply power to support grid flexibility without compromising heating load satisfaction. This advance preparation ensures that heating requirements are met even when power adjustments are necessary.
Solution Approach 2:
The patent introduces dynamic control mechanisms that allow the heating network to adapt its operation in real-time based on grid conditions and heating demands. Through dynamic adjustment of supply parameters and utilization of thermal inertia, the system can temporarily modify heating supply to provide grid flexibility while automatically recovering to satisfy heating loads. The dynamic nature of the control system ensures that heating requirements are ultimately met while providing the necessary flexibility to the power grid.
3Object-generated harmful factors
If conventional thermal power generation is decreased, then environmental performance is improved, but controllable resources for grid operation deteriorate
Solution Approach 1:
The patent applies multi-functionality by enabling the heating network to serve dual purposes: meeting heating demands and providing controllable resources for power grid operation. The heating network becomes a versatile system that can adjust its power consumption to support grid flexibility, renewable energy integration, and stability maintenance. This multi-functional role compensates for the reduction in conventional thermal power generation by creating new controllable resources within the heating sector.
Solution Approach 2:
The patent implements feedback mechanisms that allow the heating network to respond to grid conditions and adjust its operation accordingly. Through real-time monitoring and control, the system receives feedback on grid flexibility needs, renewable energy availability, and heating demand patterns. This feedback enables the heating network to dynamically adjust its power consumption to provide controllable resources, replacing the role previously filled by conventional thermal power generation while maintaining environmental benefits.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the flexibility of power grid operations by accurately describing heating network flexibility through thermal dynamic simulation, providing a standardized and concise model for adjustable heating supply power parameters, which can be applied to online operation of electric-heating coupled multi-energy flow systems to mitigate the impact of renewable energy uncertainty.
Implementation Method 1
The heating network has a great thermal inertia, which makes it possible to change the heating supply power within a certain period of time with a small impact on the heating load
Data Source
AI summary
A method for calculating control parameters of a heating supply power of a heating network, pertaining to the technical field of operation and control of a power system containing multiple types of energy. The method: establishing a heating network simulation model that simulates a thermal dynamic process of the heating network; starting an upward simulation based on the heating network simulation model to obtain first control parameters from a set of up adjustment amounts; starting a downward simulation based on the heating network simulation model, to obtain second control parameters from a set of down adjustment amounts.