Energy Management Control for Mixed Asset Regulation Pools
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Solution Overview
Problem
Existing energy production systems face challenges in dynamically regulating a mix of different types of generating assets, including fuel-based and renewable assets, due to their varying operational characteristics, which complicates the management of energy and reserve markets.
Innovation Solution
An energy management system (EMS) that calculates an 'effective control mode' for each asset based on its basic control mode, reserve call state, and actual process state, allowing for real-time adjustments to ensure compliance with energy and reserve market demands, including both fuel-based and renewable assets in a single regulation pool.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple different types of generating assets are included in a regulation pool, then the diversity and flexibility of the energy production system is improved, but the complexity of controlling and managing these assets increases
Solution Approach 1:
The control system segments the regulation pool into multiple control groups based on asset type and operational characteristics. Each control group can be managed with tailored control strategies, reducing the overall complexity while maintaining the benefits of asset diversity. The system divides the heterogeneous asset portfolio into manageable segments that can be controlled independently yet coordinated centrally.
Solution Approach 2:
The control system dynamically adjusts control parameters and strategies based on real-time asset states, market conditions, and regulatory requirements. This dynamic adaptation allows the system to handle diverse asset types efficiently by automatically optimizing control approaches for each asset class without requiring static complex control structures.
2Reliability
If real-time control adjustments are made for each asset based on multiple parameters, then the regulatory compliance and market participation are improved, but the computational complexity and data processing requirements increase
Solution Approach 1:
The control system performs preliminary calculations and pre-positioning of control parameters based on forecasted market conditions and asset availability. By preparing control strategies in advance and pre-calculating optimal operating points, the system reduces real-time computational burden while ensuring regulatory compliance and rapid response capability.
Solution Approach 2:
The system implements continuous feedback loops that monitor asset performance, market conditions, and regulatory requirements. This feedback mechanism enables automated real-time adjustments to control parameters, reducing the need for complex manual calculations and ensuring ongoing compliance while simplifying the computational process through iterative optimization.
Data Source
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AI summary
Embodiments provide for controlling a power generation system that includes a plurality of power generating assets; and an energy management system including a controller in communication with the assets and configured to control operation of the assets. The controller is operative to assign the assets to a regulation pool; determine an effective control mode for each asset; and control the assets based on the determined effective control mode of each asset. The effective control mode for each asset is calculated based upon an asset pool control mode. Numerous additional aspects are disclosed.