Grid Voltage Stabilizer Control for High-Variability Loads
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Solution Overview
Problem
Electric power systems face challenges in accommodating high variation distributed generation and loads, such as photovoltaic generation, distributed storage, and electric vehicle charging, which affect voltage reliability and efficiency.
Innovation Solution
A method and system utilizing advanced metering infrastructure (AMI) data analysis to optimize voltage control through independent voltage control devices like load tap changing transformers, voltage regulators, and capacitor banks, building piecewise linear regression models to manage voltage levels and respond to high variability loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If voltage is optimized solely for efficiency, then energy losses are minimized, but the system becomes incompatible with high variation distributed generation and loads
Solution Approach 1:
The system dynamically adjusts voltage levels based on real-time conditions. The voltage control device changes voltage setpoints in response to varying load conditions and distributed generation output, transitioning between efficiency-optimized voltage levels and compatibility-optimized voltage levels. This dynamic adaptation resolves the contradiction by making the voltage level flexible rather than fixed.
Solution Approach 2:
The system changes the voltage parameter based on operational mode. During normal operation, voltage is optimized for efficiency; during high variation events, voltage is adjusted to maintain compatibility with distributed generation and loads. The controller monitors system conditions and modifies the voltage parameter accordingly, allowing the system to achieve both efficiency and adaptability at different times.
2Adaptability or versatility
If the system accommodates high variation loads, then adaptability is improved, but voltage reliability and efficiency deteriorate
Solution Approach 1:
The system detects high variation events early and takes preliminary action by adjusting voltage levels before voltage reliability deteriorates. The controller monitors for conditions indicating high variation loads or distributed generation changes and proactively modifies voltage setpoints to maintain stability, preventing voltage excursions before they occur.
Solution Approach 2:
The system uses feedback from voltage measurements and load conditions to continuously adjust voltage levels. The controller receives feedback about actual voltage levels and load conditions, comparing them against target values, and makes real-time adjustments to maintain voltage reliability while accommodating high variation loads.
3Loss of energy
If voltage control devices are used to optimize efficiency, then energy losses are reduced, but the complexity of the control system increases
Solution Approach 1:
The control system is segmented into distinct operational modes (efficiency mode and compatibility mode) with different voltage optimization strategies. This segmentation allows the system to apply simpler control logic for each mode rather than attempting to optimize all parameters simultaneously, reducing overall control complexity while maintaining energy efficiency benefits.
Data Source
AI summary
A method, apparatus, system and computer program is provided for controlling an electric power system, including implementation of a voltage control and conservation (VCC) system used to optimally control the independent voltage and capacitor banks using a linear optimization methodology to minimize the losses in the EEDCS and the EUS. An energy validation process system (EVP) is provided which is used to document the savings of the VCC and an EPP is used to optimize improvements to the EEDCS for continuously improving the energy losses in the EEDS. The EVP system measures the improvement in the EEDS a result of operating the VCC system in the “ON” state determining the level of energy conservation achieved by the VCC system. In addition the VCC system monitors pattern recognition events and compares them to the report-by-exception data to detect HVL events. If one is detected the VCC optimizes the capacity of the EEDS to respond to the HVL events by centering the piecewise linear solution maximizing the ability of the EDDS to absorb the HVL event. The VCC stabilizer function integrates voltage data from AMI meters and assess the state of the grid and initiates appropriate voltage control actions to hedge against predictable voltage risks.