Optimizing Electrical Distribution Network Settings
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Solution Overview
Problem
Optimizing electrical distribution networks to minimize power loss and reduce voltage while managing voltage and capacitance effectively, especially in radial and interconnected networks, is challenging due to the non-linear nature of the problem and the need for discrete control variables.
Innovation Solution
A system that integrates data modeling, forecasting, and optimization using non-linear programming and heuristic techniques to determine settings for capacitor banks and voltage regulators, employing a least squares model of load flow analysis to iteratively adjust settings and minimize power loss and voltage violations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional power flow analysis methods are used, then complete voltage angle and magnitude information can be obtained, but the computational complexity increases due to the non-linear nature of the problem
Solution Approach 1:
The patent transforms the non-linear power flow equations into a linear system by changing the mathematical parameters and representation. Specifically, it uses a linearized model that reformulates the complex non-linear relationships into linear equations that can be solved more efficiently while maintaining acceptable accuracy for distribution systems.
Solution Approach 2:
The patent replaces the traditional iterative numerical methods (mechanical/computational approach) with a direct linear solution method. By substituting the iterative non-linear solver with a linear algebra-based approach, the computational complexity is reduced while still obtaining the necessary voltage information.
2Ease of operation
If discrete control variables are used for capacitor banks and voltage regulators, then realistic control settings can be determined, but the optimization problem becomes more difficult to solve
Solution Approach 1:
The patent segments the optimization problem by separating the continuous power flow calculations from the discrete control variable selection. The linearized power flow model provides a framework that allows discrete capacitor bank switching and voltage regulator tap settings to be optimized independently through the objective function, rather than dealing with the full non-linear mixed-integer problem simultaneously.
Solution Approach 2:
The patent changes the mathematical formulation to accommodate discrete variables by incorporating integer constraints into the linear optimization framework. This allows the use of mixed-integer linear programming (MILP) techniques that can handle discrete control settings while maintaining the computational advantages of linearity.
3Productivity
If optimization is performed to minimize power loss and reduce voltage, then operational efficiency improves, but the system complexity increases
Solution Approach 1:
The patent creates a universal optimization framework that simultaneously handles multiple objectives (power loss minimization, voltage regulation, capacitor bank control, and voltage regulator control) within a single linear programming model. This multi-functional approach consolidates what would otherwise require separate analysis and control systems into one unified framework.
Solution Approach 2:
The linearized power flow model acts as an intermediary that connects the control variables (capacitor banks, voltage regulators) with the performance objectives (power loss, voltage). This intermediary linear model simplifies the relationship between controls and outcomes, making the overall system more manageable despite the multiple objectives being optimized.
Data Source
AI summary
Techniques to determine settings for an electrical distribution network are described. Some embodiments are particularly directed to techniques to determine settings for an electrical distribution network using power flow heuristics. In one embodiment, for example, an apparatus may comprise a model reception component, a forecast component, and an optimization component. The model reception component may be operative to receive a model of an electrical distribution network having multiple capacitor banks and multiple voltage regulators, each of the multiple capacitor banks represented in the model by a model capacitor bank, each of the multiple voltage regulators represented in the model by a model voltage regulator, the electrical distribution network having a radial layout in which power flows from a source to multiple nodes in which each node is associated with one voltage regulator. The forecast reception component may be operative to receive a forecast for demand on the electrical distribution network. The optimization component may be operative to receive the model capacitor banks and model voltage regulators and determine one or more settings for the multiple capacitor banks and multiple voltage regulators that allow for providing power within predetermined limits while reducing power loss as compared to a power loss of the existing settings or reducing power usage as compared to a power usage of the existing settings, the one or more settings for the multiple voltage regulators determined according to a heuristic in which potential settings are iteratively determined for each of the model voltage regulators based on a least squares model of load flow analysis. Other embodiments are described and claimed.