Distribution Network Planning for Renewable Uncertainty Resilience
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Solution Overview
Problem
Existing power distribution systems struggle to address the uncertainty from renewable distributed generations during emergency operation states such as blackouts caused by extreme weather events, which requires more accurate methods for resilient distribution network planning.
Innovation Solution
A comprehensive emergency response planning system is developed, incorporating dispatchable generation resources, topology reconfigurations through switchable devices, and a planning model that uses distributionally robust joint chance-constrained methods to design resilient power distribution networks. This model includes a decision-dependent moment-based ambiguity set to accurately describe renewable uncertainty, cast as a mixed-integer second-order conic programming problem.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If renewable distributed generations are integrated into the power distribution network, then clean renewable energy penetration is maximized and services such as reactive power support are provided, but uncertainty from renewable generation makes it difficult to guarantee power system operation during emergency states
Solution Approach 1:
The patent applies preliminary action by pre-positioning dispatchable diesel generators and battery energy storage systems at strategically selected locations within the distribution network before emergencies occur. The resilience enhancement planning model determines optimal placement and sizing of these resources in advance, so they are ready to immediately compensate for renewable generation uncertainty during blackouts or emergency states, thus maintaining reliability while enabling renewable integration
Solution Approach 2:
The patent implements beforehand cushioning by incorporating contingency reserves through dispatchable generators and energy storage systems that serve as a buffer against renewable generation uncertainty. The planning model ensures these cushioning resources are sized and positioned to handle worst-case scenarios of renewable output deviation, providing a safety margin that maintains power system reliability during emergencies while allowing high renewable penetration
2Reliability
If existing optimization methods are used for power system operation under normal conditions, then uncertainty impacts are modeled and mitigated, but requirements arising from emergency operation states such as blackouts are not addressed
Solution Approach 1:
The patent applies segmentation by dividing the power system operation into distinct normal and emergency states, with separate operational modes and control strategies for each. The resilience enhancement planning model specifically addresses emergency state requirements by pre-configuring resources and constraints for blackout scenarios, while maintaining separate normal operation optimization, thus managing complexity through state-based segmentation
Solution Approach 2:
The patent implements dynamics by creating a flexible planning model that adapts to different operational states. The mixed-integer second-order conic programming formulation dynamically adjusts resource allocation and operational constraints based on whether the system is in normal operation or emergency blackout states, allowing the model to handle both scenarios effectively without being overly complex in any single mode
3Reliability
If a comprehensive emergency response planning system is developed with dispatchable generation resources and topology reconfigurations, then resilience is enhanced and disruption is minimized, but system complexity and investment costs increase
Solution Approach 1:
The patent applies local quality by implementing resilience enhancement measures selectively at specific locations within the distribution network rather than uniformly across the entire system. The planning model identifies critical areas and optimally places dispatchable generators and energy storage systems only where they provide the most benefit, thus enhancing resilience while minimizing overall system complexity and investment costs
Solution Approach 2:
The patent implements universality by designing a multi-functional resilience enhancement system where dispatchable diesel generators and battery energy storage systems can serve multiple purposes: providing emergency power during blackouts, supporting renewable integration, maintaining voltage levels, and enabling topology reconfigurations. This multi-functionality reduces the need for dedicated resources for each function, thereby limiting complexity increases while achieving comprehensive resilience
Data Source
AI summary
Disclosed a decision-dependent chance-constrained optimal model for enhancing resilience of power distribution system under renewable generation uncertainty through strategically setting-up and activating dispatchable diesel generators, renewable distributed generations, battery energy storage systems, and switchable devices. By incorporating the information of decision variables, a moment-based ambiguity set is employed to depict the uncertainty arising from renewable distributed generators. By leveraging convex approximations to handle the considered joint chance constraints, the disclosed model is transformed into a tractable mixed-integer second-order conic programming problem to be solved.