Demand-Side Resource Scheduling for Power Shortage Cost Balancing
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Solution Overview
Problem
The integration of high variability and uncertainty in renewable energy sources in power systems leads to significant power imbalances, necessitating costly purchases from other grids and inadequate reserve capacity, with existing demand-side flexible resource studies lacking effective dispatching mechanisms.
Innovation Solution
A scheduling method that classifies demand-side resources into Class I and Class II loads, constructs day-ahead-and-intraday optimization mechanisms, models these resources, aggregates their regulating abilities, and optimizes scheduling to balance power supply and demand, considering the uncertainty of distributed resources like air conditioning and residential water heaters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If demand-side flexible resources are utilized for power scheduling, then the cost of purchasing electricity from external grids is reduced, but the complexity of resource classification and optimization scheduling increases
Solution Approach 1:
The patent segments demand-side flexible resources into two distinct categories: Class I loads (industrial loads with strong adjustability) and Class II loads (residential and commercial loads with weak adjustability). This segmentation enables differentiated scheduling strategies for each class, simplifying the overall optimization problem while effectively reducing electricity purchase costs through targeted demand response programs.
2Measurement precision
If distributed resources with uncertain adjustability are included in scheduling, then the accuracy of power balance prediction improves, but the difficulty of modeling and aggregation increases
Solution Approach 1:
The patent applies local quality by assigning different modeling approaches and aggregation methods tailored to each resource class. Class I loads receive detailed individual modeling with known adjustability characteristics, while Class II loads use statistical aggregation methods that account for their uncertain and weak adjustability. This localized approach improves power balance prediction accuracy without overwhelming complexity.
3Reliability
If system reserve capacity is increased to address power shortages, then the reliability of power supply is improved, but the cost of maintaining reserve capacity increases continuously
Solution Approach 1:
The patent implements self-service by enabling demand-side resources to automatically adjust their consumption patterns in response to power shortages. Class I industrial loads can autonomously reduce demand through optimized scheduling, while Class II residential and commercial loads participate through aggregated demand response programs. This self-adjustment mechanism provides reliable power supply without requiring continuous expensive reserve capacity maintenance.
Data Source
AI summary
The present disclosure provides a scheduling method, system, electronic device, and medium for addressing power shortages, comprising: step S1: classifying demand-side flexible resources; step S2: constructing a day-ahead-and-intraday optimization scheduling mechanism for demand-side resources to participate in system regulating; step S3: modeling demand-side flexible resources; step S4: aggregating regulating abilities of the Class II load; and step S5: constructing an intraday optimization scheduling model based on a total cost of purchasing electricity from other power grids and a total cost of dispatching load-side resources. The present disclosure classifies demand-side resources and constructs an optimization scheduling mechanism, effectively dispatching different types of regulating resources to participate in optimization scheduling, balancing cost of purchasing electricity from outside the province and dispatching resources within the province, considering uncertainty of adjustability of distributed resources making the model more accurate and practical, thereby reducing cost of scheduling during power shortage.