研究目的
To develop a unified net-load balancing framework that performs both load and solar curtailment in smart grids with high PV penetration, addressing the NP-hard problem of discrete curtailment values with bounded approximation algorithms.
研究成果
The developed net-load balancing framework and algorithms effectively address the NP-hard problem of discrete curtailment in smart grids with high PV penetration, providing near-optimal solutions within tight timing constraints. The algorithms ensure practical constraints like fairness and network capacity limits are met, with theoretical guarantees on performance.
研究不足
The study assumes perfect knowledge of future load and generation without prediction errors, and it does not address uncertainties in forecasting. The framework's direct control assumption may not hold for citywide distribution grids.
1:Experimental Design and Method Selection:
The study leverages recent technological developments for selective PV module connection to the grid, developing algorithms for net-load balancing.
2:Sample Selection and Data Sources:
Utilizes historical load, generation, and curtailment prediction data from a university campus microgrid and simulated solar curtailment data based on solar radiance data for Los Angeles County.
3:List of Experimental Equipment and Materials:
Includes PV installations with micro-inverters for discrete curtailment, demand response enabled nodes, and MATLAB for algorithm implementation.
4:Experimental Procedures and Operational Workflow:
The framework identifies curtailment horizons, calculates curtailment targets, and applies approximation algorithms for strategy selection.
5:Data Analysis Methods:
Theoretical analysis and practical evaluations compare algorithm performance against optimal solutions, assessing cost, fairness, and constraint violations.
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