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<p>A steady balance between power generation and load demand presents a considerable challenge in an islanded microgrid (IMG). This paper presents an IMG that integrates two renewable energy sources: solar and wind generators. In the absence of upgrid regulation, the variation in load substantially affects the voltage and frequency variations in the IMG. This difficulty can be mitigated by implementing a centrally regulated strategic load management strategy. The proposed approach initiates with systematic classification, categorization, and prioritization of loads to facilitate more efficient load curtailment by the central regulator. A multi-objective optimization approach is employed to maximize economic efficiency and minimize client discomfort. The method incorporates an incentive-based demand response along with load shedding. Further, the uncertainties associated with solar and wind generators are addressed using Hong’s <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\((2m+1)\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">(</mo> <mn>2</mn> <mi>m</mi> <mo>+</mo> <mn>1</mn> <mo stretchy="false">)</mo> </mrow> </math></EquationSource> </InlineEquation> point estimation method. The proposed framework is executed in a 38-bus islanded microgrid. The effectiveness of the proposed framework is assessed via reliability evaluation, demonstrating its capacity to reduce service disruptions and associated operating expenses.</p>

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Stochastic prioritized load shedding to improve reliability and servility of multi-source islanded microgrid considering demand response and uncertainty modeling

  • 期刊论文

  • 发表日期：

    2026年8月4日

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  • Pujashree Dash,
  • Debapriya Das

摘要

A steady balance between power generation and load demand presents a considerable challenge in an islanded microgrid (IMG). This paper presents an IMG that integrates two renewable energy sources: solar and wind generators. In the absence of upgrid regulation, the variation in load substantially affects the voltage and frequency variations in the IMG. This difficulty can be mitigated by implementing a centrally regulated strategic load management strategy. The proposed approach initiates with systematic classification, categorization, and prioritization of loads to facilitate more efficient load curtailment by the central regulator. A multi-objective optimization approach is employed to maximize economic efficiency and minimize client discomfort. The method incorporates an incentive-based demand response along with load shedding. Further, the uncertainties associated with solar and wind generators are addressed using Hong’s \((2m+1)\) ( 2 m + 1 ) point estimation method. The proposed framework is executed in a 38-bus islanded microgrid. The effectiveness of the proposed framework is assessed via reliability evaluation, demonstrating its capacity to reduce service disruptions and associated operating expenses.