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Low-income households (LIH), exposed to the uncertain modern grid, bear greater energy burdens and face inequitable access to reliable power compared to high-income households (HIH). This paper proposes a two-stage stochastic community-based microgrid planning (CMP) framework to boost energy justice within the system. To reduce the negative impact of income levels, a weighted energy cost model for households within the microgrid (MG) is designed. To address the multisource uncertainty during the operation period, a two-stage stochastic framework is developed. Moreover, to assess the proposed method, the unbalanced IEEE 123 node system is employed and modified as an isolated MG. The analysis reveals the proposed model can achieve a risk-averse solution while economic optimality is guaranteed. Additionally, the designed weighted method improves the LIH’s impact rate to 67.95% and decreases the total planning cost by 22.43%. 

Low-income households (LIH), exposed to the uncertain modern grid, bear greater energy burdens and face inequitable access to reliable power compared to high-income households (HIH). This paper proposes a two-stage stochastic community-based microgrid planning (CMP) framework to boost energy justice within the system. To reduce the negative impact of income levels, a weighted energy cost model for households within the microgrid (MG) is designed. To address the multisource uncertainty during the operation period, a two-stage stochastic framework is developed. Moreover, to assess the proposed method, the unbalanced IEEE 123 node system is employed and modified as an isolated MG. The analysis reveals the proposed model can achieve a risk-averse solution while economic optimality is guaranteed. Additionally, the designed weighted method improves the LIH’s impact rate to 67.95% and decreases the total planning cost by 22.43%.