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Active distribution networks increasingly rely on stochastic optimization to manage uncertainties arising from renewable generation, flexible demand, distributed storage, electric vehicles, and local energy markets. These uncertainties affect voltage quality, congestion, operational cost, reliability, and the value of flexibility. This systematic review categorizes and evaluates uncertainty-aware stochastic optimization techniques for demand response, DER coordination, and flexibility provision in active distribution networks. It focuses on methodological transparency, thematic synthesis, and identification of research gaps. A PRISMA-guided systematic review of 31 peer-reviewed journal articles published from 2017 to 2023 was conducted. A structured search, screening, eligibility assessment, and data extraction process was used to organize the evidence. The review maps dominant stochastic frameworks, including two-stage stochastic programming, chance-constrained optimization, robust-stochastic formulations, and distributionally robust optimization. Five synthesis tables are used across the full manuscript to summarize study selection, article characteristics, method taxonomies, application mappings, and research gaps. Stochastic optimization supports secure and efficient operation of active distribution grids, but important gaps remain in scalability, real-world validation, interoperability, and regulatory integration. The review outlines an agenda for more adaptive, transparent, and implementation-ready optimization methods.

Recent advances in residential automation technologies and the widespread adoption of distributed energy resources (DERs) have dramatically amplified the need for sophisticated energy management strategies that harmonize operational reliability with cost-effectiveness in smart residential microgrids (SRMG). When smart homes fail to coordinate effectively or exchange energy, irregularities in the SRMG load profile emerge, potentially breaching critical technical thresholds. This work presents a fully decentralized architecture for SRMG that accommodates heterogeneous smart homes that actively participate in peer-to-peer (P2P) energy trading. This architecture targets the simultaneous minimization of load profile variability across the microgrid, reduction of household electricity bills, and preservation of occupant comfort levels enabled by P2P exchanges. At the household level, the home energy management (HEM) system is engineered to curtail overall energy expenditure by leveraging available DER capacity to enable P2P transactions and maintain continuous bidirectional links with the SRMG operator (SRMGO). Real-time, ongoing data interchange between SRMGO and HEM units proves indispensable for achieving superior load-profile smoothing in a decentralized setting. The proposed mechanism achieves roughly a 4.25% decrease in load-profile deviations while keeping energy costs unchanged, thereby confirming that decentralized P2P energy exchanges markedly improve both microgrid load balancing and household expenditure stability. Simulations conducted with the general algebraic modeling system (GAMS) software confirm that incorporating P2P energy mechanisms within a decentralized structure satisfactorily meets the SRMG’s technical constraints and the monetary priorities of participating smart homes.