Incorporating Social Acceptance into Sustainable Power System Planning: A Systematic Analysis of Modelling Approaches and Empirical Outcomes

The transition to low-carbon energy systems requires large-scale expansion and spatial reconfiguration of electricity infrastructure. While power system planning models provide detailed techno-economic pathways for achieving decarbonization targets, their real-world implementation is frequently constrained by social acceptance. This study identifies a structural “Modelling Gap”—defined as the systematic divergence between how social factors are represented in optimization frameworks and how they manifest as institutional constraints in realized infrastructure deployment. Based on a systematic review of 76 research articles—comprising 43 modelling studies, 32 empirical studies, and 1 mixed contribution—this paper develops a five-pillar taxonomy to analyze how qualitative social variables are translated into formal decision-making constraints. The analysis reveals a fundamental divergence between modelling and empirical approaches. In optimization models, social acceptance is typically represented as a parametric variable—such as cost penalties, spatial exclusions, or weighted preferences—implying that social resistance can be mitigated through marginal adjustments. In contrast, empirical evidence shows that social friction often operates through institutional mechanisms, including permitting decisions, legal rulings, and administrative processes, which function as categorical constraints on infrastructure deployment. The results further demonstrate that current models systematically underrepresent key dimensions of implementation risk. In particular, temporal delays, regulatory dynamics, and project abandonment are only partially captured in existing frameworks, despite being major drivers of real-world outcomes. This mismatch leads to planning outputs that may be technically optimal but operationally infeasible. By identifying the structural limitations of current modelling approaches, this study contributes a conceptual foundation for integrating social acceptance into sustainable power system planning. The findings suggest that improving the alignment between optimization models and institutional realities is critical for developing sustainable energy system pathways that are not only cost-efficient, but also socially and legally implementable.