Regulatory policies are key drivers of power-sector decarbonization, influencing investment decisions in renewable generation and demand-side flexibility. Common approaches such as carbon pricing or uniform investment incentives, however, are typically designed without accounting for network effects, assuming that each unit of renewable capacity or flexibility contributes equally to cost and emission reductions regardless of location. In reality, transmission constraints and spatial heterogeneity can substantially alter these impacts, leading to curtailments and diminished policy effectiveness. In this paper, we investigate how network constraints shape the fundamental trade-off between economic cost and carbon emissions of a power system. We quantify this trade-off by computing the cost-emissions Pareto front. We then analyze the front’s attractiveness for different levels of renewables and flexibility penetration as well as different spatial distributions across locations. The results show that copper-plate assumptions can produce misleading fronts, while network-aware modeling reveals saturation effects and spatial asymmetries critical for efficient policy design. These findings highlight the need for regulators to adopt network-aware planning frameworks when designing incentives for renewable and flexibility investments.