Coordinated Planning of Source–Grid–Load–Storage Systems Considering Dual-Dimensional Evaluation of Load Carbon Emission Characteristics and Regulation Potential

Abstract

Driven by “dual-carbon” targets, the large-scale integration of high-penetration distributed generation (DG) exacerbates peak-shaving pressures and supply–demand mismatches in regional power grids. Conventional planning methods often rely on spatial node homogeneity assumptions, failing to exploit the collaborative potential of flexible demand-side resources. To address this limitation, this paper proposes a coordinated source–grid–load–storage planning method guided by a “load carbon emission characteristics–regulation potential” dual-dimensional assessment. First, demand-side nodal attributes are quantitatively evaluated across two dimensions. A hybrid weighting framework fusing the Fuzzy Analytic Hierarchy Process (FAHP) and an improved CRITIC method is introduced to identify four typical characterized nodal clusters, generating a spatial priority list for resource allocation. Second, targeting the minimization of the full life-cycle net present value cost, a Mixed Integer Quadratic Programming (MIQP) model for coordinated source–grid–load–storage planning is constructed. By embedding the priority list into spatial placement decisions, DGs and energy storage systems are strategically guided to preferentially aggregate at high marginal-value nodes. Finally, simulations on an IEEE 30-node regional power grid demonstrate that the proposed method enhances peak-shaving and valley-filling capabilities by 33.1% and 39.83%, respectively, while elevating the comprehensive system load factor from 0.84 to 0.86. These numerical results validate the superiority of the proposed framework in preventing spatial resource misallocation and achieving a profound synergy between low-carbon performance and global economic efficiency.