Determination of Hosting Capacity for Combined Heat and Power and Photovoltaic Systems in Metropolitan Areas Using Quadratic Programming

This study proposes a methodology to evaluate the maximum feasible penetration levels of combined heat and power (CHP) and photovoltaic (PV) systems in densely populated urban areas with abundant solar resources. Microturbines (MTs) and PV units are modeled as distributed generation (DG) assets, and their optimal capacities are determined using a quadratic programming (QP) framework. The optimization is formulated as a hosting capacity (HC) problem for DG integration. To capture long-term investment and operational costs, life-cycle expenses are estimated with the HOMER platform and approximated through polynomial functions. These functions are incorporated into a cost-minimization problem that also accounts for technical constraints, such as voltage regulation. The QP model is implemented in MATLAB to identify HC configurations that balance economic efficiency with operational feasibility. A case study based on hourly electricity and thermal demand data from an urban residential community demonstrates the effectiveness of the approach. The findings provide practical guidance for utility planners and policymakers seeking to integrate CHP and PV systems in solar-rich metropolitan regions and advance the goal of 100% renewable energy.