The rapid integration of distributed energy resources, especially photovoltaics (PVs), has triggered the evolution of active distribution networks. This evolution necessitates the assessment of hosting capacity (HC) to determine the maximum allowable PV power generation while ensuring network operating constraints. Firstly, this paper defines a robust HC under the worst case of uncertainty realization and a risk-averse HC that can reduce the risk of inadequate assessment. Then, this paper proposes robust and risk-averse HC maximization methods with inverter-based Volt/Var control (VVC) for a three-phase unbalanced distribution network. The proposed robust or risk-averse HC can be used as an objective function in optimization models. A linearized branch flow model for the network operation and a compatible ZIP load modeling for voltage-dependent loads is developed. Finally, a Latin hypercube sampling method is adopted to model the uncertainty for the optimization models. Numerical simulations are conducted on an extensive and unbalanced distribution network. Simulation results validate the accuracy of the models with an error of less than 1% and the effectiveness of the robust and risk-averse HC maximization methods in assessing robustness and the risk control of unexpected HC realizations.

Photovoltaic (PV) inverter-based volt/var control (VVC) is highly promising to tackle the emerging voltage regulation challenges brought by increasing PV penetration. However, PV inverter operational reliability has arisen as a critical concern for practical VVC implementation. This paper proposes a new PV inverter based VVC optimization model and a Pareto front analysis method for maintaining a satisfactory inverter lifetime. First, reliability of the vulnerable DC-link capacitor inside a PV inverter is analyzed, and long-term VVC impact on inverter operational reliability is identified. Second, a multi-objective PV inverter based VVC optimization model is proposed for minimizing both inverter apparent power output and network power loss with a weighting factor. Third, a Pareto front analysis method is developed to visualize the impact of the weighting factor on VVC performance and inverter reliability, thus determining the effective weighting factor to reduce network power loss with expected inverter lifetime. Effectiveness of the proposed VVC optimization model and Pareto front analysis method are verified in a case study.