As photovoltaic (PV) generation has been one of the major renewable energy sources around the world, its PV capacity has also increased. When the large-scale PV systems are integrated into the distribution network, the complexity of the assessment process of the distribution network reliability will increase hazardously. In order to accurately assess this reliability in the distribution network combined with the PV generation, a reliability assessment procedure is proposed. In order to accurately evaluate the impact of the failure of conventional power equipment on reliability, the time-varying failure rate of conventional power equipment is modeled, taking into account the aging period. Then, in order to accurately evaluate the reliability improvement with PV systems integration, the new procedure is proposed highlighting the following contributions: 1) five new indices are added. 2) PV output is modeled so that not only the radiation intensity but also the failure and degradation of PV modules are represented. 3) time-varying islanding operation is considered and integrated. A case study using real-life distribution network topology and data in China is applied to verify that the newly proposed reliability indices display more sensitivity, and the proposed procedure significantly improves the accuracy of the reliability assessment.

The randomness of electric vehicle (EV) charging has negative impacts on three‐phase imbalance and peak–valley difference in electric energy distribution systems. Traditional EV charging strategies have shortcomings: the performance of three‐phase imbalance mitigation may be limited if the grid‐connected EVs are extremely imbalanced on three phases; in addition, the comprehensive regulation of peak–valley difference and three‐phase imbalance is not developed, and the three‐phase imbalance of reactive power is ignored. Therefore, a real‐time multilevel energy management strategy (RMEMS) for EV charging is proposed. A tri‐level optimization model (TOM) is designed as the central system. In upper‐level optimization, the three‐phase selection (TPS) of EVs is optimized to balance active or reactive power consumption on three phases. Based on the results from upper‐level optimization, the charging active power is regulated in middle‐level optimization to reduce the peak–valley difference on each phase. In lower‐level optimization, the reactive power compensated by EV chargers is optimized based on the results from upper‐level and middle‐level optimization to balance the reactive power on three phases. Case studies show that the proposed RMEMS performs well for balancing active and reactive power consumption on three phases, and the peak–valley differences of active power consumption on each phase are all mitigated.

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Electric vehicles (EV) and photovoltaic (PV) generation are widely recognized around the world. Most EV owners in the major Chinese cities are forced to charge their EV batteries at the workplace during the daytime due to the limited space near their homes, which will increase the peak load during the daytime. On the other hand, the PV output is most likely to have a peak at around noon, which means, PVs could have a potential capability to compensate the EV charging load. An EV owner-friendly charging strategy based on PV utilization which alleviates both the EV charging constraints and the negative impact of the EV charging load on the grid is proposed. The PV utilization for compensating the unconstrained EV charging load is maximized to derive the maximum number of EVs with unconstrained charging. If the actual number of EVs exceeds the maximum number, a portion of EVs have to be charged only from the grid. Then, the line loss is introduced as the optimization objective in which the charging states are regulated. The case study shows that the proposed strategy can successfully increase the number of EVs with unconstrained charging, and reduce the peak-to-peak of the load curve.

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