Due to their technical, economical, and environmental advantages, active distribution networks implement renewable energy resources (RERs) such as photovoltaic (PV) units in distribution networks DNs. However, some drawbacks may arise due to the intermittent nature of RERs, such as voltage fluctuations and increased system losses. This paper presents an optimization problem that is solved by sequential linear programming (SLP) to improve the voltage profile of the unbalanced distribution network. A probabilistic approach was applied to both the load profile and the active power generation of the PV units. SLP is applied to the modified IEEE 34 Bus Test system. The method optimizes the voltage deviations by changing the taps of the voltage regulators and the reactive power injected by the inverters of the PV systems and, in some cases, by switching a shunt capacitor. MATLAB simulations are done at different times of the day with different loads and PV outputs to compare base case and optimal case voltage profiles. The results show better voltage profiles after applying the presented approach.

The implementation of renewable energy resources (RERs) such as photovoltaic (PV) units and wind turbines (WTs) has been intensively used on active distribution networks (ADNs) due to their significant environmental, technical, and economic benefits. However, their intermittent nature causes some fluctuations in the voltage profiles, which lead to increased losses in the system. This study presents sequential quadratic programming (SQP) optimization method to improve voltage profiles by optimizing tap changer positions and reactive power output of the inverter of a single PV unit. The proposed optimization is applied to the IEEE 34-bus unbalanced distribution test system to validate its performance. Optimum voltage profiles are compared with the base case conditions where there are no PV sources and voltage regulators. The results show that the SQP provides reliable voltage profile improvement for various operational conditions.

The deployment of renewable energy resources (RER) such as photovoltaic (PV) and wind turbine (WT) systems has significantly improved the operation of active distribution networks (ADN). This can be seen in the technical, economic, and also environmental benefits observed over the past decade. However, since these resources have intermittent nature, they usually cause voltage and frequency fluctuations, which leads to increased system losses and instability. In this paper, sequential linear programming (SLP) is used to improve the voltage profile of unbalanced distribution networks. The method is applied to a modified IEEE-34 node test feeder. Three PV systems are installed in the system, and two of them are connected through a soft open point (SOP). The method optimizes the reactive power flow through the SOP and the third PV coming from the smart inverter, as well as the taps of the voltage regulators to reduce the voltage deviation from the reference voltage value. The voltages in the base and optimum cases are compared for each time simulation with and without the use of SOP. The results show that a more improved voltage profile is obtained after the use of SOP.