Yes / This paper proposes a probabilistic method for active distribution networks planning with integration of demand response. Uncertainties related to solar irradiance, load demand and future load growth are modelled by probability density functions. The method simultaneously minimizes the total operational cost and total energy losses of the lines from the point of view of distribution network operators with integration of demand response over the planning horizon considering active management schemes including coordinated voltage control and adaptive power factor control. Monte Carlo simulation method is employed to use the generated probability density functions and the weighting factor method is used to solve the multi-objective optimization problem. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system.

Yes / This paper proposes a probabilistic multi-objective optimization method for the operation of three-phase distribution networks incorporating active network management (ANM) schemes including coordinated voltage control and adaptive power factor control. The proposed probabilistic method incorporates detailed modelling of three-phase distribution network components and considers different operational objectives. The method simultaneously minimizes the total energy losses of the lines from the point of view of distribution network operators (DNOs) and maximizes the energy generated by photovoltaic (PV) cells considering ANM schemes and network constraints. Uncertainties related to intermittent generation of PVs and load demands are modelled by probability density functions (PDFs). Monte Carlo simulation method is employed to use the generated PDFs. The problem is solved using ɛ-constraint approach and fuzzy satisfying method is used to select the best solution from the Pareto optimal set. The effectiveness of the proposed probabilistic method is demonstrated with IEEE 13- and 34- bus test feeders.