Batteries are essential for efficiently utilizing the energy from the photovoltaic (PV) modules. However, integration of batteries with PV plants at large scale needs more attention in terms of size, location, and times for the charging and discharging of the batteries. This paper addresses these aspects. It presents a mixed integer optimization using genetic algorithm for determining the optimum size and placement of battery-sourced distributed PV generation (B-SDPVG) in distribution networks. The total energy loss index is formulated as the main objective function and simultaneously, the bus voltage deviations and penetrations of the B-SDPVG are calculated. The yields from the PV plants are estimated using 15 years of weather data modeled with the aid of beta probability density function. Furthermore, a novel charge–discharge control model is developed for determining the choice of the charging and discharging of batteries at each hour. By considering different time varying voltage-dependent load models, the proposed algorithm is applied on the IEEE 33 bus and the IEEE 69 bus test distribution networks. The numerical results of two distribution networks with time-varying loads show the advantages of the proposed methodology. It was revealed that integration of battery storage and intelligent scheduling for charging and discharging of batteries produced much better results and improved the quality of distribution networks. The supply of power from the B-SDPVG during the peak load hours and at night was made possible for each load model. The proposed charge–discharge control model for scheduling the charging and discharging of the batteries was found dynamic. Results of this paper can be of potential importance in planning for the integration of battery storage in distribution networks.

Battery Storage for the Utility-Scale Distributed Photovoltaic Generations

Optimal Location of a Distributed Generator for Power Losses Improvement

A Novel Method Based on PPSO for Optimal Placement and Sizing of Distributed Generation

The rate of integration of distributed generation (DG) using renewable sources is increasing in distribution networks because of their technical and economic advantages. However, mismatches in the timing of electricity demand and generation in distribution networks have restricted the penetration of non-dispatchable DGs such as photovoltaic (PV) plants. Such a problem associated with the integration of DGs in distribution networks could be eliminated using the proper application of battery energy storage systems. In this paper, optimal planning of battery-coupled distributed photovoltaic generators (BCDPGs) in distribution networks is presented. The optimal planning determines the size and location of BCDPGs and schedules the charging and discharging of the batteries, while minimizing the total energy losses subject to technical constraints. To estimate the output from PV modules, 15-year solar irradiance data is modeled using the beta probability density function. Mixed-integer optimization using a genet...

Sizing and placement of battery-coupled distributed photovoltaic generations

This paper presents an analytical approach to find the optimum sizes and locations of battery-sourced inverters (BSI) in electrical distribution networks. To find optimum sizes and locations of BSI units, two indices, namely, minimum power injection (MPI), and minimum active power loss index (MAPLI) are used. BSI units can supply active and reactive power, are used to improve system voltage profile and reduce system losses. To investigate the dynamic effects, instead of conventionally used fixed peak load, a 24-hour time varying load model is used. To supply active and reactive power, BSI units are attached to all buses, but at one bus each time, with sizes starting from 0 and are further increased with a rate of 0.5 KVA, meanwhile the two indices are calculated for every bus for each hour. Method is tested on IEEE-33 bus test distribution network and results are presented. The results show that utilization of BSI can improve the voltage profile and can reduce the system losses up to 78% in distribution networks. The study also suggests that best time for utilizing of stored energy is during the peak load hours.

An analytical approach for the sizing and siting of battery-sourced inverters in distribution networks

This paper presents a method based on analytical approach for real power loss minimization of distribution networks by injecting power by the Distributed Generation (DG) operating at a given power factors. This method does not require calculation of Zbus matrix, inverse of Ybus matrix or Jacobean matrix as well as requires less computation time. The proposed method is tested on an IEEE 33-bus radial distribution test system. The results obtained by this proposed method validate the suitability and importance of appropriate DG allocation in power distribution networks for the performance improvement.

S. G. Naik

Papers

Sizing and siting of distributed generation in distribution networks for real power loss minimization using analytical approach