Minimization of Power Losses through Optimal Battery Placement in a Distributed Network with High Penetration of Photovoltaics

Abstract

The problems associated with the deployment of intermittent, unpredictable and uncontrollable solar photovoltaics (PV) can be feasibly solved with battery energy storage systems (BESS), particularly in terms of optimizing the available capacity, increasing reliability and reducing system losses. Consequently, the degree of importance of BESS increases in proportion to the level of PV penetration. Nevertheless, the respective high cost of BESS imposes a huge concern and the need to establish a techno-economic solution. In this paper, we investigate the system losses and power quality issues associated with the high deployment of PV in a grid network and hence formulate BESS capacity optimization and placement methodology based on a genetic algorithm. The concept of the proposed methodology has been tested and validated on a standard IEEE 33 bus system. A brief stepwise analysis is presented to demonstrate the effectiveness and robustness of the proposed methodology in reducing the incremental system losses experienced with increased PV penetration. Furthermore, based on the proposed optimization objectives, a comparative study has also been performed to quantify the impact and effectiveness of aggregated and distributed placement of BESS. The results obtained exhibit a substantial reduction in system losses, particularly in the case of distributed BESS placement.

Comparison of Economical and Technical Photovoltaic Hosting Capacity Limits in Distribution Networks

“…P load and P pv are the load active power values at each node and the PV power added among the nodes in steps of 100 W. Similarly, Q corresponds to the reactive power of the loads and the added PVs where the term Q pv in ( 10) is zero in this analysis due to unity power factor of PVs. The S node is the node apparent power that is further used in the BFS load flow analysis for the calculation of nodal currents as (11) and V node is the voltage at each network node.…”

“…The authors in this study employed the simulation results of a pilot PV application to assess the grid losses, the loading level of individual grid components (cables and transformers), and voltage profiles to reach an optimal network. The load-leveling can be achieved by the optimal installation of storage systems as performed in [11] by investigating an IEEE 33-bus system to address the system losses of a distribution network under high PV penetration. Load-leveling can be achieved by storing the surplus PV power during off-peak hours and supplying the stored power in peak hours as per the findings of this study.…”

Sizing and Sitting of DERs in Active Distribution Networks Incorporating Load Prevailing Uncertainties Using Probabilistic Approaches

“…Optimal sizing of renewable energy resources with the goal of loss reduction in distribution grids using the ant lion optimization method is presented in [22]. A battery placement problem is also presented in [23], in which it is objected to reducing losses in a distribution grid with high penetration of solar sources. In [24], optimal allocation and sizing of renewable distributed generation are investigated.…”

Active Power Management for PV Systems under High Penetration Scenario

“…In recent years, different techniques associated with voltage regulation and control methods to mitigate the effect of high PV penetration have been proposed. These solutions include studies to determine the maximum loads connected to the grid [23], grid layout and loads residential design [24], variable tap transformers [25] and smart transformers applications [26], battery bank systems [27][28][29], inverters with reactive power capability [30][31][32][33], and the interconnectivity of external devices with the grid as smart electrical vehicles [34]. Additionally, the theoretical use of a communication network that allows making decisions based on grid variations has been suggested [35].…”

“…The use of ESS or electric vehicles may be a good alternative [27][28][29]34]. This allows storing the PV energy; however, the ability to regulate the voltage variations depends on the storage capacity.…”