Seasonal Scheduling of Energy Storage in Networks Incorporating PV Generation Systems

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Mekala, Santhosh Reddy (2020) Seasonal Scheduling of Energy Storage in Networks Incorporating PV Generation Systems. Research Master thesis, Victoria University.


Electricity usage has been increasing all around the world with the changing lifestyle and increasing population. Seasonal changes lead to changes in the output of Photovoltaic (PV) systems, causing power variations that feature frequency changes and voltage fluctuations. Well-designed integration of distribution energy could assist with the challenges of power quality, high system losses and peak load demand in localised distribution grids, called the micro grids. Energy Storage Systems (ESS) is an alternative solution to solve many problems in the grid. In many countries, the electrical distributors and regulators require large amounts of ESS to be installed to back up the grid in consideration of the intermittency of renewable energy resources such as wind and solar PV. In many countries, distribution planners lack optimal tools and methods to operate the ESS with impact on distribution network reliability, capacity and power quality. Especially, distribution planners are conventional to static-mode power flow calculations, but in some cases to minimise the power and voltage quality issues, ESS needs Sequential-Time-Series (STS) analysis. In ESS, the batteries are connected in parallel to increase the reliability on the distribution system but due to the charge/discharge imbalance in the scheduling of ESS, power quality issues are arising in distribution networks. This charge/discharge imbalance can also affect the battery life due to circulating currents in the batteries. However, the battery life would be shortened due to increased number of cycles and deep discharge at a specific time could raise the over voltage issues in distribution systems. This research aims to model seasonal scheduling of energy storage in networks incorporating PV generation systems. The research focuses on demonstrating the impact of seasonal variations on voltage quality in PV integrated networks. Based on the analysis, a charge/discharge schedule is developed taking account of seasonal variations. The key focus is to demonstrate the variations in the seasonal charge/discharge schedule of a battery storage system to meet ANSI (American National Standard Institute) steady-state voltage limits. One key benefits of this scheduling are efficient operation leading to increase the battery life, reduce losses in the transformer and improve power quality outcomes. The cycle life is given by the number of complete charge/discharge cycles that a battery can support before its capacity falls under a defined percentage of its original capacity with partial discharge having favourable impact on the battery life. With these outcomes, distribution planners can analyse and plan for current and future electricity demand using a seasonal approach. This research covers seasonal charge/discharge scheduling of Energy Storage Systems (ESS) for various seasonal steady-state analysis validated for the chosen most severely affected buses in a case study network with specific periods in all seasons. A key outcome is the developed seasonal Charge (C) and Discharge (D) allocations and validation of the sufficiency of such a seasonal allocation in addressing power quality issues especially the required steady-state voltage limits. The charge and discharge percentages have been chosen to implement partial charge or discharge to support the battery life. The work demonstrates the need for such a seasonal allocation schedule. The undertaken analysis validates a seasonal allocation would be sufficient to minimise Over Voltage (OV) and Under Voltage (UV) issues even in PV penetrated networks. The focus of this research is the allocation of charge/discharge schedules of the energy storage system using the sequential time series method. Research aimed to validate that a fixed seasonal charge/discharge schedule is sufficient to address the power quality issues in exchange for a complex and sophisticated scheme. Thus, the work intends to demonstrate the sufficiency of such a seasonal allocation approach. The methodology in this thesis follows modelling of the EPRI CKT24 network with network data sourced from Sandia National Laboratories (SNL) and assessment of seasonal voltage quality issues for PV and no-PV cases. Steady-state analysis of the entire network has been performed with results elaborated for two selected buses. Phase C in the unbalanced case study network was observed to suffer most from the voltage power-quality issues and therefore efforts were directed towards a more detailed analysis of this phase. Further steady-state analysis of the chosen buses highlighted over voltage issues at times of low demand especially in the early hours of the day after midnight, made worse by the PV power that begins to be injected into the network subsequent to the sunrise. Spring and autumn seasons were observed to be the worst two seasons in the terms of power quality and the impact of PV penetration on the power quality. Based on findings from the analysis of seasonal voltage variations, energy storage has then been modelled and incorporated into the existing EPRI CKT24 case study network model. Whilst the OpenDSS network model incorporated PV elements, this ESS modelling and incorporation was an original contribution in this dissertation. The storage elements were modelled as generators, which can dispatch power in charge or discharge modes within their rated specifications. A dynamic daily charge/discharge schedule has been developed consistent for the entire season to alleviate voltage quality issues taking consideration of seasonal requirements. In this thesis, a Sequential-Time-Series (STS) based seasonal charge and discharge schedule has been proposed using a storage controller that sets the charge/discharge schedules of the energy storage system in response to seasonal requirements. OPENDSS has been used to model the network power quality problems with OpenDSS compiling the network data into the MATLAB environment via a COM interface. The storage controller has been set and controlled through the MATLAB to OpenDSS interchange. Seasonal analysis was then performed using the various seasonal LoadShape allocations to demonstrate that a one-size fits allocation would not work at every season and a seasonal consideration is indeed required. Steady-state voltages have been demonstrated to be better controlled in the mid voltage range with such seasonal consideration. A key contribution is the seasonal analysis and validation of the sufficiency of a seasonal charge and discharge allocation strategy in meeting grid code requirements with respect to the bus voltages.

Additional Information

Master of Engineering by Research

Item type Thesis (Research Master thesis)
Subjects Current > FOR Classification > 0906 Electrical and Electronic Engineering
Current > Division/Research > College of Science and Engineering
Keywords electricity; energy storage systems; ESS; EPRI CKT24 network; OpenDSS; MATLAB; PV systems
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