Smart integration of distributed renewable generation and battery energy storage

Hung, Duong Quoc (2014). Smart integration of distributed renewable generation and battery energy storage PhD Thesis, School of Information Technol and Elec Engineering, The University of Queensland. doi:10.14264/uql.2014.384

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
s4250093_phd_submission.pdf Thesis (open access) application/pdf 1.45MB 1413

Author Hung, Duong Quoc
Thesis Title Smart integration of distributed renewable generation and battery energy storage
School, Centre or Institute School of Information Technol and Elec Engineering
Institution The University of Queensland
DOI 10.14264/uql.2014.384
Publication date 2014-10-30
Thesis type PhD Thesis
Open Access Status Other
Supervisor Mithulananthan Nadarajah
Ramesh Bansal
Total pages 187
Language eng
Subjects 0906 Electrical and Electronic Engineering
Formatted abstract
Renewable energy (i.e., biomass, wind and solar) and Battery Energy Storage (BES) are emerging as sustainable solutions for electricity generation. In the last decade, the smart grid has been introduced to accommodate high penetration of such renewable resources and make the power grid more efficient, reliable and resilient. The smart grid is formulated as a combination of power systems, telecommunication communication and information technology. As an integral part of the smart grid, a smart integration approach is presented in this thesis. The main idea behind the smart integration is locating, sizing and operating renewable-based Distributed Generation (DG) resources and associated BES units in distribution networks strategically by considering various technical, economical and environmental issues. Hence, the aim of the thesis is to develop methodologies for strategic planning and operations of high renewable DG penetration along with an efficient usage of BES units.

The first contribution of the thesis is to present three alternative analytical expressions to identify the location, size and power factor of a single DG unit with a goal of minimising power losses. These expressions are easily adapted to accommodate different types of renewable DG units for minimizing energy losses by considering the time-varying demand and different operating conditions of DG units. Both dispatchable and non-dispatchable renewable DG units are investigated in the study. Secondly, a methodology is also introduced in the thesis for the integration of multiple dispatchable biomass and nondispatchable wind units. The concept behind this methodology is that each nondispatchable wind unit is converted into a dispatchable source by adding a biomass unit with sufficient capacity to retain the energy loss at a minimum level. Thirdly, the thesis studies the determination of nondispatchable photovoltaic (PV) penetration into distribution systems while considering time-varying voltage-dependent load models and probabilistic generation. The system loads are classified as an industrial, commercial or residential type or a mix of them with different normalised daily patterns. The Beta probability density function model is used to describe the probabilistic nature of solar irradiance. An analytical expression is proposed to size a PV unit. This expression is based on the derivation of a multiobjective index (IMO) that is formulated as a combination of three indices, namely active power loss, reactive power loss and voltage deviation. The IMO is minimised in determining the optimal size and power factor of a PV unit. Fourthly, the thesis discusses the integration of PV and BES units considering optimal power dispatch. In this work, each nondispatchable PV unit is converted into a dispatchable source by adding a BES unit with sufficient capacity. An analytical expression is proposed to determine the optimal size and power factor of PV and BES units for reducing energy losses and enhancing voltage stability. A self-correction algorithm is then developed for sizing multiple PV and BES units. Finally, the thesis presents a comprehensive framework for DG planning. In this framework, analytical expressions are proposed to efficiently capture the optimal power factor of each DG unit with a standard size for minimising energy losses and enhancing voltage stability. The decision for the optimal location, size and number of DG units is obtained through a benefit-cost analysis over a given planning horizon. Here, the total benefit includes energy sales, loss reduction, network investment deferral and emission reduction, while the total cost is a sum of capital, operation and maintenance expenses.

The study reveals that the time-varying demand and generation models play a significant role in renewable DG planning. Depending on the characteristics of demand and generation, a distribution system would accommodate up to an estimated 48% of the nondispatchable renewable DG penetration. A higher penetration level could be obtained for dispatchable DG technologies such as biomass and a hybrid of PV and BES units. More importantly, the study also indicates that optimal power factor operation could be one of the aspects to be considered in the strategy of smart renewable DG integration. A significant energy loss reduction and voltage stability enhancement can be achieved for all the proposed scenarios with DG operation at optimal power factor when compared to DG generation at unity power factor which follows the current standard IEEE 1547. Consequently, the thesis recommends an appropriate modification to the grid code to reflect the optimal or near optimal power factor operation of DG as well as BES units. In addition, it is shown that inclusion of energy loss reduction together with other benefits such as network investment deferral and emission reduction in the analysis would recover DG investments faster.
Keyword Battery energy storage
Distribution system
Energy loss
Optimal power factor
Photovoltaic (PV)
Renewable distributed generation
Voltage deviation
Voltage stability

Document type: Thesis
Collections: UQ Theses (RHD) - Official
UQ Theses (RHD) - Open Access
Version Filter Type
Citation counts: Google Scholar Search Google Scholar
Created: Thu, 16 Oct 2014, 16:30:52 EST by Mr Hung Duong on behalf of Scholarly Communication and Digitisation Service