Development of Control Methodologies for Energy Storage Systems in Electricity Distribution Networks

Abstract

Prompted by technical issues that have arisen due to the widespread deployment of distributed intermittent renewable generators, rapidly rising peak demand and reductions in battery price, the use of Battery-Based Energy Storage Systems (BESS) in power networks is on the rise. While BESS has the potential to deliver technical benefits, the best possible sizing, location and usage govern the financial viability. Prevailing models of determining BESS size, location and charging patterns have treated them as independent problems and lack explicit dependence on factors such as load growth rate, PV penetration level, network size and structure. Furthermore, the existing literature does not provide any guidelines on possible interaction between network operators and retailers to employ batteries for a distribution network operator's benefit.To bridge the existing research gaps, a generic approach to select appropriate sizing and siting of BESS for supporting both distribution utilities and customers is developed in this thesis. A method is established to model network upgrade deferral as a function of load growth rate, renewable generation penetration and peak shave fraction. This model is then used for the formulation of an optimisation problem which benefits from multi-period power flow analysis to co-optimise the size, location and dispatch scheduling of BESS for a pre-specified number of units to be deployed in a given distribution network. The proposed approach is implemented on a segment of the Australian medium voltage distribution network under multiple practical and potential future scenarios.Moreover, the developed methodology is utilised to obtain appropriate sizing and siting while controlling a BESS in the rest of the thesis. In this thesis, a new control method is proposed and practically validated to ensure smooth BESS operation amenable for prolonged BESS life without compromising the voltage regulation performance. The approach is based on the finite short-term forecast of PV generation to obtain forecast voltage trajectories. The forecast PV generation in conjunction with calculated feasible BESS charge-discharge trajectories is utilised to regulate voltage response over a finite time horizon that substantially reduces the charge-discharge cycling of BESS.ii As the uptake of BESS for photovoltaic applications rises, their aggregated use for network voltage regulation is considered as an impending option. Therefore, a generic approach to coordinate distributed BESS of customers with a view to system voltage regulation through the help of a demand response aggregator is developed. The proposed control algorithms are practically validated by using a Hardware-in-the-Loop (HIL) setup comprising of a Real Time Digital Simulator (RTDS) and a dSPACE controller board.iii Declaration by authorThis thesis is composed of my original work, and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution ...

Voltage control in power distribution grids equipped with large-scale renewable energy sources

“…Linearization [116], [160], in this research a non-convex problem is optimised by means of the MINLP method. This approach is justified by the fact that the control coordination method should be easily applicable to any distribution grid while determination of a linear region can be unfeasible or at least impractical in a field implementation.…”

“…This can be presented as in Figure 2.20, which shows the relation between the RTDS, the dSpace and a host computer used for grid modelling, controller programming and overall process control. Figure 2.20 Example of the HIL setup with RTDS and dSpace controller [116] In contrast, in real-time SIL platforms, grid data is retrieved from the real-time grid simulator by means of digital communication protocol, which needs to be implemented both in the grid simulator as well as in the control processing unit. Interestingly, the SIL approach can be considered as a first step for testing concepts for a recently introduced digital substation [16] with centralised control [20].…”

“…[171]) of extensive use of a battery storage. Namely, J Dir ′′ (7.15) includes potential changes of power direction which is a particularly undesirable operation when BESS works in a price-driven scheme or when a micro-cycle charging shortens batteries lifetime [116]. Arguably, the J Dir ′′ might be considered as an additional constraint of (7.3).…”