Electricity generation and distribution is undergoing significant change under the influences of energy security, climate change, technological development, and economics. Technologies that have introduced two-way power flow onto a distribution grid that was designed for one-way power flow are creating challenges and opportunities for innovation in the electricity distribution sector. These technologies include solar photovoltaics (PV), wind turbines, and battery energy storage systems (BESS). As the newest technology, BESS present opportunities to both the electricity distribution network service provider (DNSP) and the consumer. This dissertation focused primarily on the consumer side of the switchboard, modelling and analysing the economics and some of the technical issues for an economic-mediated battery controller as part of a grid-tied residential hybrid renewable energy system (HRES) that consists of a BESS, 1 kW wind turbine, and 10 kW PV array.
The geographical context of this project is Nambour, Queensland; PV and wind power calculations were based on Nambour’s meteorological history. Residential energy consumption was modelled as a ‘typical’ Nambour residential customer. The technological context was such that costs and choices applied at mid-2016. The tariff context used was the recently introduced TOU tariff 12, which played a significant role in the timing and logic development of the battery charge controller algorithm.
From a technical standpoint, the charge controller algorithm was a major achievement of the present work. In developing the algorithm, it was found that the use of data from individual system components could be used to formulate the optimum mix of power sourced from or sunk to both the grid and the BESS. The output of this formulation was then demonstrated as a data input used for the control of the switching patterns of the BESS power electronics, a two-quadrant DC-DC converter (chopper).
The other major achievement of the current work was the finding that although BESS economics continue to improve, they generally still need to achieve further cost reductions in order to realise economic feasibility for the modelled context. It was also found that economic feasibility is more likely to be reached more quickly under conditions of high energy consumption, high inflation, high peak TOU tariff, and low discount rate
