Design Optimisation of Hybrid Photovoltaic and Energy Storage Systems through Smart Grid Technologies to Maximise Economic Benefit
- Publication Type:
- Thesis
- Issue Date:
- 2020
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Advances in photovoltaic and battery energy storage system (BESS) technologies have made hybrid PV-BESS systems an attractive prospect for residential energy consumers. However, the process to select an appropriate system is non-trivial due to the relatively high cost of batteries, a multitude of available retail electricity plans, the removal of incentive schemes and the impending introduction of disruptive technologies such as peer-to-peer energy trading.
The introduction of Smart Grid technologies, particularly smart meters, enables consumers to leverage high temporal resolution energy consumption data to optimise system design based on an individual customer's circumstance. In this research, real-world energy consumption data for a large sample of homes are applied to an optimisation strategy developed to the select system size, tilt, azimuth and retail electricity plan for a residential PV-BESS based on a customer's temporal load profile. A case study examining a real world hybrid PV-BESS is presented to demonstrate the potential benefit of applying the optimisation process established in this research.
Particle swarm optimisation (PSO) is utilised as the underlying optimisation algorithm given its suitability to mixed integer non-linear programming problems, characteristic of the energy models developed in this research. To improve global search performance with minimal parameter adjustments, various forms of PSO are applied including quantum-behaved PSO and a modified version with a comprehensive learning component.
To facilitate energy yield modelling, accurate hourly solar irradiation and photovoltaic array generation models are critical to the optimisation process. Numerous models have been developed to estimate diffuse and direct irradiance components based on global irradiation measurements. The Boland–Ridley–Lauret (BRL) model consists of a single set of parameters for all global locations. There is scope to improve the BRL model to better match local climatic conditions. In this research, the Köppen-Geiger climate classification system is considered to develop a set of adjusted BRL models for Australian conditions, which are subsequently applied to the energy models developed in this research.
With the future application of peer-to-peer energy trading markets, prospective investors would benefit from prior consideration of market conditions and the penetration rates of participant PV-BESS systems when designing such systems. In this research, a lifetime assessment of PV-BESS systems is undertaken for a hypothetical peer-to-peer market of over 2,000 participants. Trader margin, participant margin, network tariff structures and PV-BESS penetration rate scenarios are considered to examine the impacts on the optimal PV-BESS design maximising the economic return.
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