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Environmental and financial multi-objective optimization: Hybrid wind-photovoltaic generation with battery energy storage systems

Publication at Faculty of Social Sciences |
2023

Abstract

The present study proposes a multi-objective optimization method for wind and photovoltaic (PV) hybrid gen-eration with battery energy storage, considering a tariff policy issue for the grid-connected residential scenario. The proposed method used the Response Surface Methodology (RSM) to model two objective functions, one environmental (Carbon footprint) and the other financial (Net Present Value -NPV) in relation to four controllable variables.

To perform the multi-objective optimization, the Normal-Boundary Intersection (NBI) was used to construct the Pareto frontier. Finally, the Levelized Cost of Energy (LCOE) criterion was used to select the best Pareto optimal point.

The proposed model was applied in Brazilian cities from different geographic regions. The main results of the study indicated that only regions with favorable environmental conditions and higher energy tariffs became financially viable for the proposed model, with NPV values ranging from R$-76,080.94 to R$ 69,675.23.

As for the Carbon footprint (emission of CO2eq), the values ranged from 8951.47 to 27,939.78 kgCO2/kWh, being strongly influenced by the adopted power generation technology. The use of LCOE to select the best solution provided a metric for the cost of implementing a technology, whose values ranged from 1.093 to 1.981 R$/kWh.

It is still not advantageous to opt for the use of batteries for later use at peak hours, even when the tariff modality selected was the white tariff; and energy storage systems that could enable the imple-mentation of this policy proved to be economically unfeasible. In the current Brazilian legislation, the services and benefits generated by energy storage are not remunerated, which penalizes the investment in this type of technology.

As proved, solar PV technology, despite being cheaper, was penalized by a greater need for storage capacity, which led to optimal configurations with greater participation of wind generation. This indicates the need for incentives mainly related to wind energy and batteries, which are still expensive elements in the na-tional scenario for a residential generation, reducing the probability of achieving economic viability.