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[Display omitted] • Regions where feed-in tariff higher than valley price should follow dual objective optimization. • The economy of the household PV-BES-EV system mainly depends on the purchase cost of EVs. • Decreasing electricity price will not undermine the effectiveness of the household PV-BES-EV system. • The energy bills and carbon emissions decrease significantly with the optimal scheduling schemes. The household PV-BES-EV system (photovoltaic - battery energy storage - electric vehicle system) connected to the grid can guarantee the electricity demand of the household and facilitate the flexible trade with the grid to achieve the goals of cutting energy bills and reducing carbon emissions. In related issues, past studies often assume that renewable energy is both economical and environmentally friendly, and thus regarded it as the primary power source. While in fact, in some regions where the feed-in tariff is higher than the sales price at a certain time, households may be driven by arbitrage opportunities to frequently purchase electricity from the grid at the certain time to gain benefits, resulting in far greater carbon emissions than expected within the household measurement boundary. To avoid the environmental burden caused by pure economic incentives and to provide practical and sustainable solutions consistent with various energy price policies, the optimal scheduling schemes of the household PV-BES-EV system that considers both economic and environmental incentives for different scenarios solved by the genetic algorithm is proposed in this paper. Household data in Shanghai, China and Hamburg, Germany were selected for modelling, representing the dual-objective optimization scenario with arbitrage opportunities and the single-objective optimization scenario with sales price higher than feed-in tariff, respectively. Results show that for urban and rural residents in Shanghai, the energy bill and carbon emission would decline about 105%, 48% and 88%, 62%, respectively. As for Hamburg, the accordingly results would be 69% and 64%. In addition, based on the cost-effectiveness of the system in long-term, this paper puts forward policy recommendations that align with local conditions to further improve the economy of the system. [ABSTRACT FROM AUTHOR]