• Energy Research

Abstract In the context of last-mile electrification of rural communities, stand-alone solutions like Solar Home Systems are often considered an equivalent option for access to electricity as other technologies, such as minigrids and connection to the main grid. In this work, the authors question this paradigm and propose an alternative approach that takes into account the limited service, and in turn, limited development possibilities, that Solar Home Systems grant to their users. A monetary penalty is applied to this technology based on the missed services. The conceived approach is applied to a case study in the district of Cochabamba, Bolivia, thanks to the cooperation with a local NGO. Results show how the inclusion of shadow costs influences the optimal electrification strategy in terms of users connected to the main grid by up to 33%, highlighting how standard approaches tend to overlook key aspects of access to electricity linked to the possibility of development.

Rural electrification plays a key role in terms of achieving the target of universal access to electricity by 2030. In order to deploy reliable and sustainable solutions, the sizing phase of decentralized power systems requires specific inputs such as long-term forecasts of the electricity load. In rural contexts, access to electricity is extremely interlinked to social-economic complex dimensions that in turn, influence the electricity demand. In this paper, we rely on System Dynamics for modelling such complexities, and we calibrate the results with data from a hydroelectric-based electrification programme implemented in 2005 in the rural community of Ikondo, Tanzania. We coupled the model with a newly extended version of a load stochastic tool, namely Lifetime – LoadProGen, in order to introduce a more reliable and calibrated approach to long-term electricity load forecasts.

As it emerges from the literature, electricity access in rural contexts is deeply intertwined with socioeconomic dynamics. However, the advent of a reliable and sufficient source of electricity is not the sole driver that might contribute to local development. Indeed, complementary activities might have a crucial role in sustaining the development of rural communities as well as the electricity access. The current research addresses the lack of counterfactual scenarios in which the impact of complementary activities on electrification projects can be investigated. The authors introduce the case study of Matembwe village, a rural community in the Njombe region of Tanzania. The data collection includes the electricity consumption, number of electricity connections, and number of income-generating activities in a timespan ranging from 1989 to 2015. The analysis is based on system dynamics. The study considers different scenarios representing the dynamics related to the following complementary actions: access to market measures, access to credit measures, and access to usable skills. On the one hand, the study reveals that the effectiveness of the considered complementary actions is limited except from the access to microcredit which fosters an increase in electricity connections by 17%. On the other hand, both access to microcredit and the starting up of a local cooperative by CEFA Onlus that reinvests its profits in the local market impact the socio-economic dimension by 69% and 22%, respectively.

Human activities, such as burning fossil fuels for electricity generation, heating, and transport, are the primary drivers of a large amount of greenhouse gases emission. The individual consumers, able to influence the supply chains behind the commodities their chose to fulfil their needs is the driver behind production and, consequently, its impacts. Thus, the active and willing participation of citizens in combatting climate change may be pivotal to address this issue. The present work is aimed at presenting and modelling a novel market-based carbon emission reduction mechanism, called BitCO2, designed to incentivize individual consumption choices toward lower carbon footprints. This mechanism is tested for the Italian private transportation sector thanks to an ad hoc developed System Dynamics model. The Battery Electric Vehicle (BEV) adoption, if compared with the Internal Combustion Engine Vehicle (ICEV) one, cause less CO2 emissions per km travelled. After a certain number of travelled km, a BitCO2 token is assigned to BEV owners for each ton of avoided CO2. This token can be exchanged in a dedicated market and used to get a discount on insurance services. Assuming a Social Cost of Carbon of 9.22 [2.13-22.3] euro/tonCO2eq, model results show that the BitCO2 mechanism would allow for a cumulated CO2 emission reduction of 973 [68.9-5'230] ktonCO2eq over 20 years of operation with a peak of 39.3 [5.34-189] thousand additional BEV registration per year.