Social innovation for community energy in developing countries – new models and a Mozambican case study

Abstract

In recent decades, the transition from fossil fuels to the use of renewable energy sources has profoundly changed the world's energy landscape. This in turn has given rise to the concept of energy transition based on the principle of the "three-D’s", Decarbonization, Decentralization and Digitalization. The emergence of the concept of community energy suggests a "fourth-D", denoting democratization as a pillar underlying the concept of community energy. This concept is where energy is produced by and for the community, placing the citizen and community at the center as key actors in the entire energy value chain (generation, distribution, consumption, and associated services). This work aims to discuss the social innovation model suitable for the implementation of energy democratization, which leads to the successful penetration of the concept of community energy in developing countries, especially Mozambique, which is a use case study explored in this paper. We explain how this social innovation model can promote socio-economic empowerment, sustainable industrial and human development, and energy inclusion that contributes to environmental balance and social stability in rural communities in Mozambique. The global energy landscape is not uniform in terms of access to energy sources and this debate in developing countries is still relevant and significant, as a considerable number of citizens do not have accessibility to electricity and are still seeking access to it for the first time (energy inclusion). But beyond the social innovation through energy inclusion, we also discuss new innovative modular ways of implementing Distributed Energy Resource (DER) based on typical Photovoltaic (PV) panels and energy storage (batteries). A modular approach for the implementation of smart grids can promote a more cost-effective organic growth, distributing resources more evenly and avoiding oversizing or undersizing of rural electrification systems. Such modularization would also allow new partners or new equipment sets to be added to the infrastructure smoothly. Finally, we suggest the introduction of an AI-based algorithm capable of adapting the smart grid management to new infrastructure modifications (addition of new prosumers or consumers). The algorithm proposed would be able to help control the quality and cost of power for all participants, reduce operation and maintenance costs of the systems, and balance generation and consumption. With that, the suggested modular implementation in conjunction with AI-based smart grid management will provide smart grids that can reduce costs of investment and fair consumption and generation balance that, with time, can promote local sustainable industrial and human development in a virtuous circle to boost social transformation