The deployment of renewable energy is considered a necessary step towards sustainability and appropriate mitigation of green house gas emissions. To be effective it must achieve a balance between a diversity of energy sources, locations for deployment and demand points, and transmission and local production. Less industrialized countries have the opportunity to leapfrog fossil based centralized networks for electrification by using appropriate technologies for production and delivery of renewable based electricity. This involves the planning of a new system dependent on interconnected technical, social, economic, and environmental layers.
The use of Complexity Science expands Industrial Ecology’s capability to study these systems by providing tools that take into consideration those interconnections and can capture dynamic mechanisms, social value judgments, competing or complementary objectives, and imperfect economic incentives, while creating descriptive simulations of possible outcomes. Through complexity, Industrial Ecology can be involved in the planning of a system at early stages in a dynamic, bottom-up approach that includes technical, environmental, and social considerations, and the context in which technologies will evolve.
This paper presents an Agent-Based Model that allows stakeholders to test development strategies of electricity supply systems based on renewable energy. The model serves as a robust tool for policy experiments and scenario creation giving decision-makers illustrations of value judgment, path-dependence, and tradeoffs that occur during multi-objective planning and allowing Industrial Ecologist to responsibly participate in the development process. The model is illustrated through the case study of Liberia, West Africa, arguably the least electrified country in the world.