Life cycle carbon emission modelling of electrical power systems: The case of Kenya, Rwanda and Tanzania

Abstract

Life Cycle Carbon Emission Modelling of Electrical Power Systems: the case of Kenya, Rwanda, and Tanzania By Enock Lumuliko Chambile, PhD Electrical Power Systems The University of Rwanda, 2022 This thesis has explored the extent to which grid electricity generation and transmission system drivers are designed and operated according to environmental governance (EG) factors, with Kenya, Rwanda, and Tanzania as case study countries. So far, much work exists on environmental life-cycle assessment approaches for electrical power systems neglecting the upstream processes, due to the lack of an effective model for the life cycle inventory (LCI) and method for data collection. This calls for the development of a more effective and simplified LCI model and method for carbon emission data collection including both upstream and downstream processes of the electrical power systems. Nonetheless, most studies use data that do not certainly reflect the country’s existing status. This demands detailed investigations of the up-to-date situation in the study area. This thesis seeks to create awareness, in the electricity sub-sector, of the antagonistic relationship between technology and infrastructural advancements, and their environmental impacts both upstream and downstream. The selected countries are the most appropriate for the study of, both non-renewable and renewable electricity systems due to their environmental geographies, potential power trade, upcoming grid interconnection, different generation mixes, different transmission losses as well as different system capacities. The thesis specifically attempts to answer the following questions: (i) “Using LCI model, determine to what extent are grid electricity generation, transmission and distribution power system (downstream and upstream) drivers designed and operated according to environmental governance factors?”, (ii) “Using LCI model, determine what would be the impact on the lifetime decarbonization performance of the downstream and upstream power systems if environmental governance factors were considered?” and (iii) “Is there lifetime decarbonization performance relationship between renewable energy sources dominated power system and non-renewable energy sources dominated power systems?”. x The methodology is adopted from the life cycle assessment theoretical framework offered by the international standardisation organisation but expanded to include upstream process considering life cycle carbon emissions. The mixed methods research design is also adopted whereby both quantitative and qualitative techniques have been employed to offer a better thoughtful of epistemology (positivism and interpretivism). The data has been acquired through face-to-face discussions and reviews of consistent published data. All the data acquired has been documented and referenced. Authorisation to the actors and companies directly involved in the study has also been obtained. Where necessary, participant data or participants were fully anonymized while observing all data redistribution procedures from the platform(s). The presented data has been established within the determined system boundary using established life-cycle carbon-emission inventory Excel worksheets of different activity and emission factor data as well as the established base year, the lifetime, and the functional unit. The thesis has been achieved to: Develop the life cycle carbon emissions (LCCE) estimation model of the studied electric power systems and compile an inventory (country-specific data and assumptions) database of an electrical product for a particular grid using the developed LCCE model, as well as carry out life-cycle carbon inventory analysis of both electric power generation sources and transmission losses of each studied grid. The carbon emissions inventory analysis results showed that only Kenyan generation and transmission systems revealed the lifetime decarbonization performance relationship between renewable energy sources dominated power system and non-renewable energy sources dominated power systems. Nevertheless, the results of this study should be taken as indicative and not a conclusive answer as with so many computer models. The study has contributed to the body of knowledge by developing the LCCE model, the LCCE database, and the LCCE analysis results that could be used (by operators, researchers, and policymakers) for planning, estimating, and evaluating the environmental performance of the studied power generation and transmission systems. Further studies need to be conducted to cover more countries in all African power pools, more system dynamic impact analysis, and a wide range of environmental parameters such as wildlife species abundances and diversity (in both aquatic and terrestrial environment systems), and non-greenhouse gases emission.