A System Dynamics Analysis of Cost-Recovery A Study of Rural Minigrid Utilities in Tanzania
Licentiate thesis, 2015
Over one billion people live in poverty around the world. Access to modern energy sources such as electricity is considered important in social and economic development. A number of initiatives have been taken to improve the situation but one billion people still lack access to electricity around the world, most of whom live in rural and inaccessible areas.
One proposed solution to improve electricity access in rural areas is minigrids based on renewable energy sources. Minigrids have been constructed in all parts of the world with various levels of success. A common challenge for the utility’s operating them has been to achieve the ability to cover their own expenses, leading to financial difficulties.
Based on a systemic approach, this work investigates cost-recovery based on a dynamic understanding of the problem. By developing a system dynamics model the problem is analyzed conceptually through a causal loop diagram and mathematically through a stock and flow model. The stock and flow model is then used to investigate the effect different generation and distribution technologies have on cost-recovery.
Through the application of the system dynamics model it is found that construction and planning time together with the cost per connection are both important factors for cost-recovery. When construction and planning times are too long, the utility is not able to handle changes in demand. With a reduced power availability, usage and number of users decrease, creating a negative loop driving down the income. Even though both construction and planning time and cost per connection are found to be important, the results implies that reducing connection cost can have a large impact on cost-recovery, given that the utility has the ability to handle changes in demand.
The work also identifies a possible future area of research where system dynamics modeling is integrated with load modeling and assessments. This could reduce the issues of using a static relationship between electricity and power and thereby possibly yield new insights into the connection between electricity usage, generation source and cost-recovery.