Electricity-distribution network operators face several operational constraints in the provision of safe and reliable power given that investments for network area reinforcement must be commensurate with improvements in network reliability. This paper provides an integrated approach for assessing the impact of different operational constraints on distribution-network reliability by incorporating component lifetime models, time-varying component failure rates, as well as the monetary cost of customer interruptions in an all-inclusive probabilistic methodology that applies a time-sequential Monte Carlo simulation. A test distribution network based on the Roy Billinton test system was modelled to investigate the system performance when overloading limits are exceeded as well as when preventive maintenance is performed. Standard reliability indices measuring the frequency and duration of interruptions and the energy not supplied were complemented with a novel monetary reliability index. The comprehensive assessment includes not only average indices but also their probability distributions to adequately describe the risk of customer interruptions. Results demonstrate the effectiveness of this holistic approach, as the impacts of operational decisions are assessed from both reliability and monetary perspectives. This informs network planning decisions through optimum investments and consideration of customer outage costs.

The design of reliable and sustainable rural electrification systems relies on accurate prediction of the electrical load. This paper evaluates the current methods for load estimation and proposes an improved approach for load estimation for off-grid unelectrified rural communities that yields more accurate estimates. Improved accuracy is mainly due to better modelling of the influence of customer habits and gender on the estimated current and future load using the Markov chain process. A program was developed using MATLAB software to generate load profiles. The results show that gender considerations have a significant impact on load profiles and that the Markov chain process can suitably be used to determine year-to-year load profiles by incorporating the effect of changes in customer habits on the estimated load. The results from the case study on energy consumption in rural community households showed an increase in average daily consumption when gender was considered during load estimation. The peak consumption when gender was considered was about 50% higher than the value for when gender was not considered.

Electricity distribution network operators face several operational constraints in the provision of safe and reliable power given that investments for network area reinforcement must be commensurate with improvements in network reliability. This paper provides an integrated approach for assessing the impact of different operational constraints on distribution network reliability by incorporating component lifetime models, time-varying component failure rates as well as the monetary cost of customer interruptions in an all-inclusive probabilistic methodology that applies a time-sequential Monte Carlo simulation. A test distribution network based on the Roy Billinton test system is modelled to investigate the system performance when overloading limits are exceeded as well as when preventive maintenance is performed. Standard reliability indices measuring the frequency and duration of interruptions, and the energy not supplied are complemented with a novel monetary reliability index. The comprehensive assessment includes not only average indices but also their probability distributions to adequately describe the risk of customer interruptions. Results demonstrate the effectiveness of this holistic approach as the impacts of operational decisions are assessed from both reliability and monetary perspectives. This informs network planning decisions through optimum investments and consideration of customer outage costs.

Over 1.5 billion people currently have no access to electricity with many of them living in rural and remote areas that are far away from the main grid most especially in developing countries. Many rural electrification projects do not last beyond the initial funding phase. Metrics to measure sustainability of such projects are still lacking. This paper presents the important factors to consider when evaluating sustainability and proposes an easy to use sustainability evaluation tool kit based on risk assessment approach. The kit was tested against three microgrid projects.

More than 1.5 billion people in the world today do not have access to electricity. In developing countries, most of these people live in rural and remote areas far from the main grid necessitating establishment of off-grid electrical systems such as solar PV microgrids. Establishment of these off-grid systems requires accurate prediction of the load so as to have a sustainable system that can meet the electrical needs of the community fully. An evaluation of the efficacy of the current methods for load estimation has been carried out in this research. Informed by this evaluation, an improved approach is proposed that yields more accurate estimates of the electrical demand for off-grid systems in rural areas. Load characteristics that take account of the influence of gender as well as changes in customer habits on estimated load are investigated using the Markov Chain process. MATLAB software is used to generate the load profiles. The results show that average electricity consumption in a similar village that is already electrified can be used as a sound basis to estimate the consumption in a village without electricity. Moreover it has found that the effect of gender on estimated demand is critical in microgrid design.

Microgrids enable fast electrification of rural communities. Affordability of these community microgrids is essential for their sustainability and effective utilisation of the services they offer. This paper addresses some of the critical elements that have to be considered when designing microgrids for rural communities. The results obtained show that with the right choice of batteries and their specifications and availability of anchor customers the overall cost of electricity can be reduced.