Quality in healthcare service is essential in giving rural dwellers a good standard of living. It has been established that many rural locations in Sub-Saharan Africa away from the grid connection have difficulty accessing electricity. The inaccessibility of reliable energy and essential medical equipment was the leading barrier to improved healthcare delivery in these rural locations. The deficiency of basic medical equipment to power essential services due to limited or unreliable electricity access has reduced rural healthcare workers’ care capabilities, resulting in higher mortality rates. This paper, therefore, reviews the existing energy solutions for rural healthcare facilities, thereby analysing different approaches and the geographical energy mix and ascertaining the effectiveness of various techniques and energy mix as solutions to effective healthcare delivery in healthcare centres. Hybrid Renewable Energy Sources (HRES) microsystems, like microgrids incorporated with solar panels and battery, is identified to ensure higher and more reliable energy access in rural healthcare centres. At the same time, the adoption of Demand Side Management (DSM) in the HRES deployment in countryside healthcare facilities is reported to decrease the initial cost of installation and improve efficiency. Lastly, in improving energy access, rural electrification planning is achieved through modelling tools related to energy access modelling.
25 September 2020 in IET Generation, Transmission & Distribution
To relieve congestion due to open‐access feature in competitive power system framework, utilities plan flexible alternating current transmission systems (FACTS), ensuring improved utilization and performance of the transmission infrastructure. However, high‐investment cost restricts implementation to single type of FACTS' planning in a time. Therefore, successive planning of another FACTS to delay transmission expansion results in multi‐type FACTS planning. Consequently, to optimise performance, subsequent planning must coordinate with existing FACTS. The main objective of this study is to implement coordination of multi‐type FACTS for available transfer capability (ATC) enhancement. A hybrid real power flow performance index (PI) and particle swarm optimisation (PSO), coordinate thyristor control series compensator (TCSC) in the first planning horizon with static synchronous series compensator (SSSC) and unified power flow controller (UPFC), in the second horizon. The PI–PSO‐based multi‐type FACTS coordination improves ATC of multilateral power transfers in a standard 9‐buses test network. Results show that multi‐type FACTS achieved higher ATC; such that enhanced ATC by TCSC–SSSC ranges between 8.06–69.34% while the TCSC–UPFC ranges between 11.85–71.59% for various power transfer transactions. A comparison of the three coordination schemes shows that the scheme with more decision parameters provides superior loadability and transfer capability improvement.
1 February 2019 in Engineering Science and Technology, an International Journal
This paper takes a cursory look at the problem of inadequate power supply in the rural healthcare centres of a developing country, specifically Nigeria, and proffers strategies to address this issue through the design of hybrid renewable energy systems combined with the existing unreliable grid in order to meet the healthcare load demand, thus ensuring higher reliability of available energy sources. The simulations, analysis and results presented in this paper are based on meteorological data and the load profiles of six selected locations in Nigeria, using which hybrid grid-connected systems integrating diesel, solar and wind energy sources are designed with configurations to give optimum output. The optimised design configurations in the considered case study, Ejioku, Okuru-Ama, Damare-Polo, Agbalaenyi, Kadassaka and Doso, produce very low energy costs of of 0.0791 $/kWh, 0.115 $/kWh, 0.0874 $/kWh, 0.0754 $/kWh, 0.0667 $/kWh and 0.0588 $/kWh, respectively, leveraging solar and wind energy sources which make higher percentage contributions at all sites. The load-following-dispatch strategy is adopted at all sites, ensuring that at every point in time, there is sufficient power to meet the needs of the healthcare centres. Further works on this topic could consider other strategies to optimise general energy usage on the demand side.
Time-frequency analysis is an evolution of mathematical ideas and concepts used in the analysis of time-varying spectra of signals in order to cater for various problems in different fields. One of such fields of interest is radar related problems. This paper reviews the recent advancements made in this area with the aid of time-frequency (t-f) tools within the last year till date, it presents a good starting point for researchers interested in radar applications of t-f analysis. It investigates the nature of tools used, the problem(s) solved, advantages and limitations of method used where applicable. Illustrations of some basic concepts are also presented when necessary. The short time Fourier transform (STFT) and Wigner-Ville distribution (WVD) still remain the two main key time-frequency distributions that have undergone various modifications to mitigate radar related problems. It is also seen that considerable amount of most recent works deals with micro-Doppler identification and radar signals analysis.
This paper considers the damping of the local-mode power system oscillation using Lead-Lag power system stabilizer (PSS). Thus, a simple single-machine infinite-bus power system is used. The Lead-Lag PSS parameters are tuned using Genetic Algorithm Optimization (GAs). Simulation results are presented with and without the proposed controller. Also, a comparison study is presented when using the conventional Lead-Lag PSS, Simple Genetic Algorithm Optimization-based PSS, and when using the Improved Genetic Algorithm Optimization-based PSS. The results obtained show the significance of using improved Genetic Algorithm Optimization as compared to using conventional PSS and Simple Genetic Algorithm based PSS.