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All Journal Asian Journal of Science, Technology, Engineering, and Art
Ibekwe Arinze Ignatius
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Arts Computer Science & IT Engineering Social Sciences

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Assessment of High Electricity Tariffs on Government Hospitals in Anambra State: Challenges, Cost Implications, Way Forward, and Policy Options for Affordable Energy Ibekwe Arinze Ignatius; Josephat Chukwudi Akabuike; Ibekwe Adaobi Maryann; Nwauzor Chioma Vivian; Ibekwe Chukwubuikem Francis; Nkiru Ugochukwu Akabuike
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 1 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i1.8116

Abstract

The deregulation of the Nigerian power sector and the subsequent 2024 Multi-Year Tariff Order (MYTO) issued by NERC have precipitated a financial crisis for public institutions, as illustrated by the reclassification of government hospitals in Anambra State into “Band A” feeders, which triggered a tariff surge from ~₦68/kWh to ~₦217/kWh and effectively disregarded the social service nature of healthcare. This study assesses the financial and operational impact of these high electricity tariffs on government hospitals in Anambra State, specifically NAUTH and COOUTH, and validates the observed patterns against national trends. Adopting a mixed-methods research design, the study combines a descriptive cross-sectional survey of 12 key administrative informants with a retrospective cost analysis of energy bills from 2023 to 2024, complemented by a comparative digital verification using internet archives to benchmark local findings against reported energy crises in other tertiary institutions such as UCH Ibadan and LUTH. The findings establish a 230.8% increase in grid energy costs after April 2024; despite the “Band A” service promise, the hospitals still rely on diesel generators for 4–6 hours daily at an average cost of ₦1,400 per liter, resulting in energy expenditures consuming 40–60% of hospital overheads. Internet-based comparative analysis confirms that this represents a systemic national crisis, as peer institutions face the risk of disconnection due to similar debt profiles. The study concludes that the current commercial tariff model is unsustainable for public health parastatals and underscores the need for urgent regulatory and infrastructural responses. It recommends immediate intervention by the Anambra State Electricity Regulatory Commission (ASERC) to implement a subsidized “Social Health Tariff,” alongside a strategic migration to embedded solar-hybrid mini-grids to safeguard energy security and ensure the financial viability of affordable healthcare delivery.
Design and Assessment of a 3.7 KW Off-Grid Biogas Power System for Economic Optimization in Medium-Scale Nigerian Farming Ibekwe Arinze Ignatius; Abonyi Emeka Sylvester; Chidiebere Nnaedozie Muoghalu; Ugochukwu Edebeani Anionovo
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 3 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i3.8907

Abstract

The removal of fuel subsidies in Nigeria in May 2023 sharply increased energy costs, with Premium Motor Spirit (PMS) and Automotive Gas Oil (AGO) prices rising by more than 200%, thereby intensifying operating cost pressures in the agricultural sector, particularly for small- and medium-scale farms dependent on fossil-fuel-based power. This study evaluates the feasibility of an off-grid biogas power system as a cost-mitigation strategy through the design, capacity optimization, and techno-economic assessment of a 3.7 kW biogas-based electricity generation system. A representative medium-scale livestock farm comprising 10 cattle, 20 pigs, and 500 poultry birds was analyzed. The proposed system integrates a 30 m³ fixed-dome anaerobic digester operating under a co-digestion regime using mixed swine, bovine, and poultry substrates, with a total daily feedstock input of approximately 235 kg. System modeling indicates a biogas production potential of 13.15 m³ per day, which, when supplied to a dual-fuel generator, produces an average electrical output of 22.35 kWh per day and supports continuous operation of a 3.7 kW load for up to six hours. The economic evaluation shows an approximately 95% reduction in monthly energy expenditure, from ₦319,000 to ₦14,000, while digestate utilization as organic fertilizer provides an additional estimated monthly revenue of ₦168,000. Financial indicators reveal a payback period of 5.5 months and a gross profit increase exceeding 100% within the first year of operation. Performance assessment further demonstrates benefits in electrical output, fossil fuel displacement, operating cost savings, investment recovery, environmental impact, and waste treatment efficiency. The study concludes that small-scale biogas power systems of this capacity are technically robust and economically viable for decentralized agricultural energy supply in Nigeria, contributing to rural energy security, emission reduction, and circular resource utilization.
Optimization of Photovoltaic System Sizing Using Artificial Intelligence for a 20 KW Hybrid Solar Installation Ibekwe Arinze Ignatius; Callistus Simeon; James Chukwuemeka
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 4 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i4.9695

Abstract

The growing demand for reliable and cost-effective electricity has accelerated the adoption of solar photovoltaic (PV) systems; however, inappropriate system sizing can lead to excessive installation costs through oversizing or unreliable power supply through undersizing. This study aims to optimize the sizing of a PV power system within the 10–20 kW capacity range using an artificial intelligence-based approach. A detailed PV system model incorporating half-cut monocrystalline PV modules and lithium iron phosphate (LiFePO₄) battery storage was developed in MATLAB/Simulink. Solar irradiance and ambient temperature were incorporated to represent realistic operating conditions. Particle Swarm Optimization (PSO), implemented in Python, was used to determine the optimal PV array configuration and battery capacity. System performance was evaluated based on energy output, Loss of Power Supply Probability (LPSP), and Net Present Cost (NPC). The simulations showed that PV output increased with solar irradiance, whereas module efficiency declined as temperature increased. The optimization identified a configuration of 32 PV modules, comprising eight modules in series and four parallel strings, combined with a battery capacity of approximately 690 Ah. This configuration produced a system capacity of approximately 16 kW, achieved an LPSP of 0.006, and reduced system cost relative to larger configurations. These findings demonstrate that PSO-based optimization can improve the technical and economic performance of PV system sizing by balancing energy reliability, storage capacity, and system cost. The study provides an integrated optimization framework for designing reliable and cost-efficient PV–battery systems under variable environmental conditions.
Co-Authors Abonyi Emeka Sylvester Callistus Simeon Chidiebere Nnaedozie Muoghalu Ibekwe Adaobi Maryann Ibekwe Chukwubuikem Francis James Chukwuemeka Josephat Chukwudi Akabuike Nkiru Ugochukwu Akabuike Nwauzor Chioma Vivian Ugochukwu Edebeani Anionovo