Project – Impact of Smart Energy Management Systems on Electricity Consumption in Selected Manufacturing Firms in Ogun State

CHAPTER ONE

INTRODUCTION

1.1 Background to the Study

Energy is a fundamental input in modern industrial production because virtually every manufacturing activity requires electricity to power machinery, operate production lines, provide lighting and ventilation, control industrial processes and support information and communication systems. The manufacturing sector is therefore highly sensitive to the availability, reliability, cost and efficiency of electricity. Globally, industry accounts for the largest share of final energy consumption, making improvements in industrial energy efficiency an important component of sustainable production and energy security. The International Energy Agency (IEA, 2025) reported that industry accounted for nearly 40% of global final energy demand in 2024 and emphasized process optimisation, energy management systems, efficient equipment and digital technologies as important pathways for improving industrial energy efficiency. In the Nigerian context, electricity is similarly critical to manufacturing, although firms continue to face challenges associated with unreliable supply and high energy costs (Asaleye et al., 2021).

The importance of electricity to manufacturing is particularly significant in developing economies such as Nigeria, where inadequate and unreliable public electricity supply has historically compelled firms to depend on alternative sources of electricity, including diesel and petrol generators. Such dependence increases production costs and may influence the quantity of electricity consumed by firms because companies often operate several electricity sources simultaneously. Akinwumi, Moses and Akinbami (2006) found that unreliable electricity supply in Nigeria led manufacturing firms to acquire generating sets as alternative sources of power, while Asaleye et al. (2021) established that electricity consumption has important implications for manufacturing-sector performance in Nigeria. These circumstances demonstrate that improving electricity consumption in manufacturing requires more than increasing supply; it also requires systems that enable firms to monitor, control and optimise how available electricity is used.

Smart Energy Management Systems (SEMS) have emerged as an important technological approach for addressing inefficient energy use in industrial organisations. A smart energy management system combines conventional energy-management principles with digital technologies such as smart meters, sensors, automated controls, data acquisition systems, real-time monitoring platforms, energy analytics and, increasingly, artificial intelligence. These technologies enable firms to collect detailed information about when, where and how electricity is consumed and to use such information to identify waste, abnormal consumption patterns and opportunities for improvement. The IEA (2019) explained that digitalisation can improve energy efficiency by using sensors and smart meters to gather energy data and analytical technologies to convert such data into information that can support changes in energy use. Similarly, the IEA (2025) emphasizes that digitalisation and artificial intelligence can accelerate energy-management improvements in industry by enabling better data collection, analysis and operational optimisation.

The concept of energy management extends beyond simply installing energy-efficient equipment because effective energy performance requires continuous planning, implementation, monitoring, evaluation and improvement. Schulze et al. (2016), in a systematic review of energy management in industry, identified strategy and planning, implementation and operation, controlling, organisational factors and energy culture as key elements of effective industrial energy management. The ISO 50001 framework similarly promotes a systematic approach to improving energy performance through the establishment of an energy management system, energy baselines, energy performance indicators, monitoring, management review and continual improvement. Fitzgerald et al. (2023), using verified data from 83 manufacturing facilities, found that facilities implementing ISO 50001-type energy management systems achieved substantial and persistent energy-performance improvements, demonstrating that systematic energy management can produce more durable results than isolated energy-saving projects.

The relevance of smart energy management becomes even more pronounced in manufacturing environments where electricity is consumed by multiple energy-intensive systems. Motors, pumps, compressors, boilers, refrigeration equipment, heating systems, production machines, lighting and ventilation systems can each contribute substantially to total electricity consumption. Without accurate monitoring, firms may have difficulty determining which equipment or processes account for excessive consumption and where corrective action should be directed. May et al. (2017) observed that energy efficiency in manufacturing requires appropriate methods and tools for energy analysis, evaluation and the identification of energy-saving measures. The International Energy Agency (2019) further noted that smart sensors, advanced controls and data analytics can support the optimisation of industrial processes and enable early detection of inefficient operating conditions. Consequently, SEMS can potentially transform energy management from a largely reactive activity into a continuous, data-driven process.

The Nigerian manufacturing sector has considerable potential for improved energy management because energy inefficiency continues to impose costs on industrial firms. Aiyedun and Adeyemi (2008), in their case study of Nigeria Eagle Flour Mills Limited, found significant energy consumption across electricity, diesel, petrol and lubricants and demonstrated the value of conducting energy audits to understand industrial energy use. Similarly, Abolarin et al. (2015) examined energy-management opportunities in a medium-scale manufacturing industry in Lagos and identified practical energy-efficiency measures, including equipment operating practices and improvements to motor-drive systems. More recent evidence by Afolabi, Adeniyi and Orekoya (2025) indicates a strong positive relationship between energy efficiency and firm-level productivity in Nigeria, reinforcing the argument that reducing inefficient energy use is not merely an environmental concern but can also improve business competitiveness.

Ogun State provides an important setting for examining smart energy management because of its concentration of manufacturing and industrial activities and its close economic relationship with Lagos and other commercial centres in southwestern Nigeria. Manufacturing firms operating in the state are likely to face pressures associated with electricity reliability, production costs, energy intensity and competitiveness. The broader Nigerian experience indicates that firms have adopted different strategies in response to electricity challenges, including self-generation, energy outsourcing and energy-conservation practices. Edomah (2019) identified successive phases of industrial energy transition in Nigeria, including grid dependence, self-generation, energy outsourcing and industrial energy conservation, while noting that cost reduction and business realignment are important drivers of changes in industrial energy use. In addition, Nigeria’s industrial energy-efficiency initiatives have included efforts to support manufacturing firms in implementing energy management systems and energy-efficiency networks, demonstrating the growing institutional recognition of structured energy management within the industrial sector.

The adoption of smart energy management systems may therefore provide manufacturing firms with a practical mechanism for reducing unnecessary electricity consumption while maintaining production activities. Through real-time monitoring, energy dashboards, automated controls, equipment-level metering, consumption forecasting, energy performance indicators and data analytics, firms may be able to identify inefficient processes, reduce avoidable energy losses and improve operational control. However, the effectiveness of such systems may depend on the level of technological integration, management commitment, employee competence, investment capacity, data quality and organisational readiness. The IEA (2025) argues that systematic energy management can deliver continual improvements in energy efficiency and competitiveness, while recent research on industrial energy efficiency has shown that financial constraints, competing investment priorities and weak institutionalisation can limit the translation of energy awareness into sustained efficiency improvements.

Despite the growing international evidence supporting digital and systematic energy management, there remains a need for context-specific empirical evidence on how smart energy management systems affect actual electricity consumption among manufacturing firms in Ogun State. Existing Nigerian studies have examined electricity supply, energy efficiency, energy transitions and productivity, but relatively less attention has been devoted specifically to the relationship between smart, digitally enabled energy management systems and electricity consumption at the firm level in Ogun State. As a result, it is important to investigate whether the adoption of smart meters, real-time monitoring, automated controls, energy analytics and related management practices produces measurable reductions in electricity consumption among manufacturing firms. This study therefore focuses on assessing the impact of smart energy management systems on electricity consumption in selected manufacturing firms in Ogun State.

1.2 Statement of the Problem

Electricity consumption represents a major operational consideration for manufacturing firms because production processes depend heavily on electrically powered equipment and systems. In Nigeria, the challenge is compounded by the unreliability and cost of conventional electricity supply, which has historically encouraged firms to rely on alternative generation sources. While alternative generation may enable firms to maintain production, it can also increase energy expenditure and complicate the management of total energy consumption. Akinwumi et al. (2006) found that unreliable electricity supply compelled Nigerian manufacturing firms to adopt alternative electricity-generation strategies, while Asaleye et al. (2021) reported that electricity consumption has important implications for manufacturing-sector performance. The problem therefore extends beyond access to electricity to the efficient management of electricity resources within manufacturing operations.

A second problem is that some manufacturing firms may lack adequate real-time information concerning how electricity is consumed across individual machines, departments and production processes. Where firms depend primarily on conventional electricity meters and periodic utility bills, management may have limited ability to identify specific sources of excessive consumption, equipment inefficiency or abnormal energy use. Without detailed and timely information, energy-saving decisions may be based on estimates rather than actual operating data. The IEA (2019) noted that digital technologies such as sensors and smart meters can improve energy efficiency by collecting and analysing detailed information about energy use, while May et al. (2017) identified energy analysis and evaluation as essential components of effective manufacturing energy-efficiency management. The absence or inadequate use of these technologies may therefore limit the ability of firms to systematically control electricity consumption.

Another problem concerns the limited integration of energy monitoring with managerial and operational decision-making. Installing energy-efficient equipment or conducting occasional energy audits may not necessarily produce sustained reductions in electricity consumption if firms do not continuously monitor performance, establish energy targets, assign responsibilities and evaluate results. Schulze et al. (2016) established that effective industrial energy management requires an integrated approach involving strategy, implementation, control, organisation and energy culture rather than isolated technical interventions. Similarly, Fitzgerald et al. (2023) found that structured energy management systems can produce deeper and more persistent energy-performance improvements in manufacturing facilities. This raises the question of whether manufacturing firms in Ogun State that employ smart energy-management technologies actually experience improved electricity-consumption outcomes.

The final problem is the lack of sufficient firm-level evidence concerning the effectiveness of smart energy management systems within the specific industrial environment of Ogun State. Although Nigerian studies have established relationships between energy efficiency, electricity consumption and manufacturing performance, and although national programmes have promoted energy management systems among industrial firms, there is still a need to establish whether digitally enabled energy-management practices translate into measurable reductions in electricity consumption among selected manufacturing firms in Ogun State. Afolabi et al. (2025) found that improved energy efficiency is positively associated with productivity among Nigerian firms, while Edomah (2019) showed that industrial energy transitions in Nigeria are influenced by cost reduction and business considerations. However, the specific impact of smart energy-management systems on electricity consumption remains insufficiently established in the local manufacturing context. This study therefore seeks to provide empirical evidence on the extent to which smart energy management systems affect electricity consumption in selected manufacturing firms in Ogun State.

1.3 Aim of the Study

The main aim of this study is to examine the impact of smart energy management systems on electricity consumption in selected manufacturing firms in Ogun State.

1.4 Objectives of the Study

The specific objectives are to:

1. examine the extent of adoption of smart energy management systems among selected manufacturing firms in Ogun State;
2. assess the effect of real-time energy monitoring and smart metering on electricity consumption in the selected manufacturing firms;
3. determine the effect of automated energy controls and energy analytics on electricity consumption in the selected manufacturing firms; and
4. examine the challenges affecting the effective implementation of smart energy management systems in selected manufacturing firms in Ogun State.

1.5 Research Questions

The study will be guided by the following research questions:

1. What is the extent of adoption of smart energy management systems among selected manufacturing firms in Ogun State?
2. To what extent do real-time energy monitoring and smart metering affect electricity consumption in the selected manufacturing firms?
3. What effect do automated energy controls and energy analytics have on electricity consumption in the selected manufacturing firms?
4. What challenges affect the effective implementation of smart energy management systems in selected manufacturing firms in Ogun State?

1.6 Research Hypothesis

The following null hypothesis will be tested at 0.05 level of significance:

H₀: Smart energy management systems have no significant effect on electricity consumption in selected manufacturing firms in Ogun State.

1.7 Significance of the Study

The study will be significant to manufacturing firms because it will provide empirical information on whether smart energy-management technologies can contribute to improved control of electricity consumption. The findings may assist manufacturing managers in determining whether investments in smart meters, sensors, energy-monitoring platforms, automated controls and energy analytics can produce measurable energy-saving benefits.

The study will also be useful to energy managers and facility managers because it will identify the technological and managerial practices that can support better monitoring and control of electricity consumption. The findings may help energy managers develop more systematic approaches to identifying energy losses, monitoring energy performance and establishing appropriate energy-reduction targets.

The study will benefit manufacturing employees and technical personnel by emphasizing the importance of energy awareness, equipment monitoring and responsible energy-use practices. Smart energy systems can generate information that enables employees to understand how operational decisions influence electricity consumption and can therefore encourage more efficient production practices.

The study will also be useful to government agencies and energy policymakers because the findings may provide evidence for the development of policies and incentives that encourage industrial energy efficiency and digital energy-management adoption. This is consistent with the growing recognition that industrial energy management can support competitiveness, energy security and demand reduction (IEA, 2025).

The study will further benefit investors and business owners by providing information concerning the potential relationship between smart energy management and operating costs. Since energy expenditure can affect manufacturing competitiveness, evidence of effective electricity-consumption management may support investment decisions relating to energy-efficient technologies and digital monitoring systems.

Finally, the study will contribute to academic knowledge in energy management, industrial management, engineering, environmental management and business administration. It will provide empirical evidence concerning the application of smart energy-management systems within the Nigerian manufacturing environment and may serve as a basis for future research on industrial energy efficiency, digitalisation and sustainable production.

1.8 Scope of the Study

The study focuses on the impact of smart energy management systems on electricity consumption in selected manufacturing firms in Ogun State. The study will examine smart energy management systems from the perspective of selected technological and managerial components, including:

• smart metering;
• real-time energy monitoring;
• energy sensors;
• automated energy controls;
• energy data collection;
• energy analytics;
• energy-performance monitoring; and
• energy-management practices.

The dependent variable, electricity consumption, will be considered in terms of the management and reduction of electricity use within the selected manufacturing firms.

The study is geographically restricted to selected manufacturing firms in Ogun State, Nigeria. The study will focus on relevant management, technical, production and energy personnel within the selected firms. The findings will therefore be interpreted within the context of the selected manufacturing firms and should not automatically be generalized to all manufacturing firms in Nigeria.

1.9 Operational Definition of Terms

Smart Energy Management System (SEMS): An integrated technological and managerial system that uses digital technologies, data, monitoring and automated controls to measure, manage, optimise and improve energy consumption.

Energy Management System (EnMS): A systematic framework through which an organisation establishes energy policies, objectives, targets, monitoring procedures and continual-improvement processes for improving energy performance.

Smart Meter: A digital electricity-measuring device capable of recording and communicating electricity-consumption information at specified intervals for monitoring and analysis.

Real-Time Energy Monitoring: The continuous or near-continuous collection and display of information concerning electricity consumption to enable timely management decisions.

Energy Analytics: The use of collected energy data, analytical techniques and software tools to identify consumption patterns, inefficiencies, anomalies and opportunities for energy savings.

Automated Energy Control: The use of sensors, control systems and software to automatically regulate energy-consuming equipment or processes according to predetermined conditions or operational requirements.

Electricity Consumption: The amount of electrical energy used by a manufacturing firm or its equipment over a specified period, commonly measured in kilowatt-hours (kWh).

Energy Efficiency: The achievement of a desired level of production, service or output using less energy than would otherwise be required.

Manufacturing Firm: An organisation engaged in the transformation of raw materials, components or other inputs into finished or semi-finished products through industrial processes.

Energy Performance: The measurable results associated with an organisation’s energy use, energy efficiency and energy consumption.

Energy Audit: A systematic examination of energy use and energy-consuming systems within an organisation to identify consumption patterns, inefficiencies and opportunities for improvement.

Industrial Energy Management: The systematic planning, monitoring, controlling and improvement of energy use within industrial or manufacturing operations.

Energy Saving: A reduction in energy consumption achieved through improved technology, operational practices, management systems or behavioural changes without an unacceptable reduction in required output or service.

Project – Impact of Smart Energy Management Systems on Electricity Consumption in Selected Manufacturing Firms in Ogun State