INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025

Economic Framework for Maximising Electricity Theft Recovery

in Distribution Networks

Adebayo Adeyinka Victor¹, Pelumi Peter Aluko-Olokun², Ologunwa Oluyemi Philip³

¹Electrical Department, University of Johannesburg, South Africa

²Department of Electrical and Electronics Engineering, Sheffield Hallam University, Sheffield, South

Yorkshire, United Kingdom

³Dept. of Project Mgt. Technology Federal Uni. of Tech, Akure. Nigeria

DOI : https://doi.org/10.51583/IJLTEMAS.2025.1411000058

Received: 17 November 2025; Accepted: 25 November 2025; Published: 09 December 2025

ABSTRACT

Electricity theft, a type of non-technical loss (NTL), reduces utility revenues, distorts feeder loadings, and

hampers investments in reliability and clean energy. This study presents an integrated economic framework to

maximise recoverable value from theft within distribution networks. The framework combines mechanism

design to align customer incentives through pricing, amnesty programmes, and credible penalties with a portfolio

approach to detection and remediation strategies. These include advanced metering, feeder/DT balancing,

analytics-driven audits, and standardised legal evidence packs, all within budget, legal, and equity constraints.

It models recoveries as the discounted net present value of past back-billing and legitimate future consumption,

guided by key utility KPIs such as recovered NPV per cost, relapse rates, and alarm accuracy. Implementation

follows a three-phase plan: initial pilots, scaling and optimisation, and institutionalisation, supported by

governance structures (RACI, due process, independent audits) and measurement & verification. Examples from

India and Brazil demonstrate that integrating technology, legal processes, and social measures is vital for shifting

incentives away from theft and towards compliance. Ultimately, this approach provides regulators with a

justifiable method to reduce NTL while upholding affordability and public trust.

Keywords: electricity theft; non-technical losses; mechanism design; advanced metering infrastructure;

portfolio optimisation; governance.

INTRODUCTION

Electricity is a crucial national energy resource, and electricity theft poses a significant obstacle to achieving a

stable, reliable supply. Theft of electricity involves unauthorised tampering with meters or bypassing wires,

drastically reducing the thief's electricity costs and ultimately leading to substantial economic losses and

increased safety risks for everyone involved. In certain regions, such as Uttar Pradesh, India, electricity theft

accounts for a remarkably substantial portion of overall power loss, making it a pressing issue for local

authorities. The magnitude of electricity theft across multiple countries and the various drivers of theft affecting

different segments of society remain poorly understood, complicating efforts to devise effective

countermeasures. Addressing this challenge is crucial to enhancing overall energy security and ensuring efficient

utilisation of resources (Xia et al., 2022). Non-technical losses (NTL) refer to significant revenue and energy

losses an electricity supply system experiences that cannot be attributed to physical losses within the network

infrastructure. Hence, revenue-at-risk can arise from various issues, such as billing errors, inaccurately measured

demand, misreported consumption data, meter tampering, and even fraudulent activities (Apata et al., 2022).

The problem of theft recovery within electricity distribution networks has not been systematically addressed,

despite its critical importance across numerous jurisdictions and regions (Adebayo & Ainah, 2024). A specific

analytical framework based on economic variables can provide a robust method for estimating the value of theft

mitigation efforts and evaluating corresponding strategic options to combat these losses effectively. By

www.ijltemas.in

Page 624

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025

implementing this framework, utilities can develop targeted strategies to minimise NTL and enhance their

overall operational efficiency. (Guarda et al.2023)

Electricity is a crucial element in fulfilling basic human needs and is essential to everyday life. Ensuring access

to a stable electrical supply at reasonable, regulated prices is vital to overall well-being and to meeting

fundamental subsistence requirements. Affordability and a dependable, around-the-clock electricity supply are

particularly significant in the early phases of development and play a pivotal role in fostering growth and

improving quality of life (Maka & Alabid, 2022). Information asymmetry and principal-agent dynamics

characterise the interactions of consumers or consumer groups across different segments. Multiple players with

heterogeneous bills, physical bypasses, and wire-swap attachments create enforcement impediments that are

already challenging in segments such as domestic or commercial. Non-technical losses (NTL) refer to revenue

and energy losses experienced by electricity supply systems that are not attributable to physical network losses.

(Yuan et al., 2023)

Legal and Regulatory Foundations

Electricity theft is a deeply undesirable activity that involves the consumption of electrical energy without the

necessary constraints and regulations, and it is illegal in nearly every nation worldwide. There are primarily two

forms of electricity theft that can be distinctly recognised: the first is the act of directly stealing energy from

power lines. In contrast, the second involves tampering with the energy meter to falsify consumption.

Additionally, electricity theft may occur through various unfair or fraudulent practices, including situations in

which providers supply illegal energy sources that bypass the entire transmission system. (Hu et al., 2020). The

term non-technical losses (NTL) encompasses lost revenue in the power distribution domain, arising from theft

and other issues such as unbilled energy, incorrect customer categorisation, and reductions in billing due to

political pressures and interventions. The economic repercussions of power theft are often exacerbated in

developing countries, where various factors heighten vulnerability to such illicit practices, primarily due to harsh

economic conditions and pronounced income inequalities. To illustrate, in South Africa, electricity theft is

reported to cost the industry around R12 billion annually, which amounts to approximately 15% of Eskom’s

total revenue, highlighting the severity and widespread nature of this issue. (Hu et al., 2020)(Mbanjwa, 2017)

Economic Principles and Revenue Recovery

Recovery from electricity theft requires a comprehensive understanding of domicile-level discrepancies among

sanctioned supply, recorded consumption, and assumed normal usage. Structural aspects of markets, institutions,

rights, residuals, authorities, regulations, mandates, obligations, and penalties inform and constrain both

detection and deterrence. Revenue loss is composed of three related components: the price per unit, the fraction

of sanctioned supply deemed non-compliant, and the duration of any such non-compliance. Regulation-

disciplined utilities face the challenge of recovering the extra-market supply loss they capture under the threat

of additional sanctions, inducing only corrective changes in supply, billing, and service; these, in turn, affect

broader economic, social, and welfare objectives. Analysis of the corresponding stage game, involving non-

consented alternative recovery of sanctioned utility supply under detection uncertainty, reveals driver-player

incentive rents arising from the utility's supply distortion (Hu et al., 2020). Given that the requisite detection

features are generally unavailable without widespread deployments, the price drop-deterrent opportunity cost is

optimally maximised via metering regularity and coverage; at a second stage, the detection-target differential

continues to dominate the recovery-profit opportunity assessment.

Measurement, Detection, and Valuation of Losses

Electricity theft is the illegal acquisition of electricity from the electricity supply network. Non-technical losses

include not only theft but also consumption resulting from errors in billing procedures and measurement errors;

consequently, the measurement and valuation of such losses are of great economic significance (Joaquim et al.,

2017). Losses in the energy supply sector are categorised into technical and non-technical losses (Hu et al.,

2020). Technical losses result from factors such as resistance and transmission losses, while non-technical losses

refer to energy distributed but not billed to customers. Non-technical losses are often caused by meter tampering,

www.ijltemas.in

Page 625

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025

fraud, and similar actions. Customer parameters can categorise measurements and loss detection across the

electricity distribution network. These parameters include the level of metering accuracy, the quality of

consumption or customer data, the presence of tampering indicators, and the estimation of the total volume of

non-technical losses. Metering data is fundamental for quantifying and measuring losses. Some companies

collect metering readings from smart devices installed on customers’ premises; however, data from smart meters

is often collected at very low frequency. The management of metering data, therefore, depends on the governance

of the underlying data framework. Alternatively, companies utilise direct injection data from distribution

transformers to estimate the overall volume of distribution to customers. (Ghori et al.2023)

Cost-Benefit Analysis of Recovery Strategies

Cost-benefit analysis aids decision-making for substantial investments, competing alternatives, and uncertain

outcomes. A detailed analysis quantifies capital expenses, operating costs, social costs, and expected benefits,

enabling prioritisation of theft recovery initiatives. Completed projects and deployments of advanced

measurement and metering technologies across regions inform estimations of theft reduction and remain the

primary analytical focus. Assessment of specific components remains speculative, although valuable insights

are provided. Analysis encompasses the initial deployment and subsequent expansions of detection and recovery

programmes, along with periodic updates to metering capability (Pretorius & Gaunt, 2015). Competing policy

options, absent formalised revenue assurance practices, undergo evaluation. Opportunity costs of misallocated

resources, impacts of theft-induced changes to the customer base, and scenario-specific variations in time-to-

detection and recovery rates exert significant influences over break-even thresholds and expected net gains.

Identification of capital and operating investments associated with detection, deterrence, and recovery initiatives

constitutes a preliminary stage in cost-benefit analysis.

The implementation of fully developed detection programmes demands a substantial financial commitment,

while ancillary information gathered during the initial deployment can subsequently lower the cost of detecting

residual theft. Moreover, specific enhanced programmes require only incremental resource allocation and may

achieve cost recovery more rapidly. The expansion of detection frameworks, when circumstances permit the use

of previously acquired information on tampered customers, prioritises this and thus qualifies as a project timing

modification. Established estimates of expected reductions in annual theft from the initial implementation of

detection programmes provide a basis for anticipated benefits. Available experience further guides the

enumeration of anticipated total theft reduction attributable to each policy alternative under consideration

(ESTEBSARI et al., 2016). The principal finding indicates that the expected net gain from pursuing enhanced

employee- or customer-level deterrence and recovery initiatives ranks below that attainable through the

maturation of the initial detection programme. Competing scenarios are thus further compared on the premise

that the first programme is completed before engagement with supplementary options. (Zhang, 2024)

Revenue Assurance and Risk Management

To maximise recovery from electricity theft, an economic actions framework considers the institutional,

regulatory, and operational environment of electric distribution networks. The study assesses financial losses at

risk from theft, the expected value of additional revenue recovered if such losses are reduced, and the efficiency

of recovery strategies. To further assist operators in actively recovering revenue lost to theft, attention shifts to

high-level revenue assurance and risk management. A comprehensive revenue assurance framework guides the

utility in implementing end-to-end controls that reduce non-compliance risks. The framework identifies the risk

of revenue loss as a system-level variable that is universally applicable and of concern to the organisation at the

governance level. Appropriate procedures, governance structures, and performance metrics outline compliance

obligations, opportunities for recovery, and risks associated with additional investment. A technical perspective

briefly examines considerations for measurement technology choices, including upfront costs, ongoing

monitoring and detection capabilities, and operational implications. The additional monitoring capacity offered

by automated distribution networks and the effect of extended time between theft occurrence and detection on

overall loss are also discussed (Lateefat & Bankole, 2023). Risk-sharing arrangements include insurance

contracts to safeguard against high-impact, low-probability events, external contingency-response capabilities

www.ijltemas.in

Page 626

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025

to aid in re-establishing normal operations, and mitigation measures for the regulatory, product, and brand-

reputation component of income at risk.

Technical Considerations in Distribution Networks

Utilities deliver electricity to consumers through a vast distribution network, making massive investments in the

grid with no ability to monitor its use once it leaves substations. Despite extensive efforts to detect electricity

theft, technical and non-technical losses remain endemic globally (Hu et al., 2020). The casing of tracking

devices, concurrent load studies, and the installation of a theft-detection system on the electricity meter are the

most common approaches for detection. Utilities face the challenge of selecting appropriate technologies to

detect electricity theft while balancing the magnitude of theft and operational costs. Different technologies can

yield different results in detecting electricity theft. Automatic Meter Reading is widely used equipment for

detecting electricity theft in many countries. Lack of attention to the recovery of expenditure in the development

and exploitation of intelligent metering systems for detecting electricity theft manifested in diverse influences in

several regions (Joaquim et al., 2017). The technologies for detecting electricity theft in these two developments

can be categorised into two main groups: direct and indirect detection methods, which differ in their detection

capabilities.

Policy Instruments and Incentive Alignment

Reliable electricity is a foundational input for modern growth, trade, and digital services. As technological

progress accelerates and systems incorporate more variable renewable energy, efficient distribution and credible

billing become even more critical. However, theft via bypassing, tampering, illegal connections, or meter

damage remains a global disruptor (Cavraro et al., 2024). Non‑technical losses (NTL) are material: estimates

attribute roughly a quarter of global energy output, about twelve per cent in electricity supply, and roughly

US$35ꢀbillion in annual utility losses to NTL (Brocks et al., 2016). Exposure spans residential through industrial

customers, reflecting heterogeneous ability to pay, perceived detection risk, and the availability of recovery

pathways. NTL erodes value through three channels: direct revenue loss (unbilled energy), upkeep investment

loss (deferred maintenance and asset stress from hidden loading), and overhead loss (higher operating and legal

costs). International reviews indicate that at least 15 countries have theft‑recovery programs, five of which have

nationwide coverage, underscoring both the prevalence of the problem and the diversity of responses (Hu et al.,

2020).

A coherent policy toolkit aligns incentives so that lawful consumption dominates rational alternatives. First,

pricing and tariff instruments should match willingness‑to‑pay at the margin: lifeline blocks or social tariffs for

basic needs; demand‑reflective or time‑of‑use rates for small commercial users; and hybrid credit‑prepay options

that stabilise bills and reduce arrears. Second, advanced metering infrastructure (AMI) instruments,

distribution‑transformer and feeder metering, and tamper‑evident enclosures increase the probability and speed

of detection while supporting accurate back‑billing. Third, enforcement and legal instruments must deliver swift

certainty within due process: standardised evidence packs, dedicated prosecutor partnerships, and transparent

penalties. Fourth, social and equity instruments, such as amnesty-to-regularisation offers, structured arrears

repayment (e.g., PAYS), and safety upgrades for hazardous wiring, provide viable compliance paths, lowering

relapse. Fifth, contracting and procurement instruments should bundle meter upgrades with communications,

analytics, and service‑level agreements to ensure performance rather than one‑off hardware drops. Finally,

governance and transparency roles and RACI, KPI dashboards, and independent audits sustain legitimacy.

Effective programs combine these instruments as a portfolio. Pricing moderates incentives; AMI and audits raise

perceived detection; legal process makes outcomes predictable; and regularisation preserves future revenue. The

result is maximised recoverable value both past back‑billing and future lawful consumption while protecting

affordability and public trust (Cavraro et al., 2024; Brocks et al., 2016; Hu et al., 2020).

www.ijltemas.in

Page 627

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025

Table 1: Policy Instruments and Incentive Alignment

Incentive Pricing / Metering

Effect Tariffs Tech

&

Enforcem Amnesty

ent / Legal (Social)

PAYS

(Equity)

Contracting / Governan KPIs

Procurement ce (examples)

&

Transpare

ncy

Affordabi Lifeline

AMI; DT/feeder Proportion Time‑bou

Meter‑attac Performance‑b KPI

Share

on

lity

blocks;

TOU

where

beneficia

l; hybrid

credit–

prepay

options

metering;

tamper‑evident

enclosures

ate

penalties;

clear

back‑billin for

g rules

nd waiver hed ased SLAs for dashboards lifeline/soci

of

repayment

plans;

capped

meters,

comms,

analytics

,

al

independen average

audits, arrears

and RACI days;

ownership disconnecti

on rate;

tariffs;

penalties

t

self‑report instalments

ers; safety hardship

fixes for protections

hazardous

;

customer

complaints

per 1k

wiring

Deterrenc Bill

stability

Predictabi signals;

lity

Tamper alarms, Swift‑certa Clear

anomaly inty via re‑entry

Grace

periods;

Data‑quality

SLAs; uptime

guarantees

Due‑proces Audit

s KPIs; hit‑rate;

e

&

analytics, and prosecutor

rules after on‑time

self‑report payment

standardise ; outreach

incentives

service

alarm

transpare feeder

MoUs;

timelines

published

precision/re

call; median

days

nt

pricing

balancing

d evidence campaigns

packs

detection to

adjudication

Sustained Tariff

Complian glide

Continuous

monitoring;

Predictable Post‑amne Retention

Lifecycle

support

Annual

external

Relapse rate

at 6/12/24

adjudicatio sty

tracking;

&

ce

paths to remote

prevent disconnect/reco routes

step‑cha nnect

n; appeal follow‑ups default

upgrades;

verification months;

regularisati

penalty/bonus stakeholder on

;

manageme vendor

;

communit nt

nge

shocks

governance

y partners playbooks

forum

feedback

loop

retention;

NPV

recovered

per $ spent

Notes: Social & Equity is split into separate Amnesty and PAYS columns. KPIs are illustrative and should be

adapted to your regulator and data availability.

Case Studies and Comparative Perspectives.

Electricity theft persists across diverse regulatory settings, but its economic and operational impacts are most

acute in developing contexts where distribution utilities already face tight margins and service‑quality

constraints. As summarised in the attachment, non‑technical losses (NTL) depress billable energy, destabilise

feeder loading, and erode investment capacity, with global evidence indicating substantial and recurrent losses

to utilities and economies (Jindal et al., 2020). The problem’s salience is amplified where affordability pressures,

data scarcity, and uneven enforcement raise the perceived gains from illicit consumption relative to the expected

costs of detection and sanction (Hu et al., 2020). India illustrates the scale and persistence of the challenge. In

high‑loss states and dense urban pockets, widespread tampering, bypass connections, and billing leakages make

periodic raids or blanket inspections insufficient on their own. The attachment notes the prominence of localised

hotspots where theft accounts for a large share of overall losses and undermines reliability improvements.

Utilities, therefore, pair targeted audits with modernisation of metering (AMI/MDM), distribution‑transformer

and feeder metering for energy balancing, and pathway‑to‑compliance programs that replace punitive

back‑billing alone with durable regularisation (e.g., prepayment migration and structured repayment). These

measures aim to raise perceived detection probability while reducing relapse. Complementary policy instruments

stress segmentation by feeder and customer class, so scarce inspection capacity is directed to value‑at‑risk

clusters rather than spread thinly.

www.ijltemas.in

Page 628

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025

Brazil, as framed in the attachment’s comparative discussion, faces similarly entrenched NTL concentrated in

specific urban and peri‑urban zones. The response emphasises technical hardening (tamper‑resistant metering,

remote monitoring), analytics‑guided field operations, and standardised legal evidence packs to shorten

time‑to‑resolution, an approach that seeks “swift‑certainty” within due‑process limits rather than relying solely

on extreme fines. Social‑policy levers (targeted affordability mechanisms and clear regularisation offers) are

deployed to depress incentives for subsistence theft while preserving prosecutorial focus on organised

commercial fraud. Although the precise program mix differs by concession area, the common thread is the

integration of AMI/MDM data with legal process design to raise the expected penalty of theft and improve

collectability. Across both countries, the attachment’s core insight is that technology alone is insufficient: the

most effective portfolios combine (i) data‑driven detection (AMI, feeder/DT metering, anomaly analytics), (ii)

credible enforcement with faster adjudication, and (iii) customer‑centric compliance pathways (prepayment,

structured arrears repayment, and limited‑time amnesties). This triad maximises recoverable value both past

back‑billing and future lawful consumption while reducing relapse and political resistance, aligning with the

broader economic framework advanced in the document (Jindal et al., 2020; Hu et al., 2020). The table below

lists one example country from each inhabited continent. Antarctica has no sovereign countries and is governed

by the Antarctic Treaty System.

Table 2: Example country from each inhabited continent.

Continent

Example

Country

Notes / Reference

Africa

Nigeria

The United Nations geographic scheme lists Nigeria as an African state

(UN Geoscheme; UN Member States list).

Asia

India

Recognised in Asia under the UN Geoscheme; UN Member States list.

Classified in Europe (UN Geoscheme; UN Member States list).

Europe

France

North America Canada

Part of North America per the UN Geoscheme and the UN Member

States list.

South America Brazil

Listed in South America (UN Geoscheme; UN Member States list).

In Oceania, per the UN Geoscheme (UN Member States list).

Oceania

Australia

Antarctica

—

No sovereign countries; governed by the Antarctic Treaty System

(ATS).

- United Nations Statistics Division – Standard country or area codes for statistical use (M49) / UN Geoscheme.

- United Nations – Member States.

- Antarctic Treaty Secretariat – Antarctic Treaty System.

Implementation Roadmap and Governance

Electricity theft diminishes the economic efficiency of distribution utilities and compromises reliability. An

effective response should therefore go beyond ad hoc inspections to a well-structured roadmap with transparent

governance. Based on the attached framework, the roadmap combines analytics, technology, legal processes,

and community engagement to maximise recoverable value while maintaining fairness and legitimacy.

Phase 1 (0–6 months): Establish baselines and run learning pilots. Utilities quantify non‑technical losses (NTL)

at substation, feeder, and distribution‑transformer levels; build a value‑at‑risk heatmap; and launch pilots that

combine AMI/MDM reads, feeder/DT metering for energy balancing, and analytics‑guided field audits. A small

www.ijltemas.in

Page 629

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025

governance cell coordinates legal, field, customer, and data functions, sets initial KPIs (e.g., recovered NPV per

unit cost, relapse rate at 6–12 months), and defines due‑process standards and equity safeguards. This phase also

designs the evidence pack for back‑billing and prosecution to shorten time‑to‑resolution.

Phase 2 (6–24 months): Scale winning portfolios and optimise. AMI rollout is targeted to high‑VaR feeders;

anomaly engines guide audit routing; and customer‑centric compliance pathways (prepayment migration,

structured arrears repayment, and limited‑time amnesties) reduce relapse. Operational playbooks specify

responsibilities (RACI), escalation paths, and safety protocols. A live KPI dashboard tracks financial recovery,

technical loss reduction, customer outcomes, and the timeliness of legal actions. Feedback loops tune inspection

intensity, meter hardening, and outreach based on measured elasticities and collectability.

Phase 3 (24+ months): Institutionalise and assure. Standard operating procedures, training, and regulator‑facing

reports make results durable. Independent audits validate NTL metrics and case handling; stakeholder forums

surface equity concerns; and continuous M&V maintains model fidelity. At this stage, deterrence is stochastic

and continuous (via AMI alarms and randomised audits), not cyclical.

Governance overlay: Across all phases, a formal governance structure aligns incentives and protects legitimacy.

Key elements include a multi‑disciplinary steering group; a RACI matrix for field, legal, customer, and analytics

teams; risk/compliance gates before mass actions; and transparent routes for customer redress. Mathematical

models inform prioritisation (inspection routing, tariff and settlement design, CVaR‑bounded recovery planning)

and ensure that deterrence, capacity upgrades, monitoring, and targeted detection are chosen on expected value

rather than intuition (Kasumba et al., 2025).

Fig. 1: Implementation Roadmap and Governance Overview

Ethical and SocFinal Implications

Conversations surrounding the ethics of energy theft, especially in an unequal world where access to energy is

tied to income, raise questions about redistribution and the boundaries between public and private property. The

South African case demonstrates that electricity theft comprises a combination of non-technical and technical

losses, with the former characterised as a wide-scale, unmeasured load that can be engineered by the utility or

the consumer to go undetected (Mbanjwa, 2017). Societal costs underpin the economics of energy theft. In the

absence of theft, the average cost per kilowatt-hour, paid on a nominal basis, does not vary across different

locations. The cost of theft can be recovered from both overall electricity sales and the eventual limit on theft,

which also supports system security. When Parliament passed a bill into a drought-disaster area, low-income

and low-payment prospects increased, exacerbating the crisis of widespread unlawful connections, electrical

fires, and transformer explosions, prompting intervention on the distribution network itself. A case study of

KwaXimba in eThekwini, KwaZulu-Natal, illustrates how Eskom’s financial burden leads to a cycle of

infrastructure dampening, storage reduction, and ultimately translates into load shedding. Educating

communities about the detrimental cascade of theft to system viability is an indirect yet crucial way to address

www.ijltemas.in

Page 630

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025

theft through various metrics. The approach advocates refraining from quantifying the social costs of electricity

theft, often deemed insurmountable, in favour of stress-testing estimated recovery gains against perceived costs

of improvement to business metrics. Public transport, accessible routes to education, and township residents

indicate that awareness of faulty infrastructure significantly reduces the perceived need for theft. Each municipal

region is expected to experience theft as a function of the consumer’s relationship to the utility, warranting

diligence in evaluating the theft dynamics for electricity recovery. (Hole, 2022)

Unmonitored “free” energy fuels additional societal ramifications: system unsustainability ultimately aligns back

to public sustenance. Structures capable of estimating public accountability enable stakeholders beyond

currency-printing institutions to intervene and recapture sustenance. Such processes quantifiably bolster the

trajectory from non-technical and systemic, unmeasured losses to gains recovery towards urban, sector-

positioned, and corporate welfare. However, the contestable framing of electricity as an inalienable right

invariably arises. Never does the question originate from a value standpoint; rather, it concerns how theft adjusts

business lifelines to continue funding incumbent and emergent businesses (Jindal et al., 2020).

CONCLUSION

Electricity theft is fundamentally an incentives and optimisation problem, not merely an enforcement challenge.

Treating NTL reduction as recoverable-value maximisation clarifies priorities: segment customers and feeders

by value-at-risk; invest in information (AMI/MDM, feeder/DT metering, analytics) to raise credible detection;

pair swift-certainty legal pathways with amnesty-to-regularisation and PAYS-style arrears management to

reduce relapse; and institutionalise governance that balances deterrence with equity. The staged roadmap

proposes baseline & pilots, scale & optimise, and institutionalise, providing a practical sequence for building

durable capability, while KPI-driven M&V and independent audit sustain legitimacy. Comparative evidence

underscores that technology alone is insufficient; enduring results come from aligning tariffs, detection, legal

process, and social supports so that lawful consumption is the rational choice. Utilities that adopt this framework

can boost recovered NPV, improve reliability, and create a transparent, regulator-friendly program that persists

beyond one-off raids or meter swaps, ultimately funding the transition to a cleaner and more resilient distribution

system.

REFERENCES

1. Xia, X., Xiao, Y., Liang, W., & Cui, J. (2022). Detection methods in smart meters for electricity theft: A

survey. Proceedings of the IEEE. researchgate.net

2. Apata, G.; Adebayo, A.; Ainah, P. Transmission Losses in Power Systems: An Overview. In Proceedings

of the 1st ICEECE & AMF (2021), Ibadan, Nigeria, 30 November–2 December 2021; University of

Ibadan: Ibadan, Nigeria, 2022; pp. 1–6.

3. Adebayo, A. V., & Ainah, P. K. Addressing Nigeria's Electricity Challenges: Past, Present, And Future

Strategies. American Journal of Applied Sciences and Engineering. 2024, 5(2), 1-16.

https://doi.org/10.5281/zenodo.12633012

4. Guarda, F. G., Hammerschmitt, B. K., Capeletti, M. B., Neto, N. K., dos Santos, L. L., Prade, L. R., &

Abaide, A. (2023). Non-hardware-based non-technical losses detection methods: a review. Energies,

16(4), 2054. mdpi.com

5. Maka, A. O. M. & Alabid, J. M. (2022). Solar energy technology and its roles in sustainable development.

Clean Energy. oup.com

6. Yuan, X., Yang, Y., Iqbal, A., Gope, P., & Sikdar, B. (2023). A Novel DDPM-based Ensemble Approach

for Energy Theft Detection in Smart Grids. [PDF]

7. Hu, W., Yang, Y., Wang, J., Huang, X., & Cheng, Z. (2020). Understanding Electricity-Theft Behaviour

via Multi-Source Data. [PDF]

8. Mbanjwa, T. (2017). An analysis of electricity theft: the case study of KwaXimba in eThekwini,

KwaZulu-Natal.. [PDF]

9. Joaquim, V., Paulo, E., Rui, M., Victor, M., & Susana, V. (2017). Solutions for detection of non-technical

losses in the electricity grid: a review. [PDF]

www.ijltemas.in

Page 631

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025

10. Ghori, K. M., Imran, M., Nawaz, A., Abbasi, R. A., Ullah, A., & Szathmary, L. (2023). Performance

analysis of machine learning classifiers for non-technical loss detection. Journal of Ambient Intelligence

and Humanised Computing, 14(11), 15327–15342. springer.com

11. Pretorius, J. & Gaunt, C. T. (2015). Cost-benefit analysis of recloser placement for reliability. [PDF]

12. ESTEBSARI, A. B. O. U. Z. A. R., HUANG, T. A. O., PONS, E. N. R. I. C. O., & FRANCESCO

BOMPARD, E. T. T. O. R. E. (2016). Electricity Infrastructure Enhancement for the Security of Supply

against Coordinated Malicious Attacks. [PDF]

13. Zhang, Y. (2024). Corporate R&D investments following competitors' voluntary disclosures: Evidence

from the drug development process. Journal of Accounting Research. ssrn.com

14. Lateefat, T. & Bankole, F. A. (2023). Automation-Driven Tax Compliance Frameworks for Improved

Accuracy and Revenue Assurance in Emerging Markets. shisrrj.com

15. Cavraro, G., Comden, J., & Bernstein, A. (2024). Feedback-Optimised Incentives for Distribution Grid

Services. [PDF]

16. Brocks, A., Nyangon, J., & Taminiau, J. (2016). Utility 2.0: A multi-dimensional review of New York’s

reforming the Energy Vision (REV) and Great Britain’s RIIO utility business models. [PDF]

17. Jindal, A., Schaeffer-Filho, A., Marnerides, A., Smith, P., Mauthe, A., & Granville, L. (2020). Tackling

Energy Theft in Smart Grids through Data-driven Analysis. [PDF]

18. Kasumba, D., Nkulu, G., Diambomba, H., Kayembe, M., Tshikala, F., & Banza, B. (2025). Electricity

Theft and Its Impact on Service Quality in Lubumbashi, DR Congo. Energy Engineering: Journal of the

Association of Energy Engineers, 122(6), 2401. researchgate.net

19. Hole, J. W. (2022). … theft and its effects on victims, commerce, and society: Ideal systematic approach

combatting identity theft involving a combination of prevention, education …. wisconsin.edu

www.ijltemas.in

Page 632