© M.H. Mohamed Hariri et al., Published by EDP Sciences, 2025

1 Introduction

The continuous development in the economy, urbanization, and population growth has contributed to the rise of energy consumption [1]. Concurrently, the combustion of fossil fuels stands as a predominant progenitor of greenhouse gas (GHG) [2]. Hence, Malaysia pledged to cut its GDP's GHG emissions intensity by 45% by 2030 compared to 2005 levels [3,4]. Reducing GHG emissions could be achieved by implementing energy-saving practices, optimizing energy efficiency, and properly utilizing renewable energy sources [5]. The nation's geographical positioning allows it to receive an estimated 400-600 MJ/m² of solar radiation monthly, translating to a prospective solar power generation capacity of up to 6500 MW [6]. In order to promote the nationwide adoption of renewable energy technologies, the Malaysian government enacted pivotal legislative frameworks in 2011 namely the Sustainable Energy Development Authority Act and the Renewable Energy Act [2,3,6]. The government introduced the Feed-in Tariff (FiT) program in 2011, which subsequently transitioned to the Net Energy Metering (NEM) scheme in 2016, undergoing further revisions and updates in 2019. These policy evolutions collectively aim to propel Malaysia towards its national objective of achieving 20% renewable energy in its total installed capacity by 2025 [1,3,6,7]. This initiative facilitates both commercial and residential electricity consumers in generating renewable energy, enabling them to sell any surplus power back to the national utility provider, Tenaga Nasional Berhad (TNB). Such a mechanism actively incentivizes various sectors to generate their own electrical power from renewable resources thereby fostering a more resilient and sustainable national energy landscape. Recent advancements in Malaysia's renewable energy policy have seen the implementation of three distinct iterations of the NEM scheme, specifically NEM 1.0 (2016), NEM 2.0 (2019), and NEM 3.0 (2021). The most recent scheme, the NEM 3.0 program, formally launched on December 29, 2020, is designed to broaden opportunities for electricity consumers to integrate solar PV systems onto their premises' rooftops, thereby maximizing savings on their electricity bills. The cumulative additional quota allocation under NEM 3.0 has been expanded to 1050 MW, with its implementation commencing effectively from 2021 and extending through 2023 [6,7]. In 2023, Universiti Sains Malaysia (USM) Engineering Campus formally registered under this scheme with the primary objective of realizing reductions in its monthly electrical expenditures through the strategic installation of a Grid-Connected Photovoltaic (GCPV) System across designated buildings. This initiative is particularly timely given the sustained decline in the cost of PV systems over recent years, rendering them increasingly economically viable and accessible for installation [8,9].

This research evaluates the NEM 3.0 scheme for commercial buildings within the USM Engineering Campus, helping Malaysians to understand the practical NEM operational mechanism and its effects on significant economic parameters [10]. Existing research work has mainly concentrated on technical advancements for small or large-scale PV systems under older energy policies. This research analyses the financial feasibility of a commercial-sized rooftop PV system under the recently promulgated 2021 regulatory framework as shown in appendix Figure A.1. This research provides guidance for consumers regarding diverse electrical tariff structures, prevailing PV system costs, and economic evaluation methodologies relevant to the NEM 3.0 scheme. It also incorporates an analysis of the power quality aspects at the GCPV system at the selected premises. A unique contribution of this research is the definitive identification that the observed power factor degradation was not a direct consequence of the solar PV system itself, but rather stemmed from the suboptimal condition of pre-existing capacitor banks. Table 1 offers a comparative overview of the established policies within Malaysia's renewable energy sector implemented to date.

2 Net energy metering scheme

2.1 Net energy metering

Net Energy Metering (NEM) has emerged as a locally recognized and effective mechanism for stimulating the widespread adoption and installation of photovoltaic (PV) systems, particularly within Malaysia's commercial sectors. This research undertakes an inclusive economic analysis of the NEM scheme with a focused examination of its implementation at the USM Engineering Campus. Under the NEM scheme, utility customers are allowed to offset their energy consumption with the electricity generated by their solar PV systems, effectively crediting their generated power against the main utility retail rate. The origin of the NEM framework can be traced to its design as a strategic response to address various challenges inherent in the preceding Feed-in Tariff (FiT) scheme. In its initial operational phase, the NEM scheme was structured to prioritize the self-consumption of energy generated from PV systems by consumers. Any excess energy produced by the PV system beyond immediate consumption requirements was then permitted for export to the national grid. Under this arrangement, the selling price of exported energy to the grid was set at MYR 0.31/kWh, a rate demonstrably lower than the utility electricity tariff, which typically exceeded MYR 0.50/kWh. To accurately measure and account for the bidirectional flow of energy, a specialized bidirectional meter is invariably employed [1–4]. The initial implementation of the first NEM scheme witnessed a constrained rate of PV system installations. This observation prompted the subsequent introduction of NEM 2.0 in July 2018, designed to enhance the scheme's attractiveness and efficacy. A key feature of NEM 2.0 was the provision for a one-to-one offset mechanism, signifying that each 1 kWh of power exported to the grid could directly balance an equivalent 1 kWh value of grid electricity on the subsequent utility bill. The total allocated capacity for NEM 2.0 amounted to 500 MW, encompassing a broad spectrum of sectors including residential, commercial, industrial, and agricultural, each with specific capacity limitations for both single-phase and three-phase systems [4,5]. NEM 3.0 introduces further refinements. This scheme enables consumers to prioritize the utilization of their self-generated solar PV energy with any residual excess energy being exported to TNB at a one-to-one cost offset. The NEM 3.0 designates a cumulative quota of 500 MW, strategically apportioned across three distinct sub-programs, as delineated in Table 2, namely the NEM Rakyat (catering to residential installations, with a 100 MW quota), NEM GoMEn (dedicated to government agencies, also with a 100 MW quota), and NEM Net Offset Virtual Aggregation (NEM NOVA, designed for commercial and industrial sectors, allocated a substantial 300 MW). Each of these programs is characterized by specific capacity limitations and distinct offset policies. It is important to differentiate these from “Self-consumption” (SELCO), a scenario where energy is generated exclusively for individual consumption, and any surplus energy is explicitly prohibited from being transmitted to the grid.

For the case of the USM Engineering Campus, which operates under the NOVA scheme, any excess PV energy generated is exported to TNB (the national utility provider) at the prevailing System Marginal Price (SMP) rate. The offset period for this arrangement is strictly limited to ten years. Subsequent to these ten years, the USM Engineering Campus will no longer be eligible to offset its energy consumption with the electricity generated from its PV system. To comprehensively ascertain the economic feasibility of the NEM 3.0 scheme for the USM case study, it is imperative to conduct a rigorous economic investigation. This investigation must meticulously consider historical energy consumption data and thoroughly analyze the details of net metering policies. A rapid payback period coupled with a robust and favourable financial model would serve as compelling indicators of a viable future investment opportunity within the renewable energy sector. Furthermore, a detailed exploration of available financial incentives and governmental support mechanisms specifically tailored for renewable energy projects could significantly augment the project's overall attractiveness and viability.

2.2 PV characteristic

Photovoltaic (PV) systems fundamentally operate by converting incident sunlight directly into electrical energy. Crucial to this understanding are rigorous investigations into the interrelationships between the Power-Voltage (P-V) and Current-Voltage (I-V) characteristics of PV cells, with a particular emphasis on explaining the differential impacts of solar irradiance and ambient temperature on PV energy generation. The classification of PV systems includes systems that utilize a PV-grid connection for energy storage purposes, stand-alone PV systems that rely exclusively on battery storage, and hybrid systems that ingeniously combine both approaches [7]. The operational efficacy of a PV cell is notably susceptible to meteorological factors, predominantly solar irradiance and the surface temperature of the PV module itself [12]. It is noteworthy that excessively high irradiance levels can absurdly result in a decrease of the fill factor (FF) due to enhanced recombination losses within the cell [13]. Conversely, a reduction in solar irradiance precipitates a decrease in both the output current and voltage of the solar cell. Concurrently, an increase in cell temperature, while causing a marginal rise in output current, leads to a significant decrease in output voltage, culminating in a net reduction in output power. These intricate relationships and their effects on PV cell performance are graphically represented in Figures 1 and 2, respectively.

Recent advancements in research underscore the critical importance of the P-V and I-V characteristics of PV cells when subjected to diverse irradiance and temperature conditions. Such an understanding is indispensable for the continued optimization of PV system performance.

Fig. 1 Effect of irradiance on solar cell I-V curve [14].

Fig. 2 Effect of temperature on solar cell I-V curve [14].

2.3 Power factor

The power factor (PF) is defined as the ratio between the real power and the apparent power consumed by an electrical load. For purely resistive loads, the voltage and current waveforms are inherently in phase, consequently yielding a power factor of unity [15]. However, the presence of capacitive and inductive elements introduces a phase displacement between the voltage and current. This phase difference results in a non-unity power factor, wherein the voltage either leads or lags the current. Most grid-connected photovoltaic (GCPV) inverters are specifically configured to inject only active power into the grid, typically operating at a unity power factor. This operational characteristic inherently leads to a reduction in the overall system power factor, as the grid is then required to supply a diminished amount of active power while the demand for reactive power remains unchanged [15]. When a PV system is integrated, the active power generated by the system is directly supplied to the load, thereby diminishing the active power demand from the utility grid; nevertheless, the reactive power demand from the grid persists at its original level [16]. This phenomenon invariably results in a decrease in the power factor at the point of grid connection, which can lead to financial penalties for the consumer. Despite these challenges, several engineering approaches exist to mitigate the observed power factor degradation. The PF can be expressed by the following relationship;

$$Powerfactor=\cos \left(\theta \right)$$(1)

where θ (theta) denotes the phase angle between the real power (P) and the apparent power (S). Generally, the power factor tends to decline following the installation of a GCPV system, a phenomenon attributable to various factors. To counteract these adverse impacts on system power quality and ensure optimal operational performance, PV systems require careful design, sophisticated control mechanisms, and continuous monitoring to effectively address and remediate any arising power quality issues.

3 Methodology

3.1 Research workflow

The initial phase involves the utilization of PVsyst software to model and simulate the PV system's performance based on the collected data. The payback period for the investment is calculated using established mathematical formulas. The subsequent phase entails a comprehensive assessment of the system's performance. This is achieved by conducting a comparative analysis between the simulated energy production data and the actual energy generated post-GCPV installation. This assessment involves calculating the associated cost savings after the GCPV system has been commissioned. Furthermore, on-site inspections are deemed crucial to identify and address any operational issues, particularly those pertaining to the system's power quality.

3.2 Project site background

The economic assessment of this research is to evaluate the design and construction of GCPV systems deployed across multiple buildings within the campus. The main aim is to actively participate in and implement national renewable energy programs, reduce the campus's reliance on conventional utility supplies, and ultimately, lower monthly electricity expenditures. The installed GCPV system operates under the regulatory framework of the NEM 3.0 scheme, specifically under the NOVA Category B Scheme. The methodological approach involves several key steps such as comprehensive data collection pertaining to available solar energy resources at the site, the development of detailed monthly load profiles for the campus, the modelling of the GCPV system incorporating specific arrays and inverters, and finally, a thorough economic analysis aimed at assessing the project's feasibility within the NEM policy context. Figure 3 provides a schematic representation of the inverter SG110CX circuit diagram, highlighting its essential electronic and electrical components, including Maximum Power Point Trackers (MPPT), AC relays, and filters. This particular inverter model is representative of the types employed at the USM Engineering Campus.

Figure 4 illustrates the average daily solar irradiation data recorded at the USM Engineering Campus. The observed pattern indicates an increase in irradiation commencing around 8:00 AM, reaching its peak at approximately 1:30 PM, and subsequently exhibiting a gradual decline until midnight. The period of optimal irradiation, exceeding 800 W/m², extends for approximately 6 hr each day, spanning from around 10:00 AM to 4:00 PM. The minor fluctuations are occasionally observed during this peak period, which are most likely attributable to transient adverse weather conditions such as cloud movements and others.

Fig. 3 Inverter SG110CX circuit diagram.

Fig. 4 The average daily solar irradiation data at the USM Engineering Campus.

3.3 PVsyst software

PVsyst is a widely recognized software application specifically engineered for the simulation and design of various PV system configurations as shown in appendix Figure A.2. The software leverages extensive internal databases that encompass a wealth of geographical, meteorological, and PV component data, including detailed specifications for PV modules and inverters. Meteonorm-8.1 data was utilized in this research for the accurate modelling of the GCPV system installed on campus. While other analytical tools such as MATLAB, HOMER, and PVWATT are available for PV system sizing and analysis, PVsyst was specifically selected for this research due to its comprehensive technical specifications and its inherent flexibility in PV module selection [7,17]. The simulation process in PVsyst involves defining system variations, followed by the selection of critical orientation parameters such as field type, tilt angle, and azimuth angle. Subsequently, the appropriate inverter and PV module types are chosen. If specific datasheets are not pre-loaded, manual definition of these components is accommodated, as detailed in appendix Figure A.3. Adjustments to the quantity of PV modules are performed by modifying the number of inverters, strings, and series modules to optimize system configuration. For this research, thirteen simulations were conducted, each corresponding to a specific building within the USM Engineering Campus. The energy production data from each building will then be aggregated to determine the total annual output of the entire GCPV system. The resulting report will furnish a forecast of anticipated energy production over a 25-year operational lifespan, incorporating relevant degradation factors associated with solar panel aging.

3.4 Annual savings

Annual savings are defined as the cumulative amount of money saved on the electrical bill over twelve months following the installation of the GCPV system. These savings are expressed in Ringgit Malaysia per year (RM/year). To evaluate the economic performance of the installed GCPV system, Equations (2)–(5) are employed. Specifically, these equations facilitate the calculation of both payback times and annual monetary savings. Equation (2) provides an estimation of the hypothetical electricity bill in the absence of the GCPV system. Equation (3) is utilized to compute the new Imbalance Cost Pass-Through (ICPT) charge applicable to the total load demand, assuming the PV system had not been installed. The annual savings are precisely quantified by calculating the difference between the newly estimated TNB bill and the actual current solar bill for a single month, and then extrapolating this value over 12 months [18,19]. The relevant mathematical formulations are presented as follows;

$$\mathit{Electrical}\mathit{Bill}\left(\mathit{RM}\right)=\mathit{Total}\mathit{Load}\mathit{Demand}\left(\mathit{kWh}\right)\times \mathit{Tariff}\mathit{Rate}\left(\mathit{RM}/\mathit{kWh}\right)-\left(\mathit{TNB}\mathit{Load}\mathit{Demand}\left(\mathit{kWh}\right)\times \mathit{Tariff}\mathit{Rate}\left(\mathit{RM}/\mathit{kWh}\right)\right)+\mathit{Current}\mathit{TNB}\mathit{Bill}\left(\mathit{RM}\right)+\mathit{Net}\mathit{Offset}\left(\mathit{RM}\right)$$(2)

$$\mathit{ICPT}\mathit{Charge}\left(\mathit{RM}\right)=\mathit{Total}\mathit{Load}\mathit{Demand}\left(\mathit{kWh}\right)\times \mathit{ICPT}\mathit{Rate}\left(\mathit{sen}/\mathit{kWh}\right)-\mathit{Current}\mathit{ICPT}\mathit{Charge}\left(\mathit{RM}\right)$$(3)

$$\mathit{New}\mathit{TNB}\mathit{Bill}\left(\mathit{RM}\right)=\left(\mathit{Electrical}\mathit{Bill}\left(\mathit{RM}\right)+\mathit{ICPT}\mathit{Charge}\left(\mathit{RM}\right)\right)-\mathit{Current}\mathit{TNB}\mathit{Bill}\left(\mathit{RM}\right)$$(4)

$$\mathit{Annual}\mathit{Savings}\left(\mathit{RM}\right)=\left(\mathit{New}\mathit{TNB}\mathit{Bill}\left(\mathit{RM}\right)-\mathit{Current}\mathit{Solar}\mathit{Bill}\left(\mathit{RM}\right)\right)\times 12.$$(5)

3.5 Payback period

The payback period, expressed in years, represents the duration required for the cumulative annual savings generated by the solar energy system to equal the initial investment cost. The initial investment refers to the aggregate financial capital, denominated in Ringgit Malaysia (RM), necessary for the complete construction and commissioning of the entire GCPV project. The annual savings are defined as the total monetary value generated by the solar energy system on an annual basis, also expressed in RM, as mathematically represented in equation (6) [20].

$$PaybackPeriod=\frac{InitialInvestment}{AnnualSavings}.$$(6)

3.6 Site inspection

This research incorporates a critical component of site inspection, specifically focusing on the operational status of one of the GCPV system's inverters located within the Main Switchboard (MSB) room. The inspection will focus on Inverter number 3. The assessment protocol includes continuous monitoring of both the output voltage and current parameters, in addition to a thorough evaluation of the Total Harmonic Distortion (THD) values to ascertain power quality.

4 Results and discussion

This section presents an assessment of the economic viability of the GCPV system implemented at the USM Engineering Campus under the NEM 3.0 scheme. The findings demonstrate substantial improvements in both energy generation capacity and significant reductions in electricity bills, thereby validating the system's efficacy in optimizing the campus's overall energy consumption profile. A careful analysis of the electrical bills, both before and after the installation of the GCPV system, revealed considerable cost savings. Furthermore, this section evaluates the power quality characteristics observed after the installation of the GCPV system.

4.1 Solar energy production

Figure 5 illustrates the simulated annual energy production over a projected 25-yr operational lifespan for the 4,324.75 kWp PV system installed at the USM Engineering Campus, as computed using PVsyst software. The estimated energy production over this period is approximately 146,036.60 MWh, with the initial year's yield projected at around 6,272.20 MWh. It is anticipated that the energy output will experience an annual decrement ranging from 0.4% to 0.8%. This reduction is attributable to various factors, including the degradation of solar panel module efficiency over time, soiling losses from accumulated dust and debris, inverter conversion losses, and resistive ohmic losses within the electrical circuitry. The blue data series represents the discrete simulated energy production values over the 25 years, while the orange trend line outlines the overall trajectory of energy production. The graphical representation distinctly indicates a linear decrease in energy output as the system ages.

Figure 6 presents a comparative analysis of the actual energy produced versus the energy consumed at the USM Engineering Campus during the year 2023. The average monthly energy generation for the campus was 464 MWh. A significant proportion of the generated power was directly consumed by USM, with an average monthly consumption figure of 403 MWh. In terms of consumption peaks, January exhibited the highest at 540 MWh, while November recorded the lowest at 362 MWh. The USM Engineering Campus effectively utilized 86.8% of the energy produced by its PV system, with the remaining 13.2% being exported back to the national utility grid. On a monthly average, approximately 61 MWh was exported, culminating in a total export of 735 MWh for the entirety of 2023. This exported energy, purchased by Tenaga Nasional Berhad (TNB) at the prevailing System Marginal Price (SMP), resulted in an average monthly discount of RM 14,683 on USM's electrical bill, amounting to a substantial RM 176,191 in total savings for 2023.

Figure 7 depicts the total electrical bill incurred by the USM Engineering Campus in 2023, divided into payments to TNB and costs associated with the solar PV system. The average monthly power consumption cost for the campus was approximately RM 548,452.61. Of this total, approximately 84% was remitted to TNB, with the residual 16% allocated to the solar installer.

Figure 8 illustrates the proportional contribution of TNB and the GCPV system to the total load demand in 2023. TNB supplied approximately 60% of the monthly total load demand, while the GCPV system consistently provided the remaining 40%. This distribution indicates that the GCPV system has significantly mitigated electrical bill costs for the campus, concurrently generating an energy volume nearly equal to that supplied by TNB.

Furthermore, as presented in Figure 9, the GCPV system consistently fulfilled an average of 40% of the monthly load demand throughout 2023. March recorded the highest solar energy contribution, supplying 49.46% (equivalent to 549,968 kWh) of the total load, with the remaining 50.54% (561,977 kWh) sourced from TNB. Conversely, November registered the lowest solar contribution, with solar energy meeting only 31.14% of the total load demand. The annual average load demand for the USM Engineering Campus stood at 1,180,427.01 kWh per month. June experienced the highest demand at 1,321,920.00 kWh, while September recorded the lowest at 923,717.00 kWh.

The graphs presented in Figure 10a demonstrate the impact of the PV system in reducing electricity expenses. With the integration of the GCPV system, the average monthly electricity bill in 2023 was approximately RM 548,452.61. This stands in contrast to a hypothetical average monthly bill of RM 732,881.43 without the PV system. Figure 10b further explicates the savings achieved by the campus. A minimum monthly saving of RM 148,322.14 was consistently realized, with the highest monthly savings recorded in March at RM 233,584.85. On average, USM accumulated approximately RM 184,428.83 in savings per month in 2023, culminating in a remarkable total of RM 2,213,145.91 during the initial year of GCPV system operation. This represents an approximate 25% reduction in the overall electricity bill.

For a post-installation evaluation of the GCPV system, a comparative analysis of energy consumption and electricity bills was conducted between 2022 (pre-installation period) and 2023 (the first year of operational integration). Figure 11 distinctly illustrates a significant reduction in TNB's load demand for nearly every month in 2023. This observation indicates that the GCPV system effectively met the total energy requirements of the USM Engineering Campus by supplying a considerable portion of the demand, including any excess. To validate these critical findings, direct comparisons were made utilizing the actual TNB bills from both years.

In 2023, TNB implemented a revised Imbalance Cost Pass-Through (ICPT) rate under its Incentive-Based Regulation (IBR) framework. This adjustment aimed to reflect fluctuations in fuel and generation costs. Figure 12 demonstrates a noticeable decrease in the electricity bill following the GCPV system's installation, specifically when normalized against the 2022 ICPT rate. However, even with the new ICPT rate (ICPT=0.2) in 2023, the overall costs remained largely comparable despite a lower energy demand. A direct comparison of bills between 2022 and 2023, utilizing the constant 2022 ICPT rate (ICPT=0.037), revealed an average bill reduction of approximately RM 85,850.15. This compelling evidence underscores the GCPV system's sustained effectiveness in mitigating the impact of rising electricity costs at the USM Engineering Campus.

Fig. 5 Simulated annual energy production over a projected 25-year operational lifespan.

Fig. 6 Energy produced against energy consumed in 2023.

Fig. 7 Total electrical bill in the year 2023.

Fig. 8 Energy consumption percentage in the year 2023.

Fig. 9 USM engineering campus load demand in the year 2023.

Fig. 10 Data collection with GCPV system in 2023 (a) Monthly electrical bill, (b) Current savings.

Fig. 11 Load demand (kWh) comparison before and after the GCPV installation.

Fig. 12 TNB electrical bill with different ICPT charges.

4.2 Payback period

For the USM Engineering Campus, the mode of PV system acquisition is structured under a Power Purchase Agreement (PPA), which inherently implies that there is no direct return on investment (ROI) for the end-user. In a typical solar power purchase agreement (PPA) model, the installer assumes responsibility for the financing, design, permitting, and installation of the solar energy system on the customer's property, often requiring minimal to no upfront deposit. The developer, in turn, sells the electricity generated to the host consumer at a predetermined rate, which is typically lower than the prevailing retail rate charged by the local utility provider. Nevertheless, for illustrative purposes, the simple payback period can be theoretically calculated using equation (6). Based on this equation, if the total cost of the PV system had been fully financed by USM, the estimated payback period or return on investment would approximate 5 years. This projection implies that after a five-year operational period, the PV system would commence generating net financial benefits for the consumer.

4.3 Power factor analysis

In 2023, a significant observation at the USM Engineering Campus was the degradation of the system's power factor to below 0.85 during specific periods, following the installation of the solar PV system. This reduction resulted in the imposition of penalties by Tenaga Nasional Berhad (TNB), Malaysia's national electricity provider [21]. Consequently, a detailed follow-up research study was initiated to comprehensively identify the root cause of this power factor issue [22]. Figure 13 provides a visual representation of several buildings within the USM Engineering Campus that have been equipped with GCPV systems.

To address power factor degradation, a targeted inspection was conducted on a selected PV inverter located within the campus to ascertain its operational integrity and detect any irregularities. A three-phase power quality analyzer was connected to the outgoing cable of the PV inverter, as illustrated in Figure 14. The parameters precisely measured during this assessment included the line-to-neutral voltage, line-to-line voltage, total harmonic distortion (THD), and the system operating frequency [23].

Figure 15 displays the collected phase R voltage and current data. The inverter consistently recorded a stable voltage of 245.4 V at a frequency of 50 Hz as shown in Figure 15a. Current measurements exhibited fluctuations that correlated directly with solar energy production levels, providing further affirmation of the continuous and effective operation of the PV system. The measured THD for the phase current was recorded at 3.6%. Furthermore, in Figure 15c, the measured line voltage was 423.6 V, which further validated the normal operational status of the inverter. Conventionally, the standardized three-phase voltage is 415 V, however, measured voltages frequently exceed this nominal value as utility grids intentionally maintain slightly higher voltages to compensate for inherent transmission losses and voltage drops along extended transmission lines. The measured line current was 53.7 A, while Figure 15d shows the THD for the line current at 3.1%, complies with the specification of IEEE-519 where the current THD should be less than 5%.

As presented in Figure 16, real-time measurements from the GCPV inverter indicate that the solar system generated 20 kW of real power, 23.1 kVA of apparent power, and 11.4 kVAr of reactive power. The measured power factor (PF) was 0.87, and the displacement power factor (DPF), which quantifies the phase shift between the fundamental voltage and current components, was 0.88. These data collectively suggest that the inverter is functioning optimally without any discernible issues. Given that the USM Engineering Campus utilizes identical inverter models across its various installations, it can be reasonably presumed that the power factor characteristics should be consistent across all inverters. For a comprehensive power factor assessment, the individual power factors of all inverters are aggregated, and an average power factor is computed for the entirety of the GCPV system at the USM Engineering Campus. The fact that the inverter is functioning correctly, without any identifiable faults, strongly suggests that the GCPV system itself is not adversely affecting the power factor. The observed decline in the power factor is therefore more plausibly attributed to the deteriorated condition of the existing capacitor banks at the USM Engineering Campus, which are likely in need of replacement. Consequently, it is concluded that the installation of the GCPV system does not inherently degrade or cause issues with the power factor.

Fig. 13 USM Engineering campus with rooftop GCPV system.

Fig. 14 Inverter outgoing cable measurement setup.

Fig. 15 Measurement on phase A: (a) Phase voltage, (b) Phase current THD, (c) Line voltage, (d) Line current THD.

Fig. 16 Real-time power factor measurement of the GCPV Inverter.

5 Conclusions

This research provides a case study for commercial building owners across Malaysia, given the nation's abundant solar resources, encouraging the exploration of green energy production and opportunities for significant cost reduction. Moreover, the comprehensive economic evaluation of the GCPV system at the USM Engineering Campus under the NEM 3.0 program unequivocally demonstrates substantial benefits in terms of energy production and cost savings, thereby validating both the financial viability and the favorable return on investment. The primary objectives of this research were to assess the system's performance, conduct a detailed analysis of changes in electrical bills both pre- and post-installation for commercial buildings, and critically address significant operational issues, notably observed power factor drops. The evaluation conclusively demonstrated substantial benefits in both energy production and financial savings attributable to the NEM scheme. Furthermore, a comparative analysis of electrical bills from before and after the system's installation revealed a marked decrease in energy costs, primarily due to the system's inherent capacity to feed excess generated energy back into the national grid. On average, USM accumulated approximately RM 184,428.83 in savings per month in the year 2023, culminating in a remarkable total of RM 2,213,145.91 during the initial year of GCPV system operation. This represents an approximate 25% reduction in the overall electricity bill. This reduction unequivocally underscores the robust economic feasibility and long-term financial advantages of deploying GCPV systems within commercial settings. One of the principal issues identified during the course of this research was the degradation of the power factor subsequent to the installation of the GCPV system. Detailed investigations, however, strongly suggested that this observed power factor drop was not directly attributable to the solar PV system itself. Instead, the underlying cause was determined to be the suboptimal operational condition of the pre-existing capacitor banks within the USM Engineering Campus's electrical infrastructure. It is therefore concluded that the replacement or systematic upgrade of these capacitor banks is a necessary intervention to maintain an optimal power factor and effectively avert potential financial penalties from utility providers. Based on the findings, if the total cost of the installation of the GCPV system had been fully financed by USM, the estimated return on investment (ROI) would approximate 5 years. In conclusion, this research definitively affirms the economic viability and demonstrable performance benefits of GCPV systems operating under the NEM 3.0 scheme at the USM Engineering Campus. It emphatically underscores the critical importance of ongoing maintenance protocols and continuous component upgrades to ensure the sustained efficiency and operational longevity of the system. Ultimately, these findings provide a compelling motivation for the broader adoption of GCPV systems as a cornerstone for sustainable commercial energy solutions.

Funding

The authors wish to express their sincere gratitude to the School of Electrical & Electronic Engineering at Universiti Sains Malaysia (USM) for providing the invaluable opportunity and guidance that facilitated the completion of this research. This work was supported by Universiti Sains Malaysia, Short-Term Grant with Project No: 304/PELECT/6315776.

Conflicts of interest

The authors declare that there is no conflict of interest regarding the publication of the paper.

Data availability statement

All data supporting the findings of this study including energy production records, financial evaluations, and pre- and post-installation electricity bills for the USM Engineering Campus have been made publicly available.

Author contribution statement

The authors confirm contribution to the paper as follows: study conception and design: Muhammad Hafeez Mohamed Hariri, Mohamad Kamarol Mohd Jamil; data collection: Muhammad Imran Joohari; analysis and interpretation of results: Amir Rabani Abd Halim; draft manuscript preparation: Muhammad Hafeez Mohamed Hariri, Nor Azizah Binti Mohd Yusoff. All authors reviewed the results and approved the final version of the manuscript.

References

Appendix A

A. 1 Programme Structure and Description of Subroutines.

The main flow chart of the programme is shown in Figure A.1.

Fig. A.1 Main flow chart of the research used in this study.

Fig. A.2 PVsyst program flowchart.

Fig. A.3 PVsyst program interface.

All Tables

All Figures

	Fig. 1 Effect of irradiance on solar cell I-V curve [14].
In the text

	Fig. 2 Effect of temperature on solar cell I-V curve [14].
In the text

	Fig. 3 Inverter SG110CX circuit diagram.
In the text

	Fig. 4 The average daily solar irradiation data at the USM Engineering Campus.
In the text

	Fig. 5 Simulated annual energy production over a projected 25-year operational lifespan.
In the text

	Fig. 6 Energy produced against energy consumed in 2023.
In the text

	Fig. 7 Total electrical bill in the year 2023.
In the text

	Fig. 8 Energy consumption percentage in the year 2023.
In the text

	Fig. 9 USM engineering campus load demand in the year 2023.
In the text

	Fig. 10 Data collection with GCPV system in 2023 (a) Monthly electrical bill, (b) Current savings.
In the text

	Fig. 11 Load demand (kWh) comparison before and after the GCPV installation.
In the text

	Fig. 12 TNB electrical bill with different ICPT charges.
In the text

	Fig. 13 USM Engineering campus with rooftop GCPV system.
In the text

	Fig. 14 Inverter outgoing cable measurement setup.
In the text

	Fig. 15 Measurement on phase A: (a) Phase voltage, (b) Phase current THD, (c) Line voltage, (d) Line current THD.
In the text

	Fig. 16 Real-time power factor measurement of the GCPV Inverter.
In the text

	Fig. A.1 Main flow chart of the research used in this study.
In the text

	Fig. A.2 PVsyst program flowchart.
In the text

	Fig. A.3 PVsyst program interface.
In the text