Solar photovoltaic systems could reduce the energy cost and emissions of Malaysian wastewater treatment plants (WWTPs), but the plants first need a clearer view of their demand. This note covers the operational constraints, control architecture, and the role of ML-based forecasting in deployment decisions.
Why Solar PV in WWTPs?
Wastewater treatment facilities are globally recognized as energy-intensive operations, often relying on electrical energy accounting for a significant portion of their operational expenditure (OPEX). For conventional WWTPs, energy use contributes between 25%-60% of the total OPEX Muzaffar2022 . This high dependency on the central electricity grid exposes these facilities to electricity tariffs volatility and supply uncertainties. The national sewerage company, Indah Water Konsortium (IWK) Sdn Bhd, has experienced a substantial increase with electricity costs ballooned from RM22.53 million in 2000 to RM256.30 million in 2020 IWK2021 . This became the primary motivation for IWK to explore renewable energy sources, particularly solar PV systems, to mitigate energy costs and enhance sustainability.
IWK operates as Malaysia's national sewerage company and manages a vast network of public treatment plants. As of December 2021, IWK operated and maintained 7,272 public Sewerage Treatment Plants (STPs) and 1,375 network pump stations across the country IWK2021_report . The regulatory oversight is provided by the Suruhanjaya Perkhidmatan Air Negara (SPAN), which ensures compliance with national water quality, ensuring that operators comply with stipulated standards and contractual obligations.
Energy Demand Characteristics of WWTPs
Before implementing solar PV systems, it is important to understand the energy demand of WWTPs so the system can be sized correctly. Energy consumption depends heavily on plant scale and the treatment technology used.
Specific Energy Consumption (SEC) and Categorization
Energy intensity, generally measured as Specific Energy Consumption (SEC) in kilowatt-hour per cubic meter (kWh/m³) of treated wastewater, is a key metric for evaluating the energy efficiency of WWTPs. The SEC values can vary significantly based on the treatment processes employed and the plant's capacity. Data suggests that smaller WWTPs, particular those below $10,000 m^3/month$ capacity, tends to bear a disproportionately higher electricity cost, accounting for 30%-40% of their total running costs Muzaffar2022 . In contrast, larger WWTPs with capacities exceeding typically exhibit lower SEC values, accounting for 15%-30% of the total running costs.
Specific data collected from village WWTPs in Romania indicated high annual average SEC values, ranging from $1.786 kWh/m^3$ to $2.334 kWh/m^3$ of treated wastewater Tokos2021 . The volume of sewage sludge has also grown alongside the population, reaching 7 million $m^3$ annually. Managing this sludge requires significant energy input, with sewage sludge treatment alone consuming an estimated $544,900 GWh$ across IWK operations between 2016 and 2019 Quan2022 .
This variability makes small- to medium-sized conventional STPs the strongest candidates for early solar PV integration. These plants have higher SEC values and greater dependence on grid power, so the marginal return from offsetting electricity use is likely highest in this segment.
Identification of Energy-Intensive Processes
The greatest energy concentration of electrical energy demand within a conventional WWTP is typically found in the biological treatment line (BgT), primarily driven by the aeration systems. This process is necessary for activated sludge processes to maintain adequate dissolved oxygen levels for microbial activity. Data confirms that BgT accounts for the majority of total energy consumption, ranging from 63.2% to 72.9% in surveyed WWTPs Tokos2021 .
Whether through diffused-air systems or mechanical aerators, such as those used in oxidation ditches, aeration systems require continuous operation for oxygen transfer, circulation, and mixing. This daytime demand suits solar PV integration. Blowers and aerators can consume generated solar power immediately, improving utilization and reducing the need for Battery Energy Storage Systems (BESS), which are often a significant cost driver in renewable-energy projects.
The high concentration of energy use in aeration suggests that WWTP operators should measure aeration efficiency before installing solar PV. A large array will not solve inefficient blowers or biological processes. Improving those systems first can reduce demand before the PV system is sized.
Advanced PV Power Forecasting and Control Systems
Integrating photovoltaic systems into WWTPs requires forecasts and control systems that can handle changing generation and demand. Recent research describes hybrid forecasting models that combine deep learning with optimization algorithms IturraldeCarrera2025 . These models are designed for the non-linear and variable conditions of real-world PV generation.
Ensemble algorithms such as XGBoost, LightGBM, and CatBoost are used for solar power prediction Nguyen2025 . The cited study identifies humidity and ambient temperature as important factors affecting PV module efficiency, especially in tropical and humid climates.
Integrated Energy Management
Effective PV system integration requires a multi-layered control hierarchy. The foundational layer is Maximum Power Point Tracking (MPPT), which continuously adjusts the DC-DC converter to extract maximum available power from the solar array. A critical technical constraint in many jurisdictions is the Zero Export requirement, which prohibits injecting electrical power back into the grid. To comply, Zero Export Controllers (ZEC) operate on near-instantaneous feedback loops Alnawafah2025 .
Battery Energy Storage Systems provide flexibility to address both PV intermittency and zero-export constraints. Advanced control algorithms optimize charging during low-cost periods and discharging during peak tariff hours Hvala2025 .
Conclusion
Successful solar PV integration at Malaysian WWTPs needs a strategy that connects generation forecasts to plant demand. Better forecasts can help facilities use more of their own generation and decide when storage or grid electricity is needed.
Future research should examine how predictive models and control algorithms are implemented in WWTPs, alongside detailed reviews of existing energy-prediction systems.