Jeyraj Selvaraj

Time series foundation models (TSFMs) promise accurate zero-shot forecasts, but their value for carbon markets has been examined only in the European Union Emissions Trading System (EU ETS). We evaluate Chronos-2 and TimesFM-2.5 alongside six benchmark and hybrid models in four markets (the EU ETS, China’s national ETS, and the Hubei and Guangdong pilots) at horizons of 1–60 trading days, using a rolling-origin design without information beyond the forecast origin. No model significantly outperforms the random walk in the EU ETS. TSFMs achieve the lowest point and probabilistic forecast errors in the Hubei pilot, but their point forecasts are less accurate than the random walk in the national market and, over the full test period, in Guangdong. In the national market, Chronos-2 errors reach 22.8% at the 60-day horizon and its 80% intervals cover only 62% of outcomes, whereas TimesFM-2.5 attains the lowest quantile loss despite under-coverage. The national-market and Hubei results hold over a common calendar period and for targets postdating the model weights. Across the markets and periods studied, gains are associated with a large transitory component in daily returns and losses with persistent price moves. Look-ahead bias roughly halves the apparent error of decomposition-based models. TSFMs therefore require market-specific validation before deployment.

This study proposes an improved high-efficiency bidirectional CLCLC resonant DC-DC converter, highlighting its significance as a vital component in power electronic systems. The converter operates at a high switching frequency of 100 kHz while achieving zero-voltage switching (ZVS) and zero-current switching (ZCS), effectively minimizing switching losses. In a bidirectional DC-DC converter (BDDC), a distinct interleaved pulse-width modulation (PWM) control strategy is applied to both the low-voltage and high-voltage sides, enabling a zero-voltage-switched half-bridge (ZVSHB) topology for seamless bidirectional power flow. In this study, a detailed circuit configuration and bidirectional operation modes are discussed, followed by rigorous small-signal modeling (SSM) and state-space averaging (SSA) methods using MATLAB software to assess the dynamic closed-loop stability. Extensive PSIM simulations provide insight into the soft-switching performance, while a 1 kW experimental model was built to validate the theoretical and simulation outcomes. The converter reached maximum efficiencies of 96.332% when operating in boost mode and 96.623% in buck mode. Furthermore, the analytical efficiency and power loss breakdown are presented, demonstrating a close agreement between the theoretical predictions and the experimental results. A comprehensive comparative evaluation of existing isolated and non-isolated bidirectional converter topologies demonstrate that the proposed design achieves superior performance by delivering higher circuit efficiency and reduced structural complexity.

Solar energy has seen the most significant development in the past decade. Electricity and hot water production are the two most common uses of solar energy. A photovoltaic (PV) system is a popular method for generating electricity from solar energy. However, PV systems are known for their low efficiency, which reduces further as the PV cell temperature rises. The photovoltaic-thermal (PVT) system combines a PV system with a thermal collector to provide dual benefits, namely power generation and hot water production. However, PVT system research often employs a constant flow (CF) strategy in which water is continually cycled throughout the experiment, making it inapplicable. In comparison, the constant collection temperature (CCT) scheme is a more feasible approach, but its impact on PVT system performance has received less attention. This study compares a flow channel PVT system using both CF and CCT strategies. The results show that the CF scheme achieved a higher maximum thermal efficiency of 35.05%, while the CCT scheme reached 17.89%. The CCT method can also maintain the optimum water temperature despite changing radiation circumstances. The PVT system outperforms traditional PV panels regarding electricity efficiency, with a maximum improvement of 0.89% and 0.96% utilizing the CF and CCT schemes, respectively. These results show that PVT systems with CCT schemes that use less energy for pumping outperform PV panels in terms of power production and electricity efficiency.

Energy storage systems (ESSs) have recently emerged as a common solution for mitigating the variability of intermittent renewable energy sources. A major challenge linked to ESSs is their expense. This study focuses on investigating techniques to decrease the size of an ESS while maintaining its performance levels. Data were gathered from a grid-connected 2MW PV system in Malaysia over multiple days, with numerous variables showing considerable hour-to-hour variations from hour to hour due to solar irradiation. A Python code was created to examine the impact of different ESS sizes on power grid stabilization utilizing the power conservation technique. The suggested ESS size derived from the program outcomes was evaluated utilizing a hybrid ESS, incorporating a vanadium redox battery (VRB) as the high-energy-density component and supercapacitors (SCs) as the high-power-density component. The effects of altering the output period lengths were examined. The result must stay consistent for at least five minutes as the minimum required duration. The findings show that an ESS capacity of approximately 10% of the overall produced power can meet the above duration requirement. A straightforward test was employed in the system to assess the power generation level in the upcoming time period. Simulink was employed to model the produced system, and the outcomes met the ESS requirements, enhancing efficiency and extending the battery lifespan.

The use of power smoothing for renewable energy resources is attracting increasing attention. One widely used resource that could benefit from this technique is the grid-tied photovoltaic (PV) system. Solar energy production typically follows a Gaussian bell curve, with peaks at midday. This paper confirms this pattern by using the bell curve as a reference; however, climate variations can significantly alter this pattern. Therefore, this study aimed to smooth the power supplied to the grid by a PV system. The proposed controller manages the charge and discharge processes of the energy storage system (ESS) to ensure a smooth Gaussian bell curve output. It adjusts the parameters of this curve to closely match the generated energy, absorbing or supplying fluctuations to maintain the desired profile. This system also aims to provide accurate predictions of the power that should be supplied to the grid by the PV system, based on the capabilities of the ESS and the overall system performance. Although experimental results were not included in this analysis, the system was implemented in SIMULINK using real-world data. The controller utilizes a hybrid ESS comprising a vanadium redox battery (VRB) and supercapacitors (SCs). The design and operation of the controller, including curve tuning and ESS charge–discharge management, are detailed. The simulation results demonstrate excellent performance and are thoroughly discussed.

Energy storage systems (ESS) have recently emerged as a prevalent solution for mitigating the variability of intermittent renewable energy sources. One of the primary challenges associated with ESS is their cost. This paper aims to explore methods for reducing the size of ESS without compromising performance. Data was collected from a grid-tied 2MW PV unit in Malaysia over several days, as many variables exhibit significant fluctuations from hour to hour due to solar irradiation. Python code was developed to analyze the effects of varying ESS sizes on power grid smoothing. Both high-power density devices and high-energy density devices were tested, and the impact of changing output period durations was investigated. The output should remain stable for no less than five minutes, which is the minimum acceptable timeframe. SIMULINK was utilized to simulate the recommended ESS size, employing a vanadium redox battery (VRB) as the high-energy density device and supercapacitors (SC) as the high-power density device.

The growing demand for advanced power monitoring underscores the limitations of traditional smart meters, which often lack detailed insights into power quality. This capability has become increasingly important as modern electrical systems are more vulnerable to disturbances and inefficiencies. This paper presents the design and development of a low-cost, real-time power quality and energy monitoring device (PQEm), specifically engineered for easy installation in any electrical setup, whether for bulk metering or submetering of individual units or appliances. The PQEm system integrates a highly precise multiphase analog front-end (AFE) power quality IC with a system-on-a-chip (SoC) platform, enabling the collection of real-time data on key energy metrics such as active, reactive, and apparent power, while also detecting a wide spectrum of power quality disturbances, including sags, swells, interruptions, and voltage imbalances, with a detection latency of less than 5 ms. The PQEm device includes time-frequency analysis to enhance visualization and characterization of voltage and current data. It also supports long-term raw data recording at the native sampling frequency, a feature typically reserved for high-end power quality analyzers. The device has been calibrated and validated through both laboratory testing and real-world applications, offering a cost-effective and user-friendly solution that addresses critical gaps in existing smart metering systems while empowering consumers to monitor power quality issues with greater precision.

Power smoothing for renewable energy resources is receiving increasing attention. One widely used resource is the grid-tied photovoltaic (PV) system. Solar energy production typically follows a Gaussian bell curve, with peaks at midday; however, climate varia-tions can significantly alter this pattern. This paper aims to smooth the power supplied to the grid by the PV system. The proposed controller manages the charge and discharge processes of the Energy Storage System (ESS) to ensure a smooth Gaussian bell curve out-put. It adjusts the parameters of this curve to closely match the generated energy, absorb-ing or supplying fluctuations to maintain the desired profile. This system aims also to provide accurate predictions of the power that should be supplied to the grid by the PV system, based on the capabilities of the ESS and the overall system performance. Although experimental results were not included in this analysis, the system was implemented in SIMULINK using real-world data. It utilizes a hybrid ESS comprising a Vanadium Redox Battery (VRB) and Supercapacitors (SC). The design and operation of the controller, in-cluding curve tuning and ESS charge‒discharge management, are detailed. The simula-tion results demonstrate excellent performance and are thoroughly discussed.