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Wave Energy Converters (WECs) need to be deployed in large numbers in an array layout in order to have a significant power production. Each WEC has an impact on the incoming wave field, by diffracting, reflecting and radiating waves. Simulating the wave transformations within and around a WEC array is complex; it is difficult, or in some cases impossible, to simulate both these near-field and far-field wake effects using a single numerical model, in a time- and cost-efficient way in terms of computational time and effort. Within this research, a generic coupling methodology is developed to model both near-field and far-field wake effects caused by floating (e.g., WECs, platforms) or fixed offshore structures. The methodology is based on the coupling of a wave-structure interaction solver (Nemoh) and a wave propagation model. In this paper, this methodology is applied to two wave propagation models (OceanWave3D and MILDwave), which are compared to each other in a wide spectrum of tests. Additionally, the Nemoh-OceanWave3D model is validated by comparing it to experimental wave basin data. The methodology proves to be a reliable instrument to model wake effects of WEC arrays; results demonstrate a high degree of agreement between the numerical simulations with relative errors lower than 5 % and to a lesser extent for the experimental data, where errors range from 4 % to 17 % .

With the development of distributed energy resources, the low voltage distribution network (LVDN) is supposed to be the integrator of small distributed energy sources. This makes the users in LVDNs multifarious, which leads to more complex modeling. Additionally, data acquisition could be tricky due to rising privacy concerns. These impose severe demands on control schemes in LVDNs that the classical centralized control might not be able to fulfill. To tackle this, a model-free control approach with distributed decision-making architecture is proposed in this paper. Employing statistical methods and game theory, individual users in LVDNs achieve local optimum autonomously. Comparing to conventional approaches applied in LVDNs, the proposed approach is able to achieve active control with less communication burden and computational resources. The paper proves the convergence to the Nash Equilibrium (NE) and uses player compatible relations to form the specific equilibrium. A variant of the log-linear trial and error learning process is applied in a novel “suggest-convince” mechanism to implement the proposed approach. In the case study, a 103 nodes test network based on a real Belgian semiurban LVDN is illustrated. The proposed approach is validated and analyzed with practical load profiles on the 103 nodes network. In addition to that, centralized control is implemented as a benchmark to show the performance of the proposed approach by comparing it with the classical optimization result. The results demonstrate that the proposed approach is able to achieve player compatible equilibrium in an expected way, resulting in a good approximation to the local optimum.

Liquid biowaste represents more than 98% of the total municipal waste streams on wet basis and 4–5% on dry basis. Recent attention has been focused on how to manage it optimally, and several novel technologies are being developed to valorize it. Among the developing alternatives is a technology that operates continuously by integrating a hydrothermal reactor, a gasifier and condenser to recover hydrochar using any produced gases to power the system. This study introduces the “3-step evolution model” in order to simulate the hydrothermal reactor. The model has been developed in a MATLAB/Cantera environment and calculates the outputs as the products of a series of sub-stoichiometric char-gas reactions. Experiments with chicken manure slurry as feedstock were implemented for the validation of the model. Treatment of 32.16 kg/h of chicken manure produces 4.57 kg/h of hydrochar and 3.45 kg/h of syngas. The 3-step evolution model simulated the correct ratio of solid-to-gas, 57–43% (excluding the liquids). The experimentally measured carbon dioxide is used as a correction factor to calculate all the other parameters that cannot be assessed during the continuous operation of the hydrothermal reactor. The simulated compositions for carbon dioxide and methane were 94–96% and 0.5–0.8%, respectively. The values were close to the experimental results that ranged from 94.7% to 95.6% for the carbon dioxide and from 0.5% to 0.7% for the methane. The model predicts that higher temperatures of operation would increase carbon monoxide composition from 4–5% up to 7–8%.

This paper presents three new and improved non-isolated topologies of quadratic boost converters (QBC). Reduced voltage stress across switching devices and high voltage gain with single switch operation are the main advantages of the proposed topologies. These topologies utilize voltage multiplier cells (VMC) made of switched capacitors and switched inductors to increase the converter’s voltage gain. The analysis in continuous conduction mode is discussed in detail. The proposed converter’s voltage gain is higher than the conventional quadratic boost converter, and other recently introduced boost converters. The proposed topologies utilize only a single switch and have continuous input current and low voltage stress across switch, capacitors, and diodes, which leads to the selection of low voltage rating components. The converter’s non-ideal voltage gain is also determined by considering the parasitic capacitance and ON state resistances of switch and diodes. The efficiency analysis incorporating switching and conduction losses of the switching and passive elements is done using PLECS software (Plexim, Zurich, Switzerland). The hardware prototype of the proposed converters is developed and tested for verification.

The output of a photovoltaic array is reduced considerably when PV panels are shaded even partially. The impact of shading causes an appreciable loss in power delivery, since the PV panels are connected in series and parallel to contribute to the required voltage and power for the load. The prevailing research on mitigating the shading impact is mostly based on complex reconfiguration strategies where the PV panels are subjected to complex rewiring schemes. On the other hand, to disperse the shading many studies in the literature defend the physical rearrangement of the panels. The available intensive reconfiguration schemes, such as the series parallel (SP), bridge link (BL), honeycomb (HC), and total cross tied (TCT) schemes, try only to mitigate the shading impact and there is no scope for compensation; as a result, a loss of output power is inevitable. In the proposed research work, both the mitigation of and the compensation for the losses incurred due to shading are studied. In this work, an optimal reconfiguration scheme is adopted to reduce the shading impact and a power electronic circuit with a battery source is designed to compensate for the shading losses in all aspects. In the optimal reconfiguration scheme, a bifurcation strategy is adopted in each column and the electrical connections of the PV panels are interchanged such that the shading impact is dispersed. The power electronic circuit consists of a half-bridge buck converter with a battery source that injects the current required by a shaded column. This setup compensates for the shaded PV array’s power and improves the efficiency of the total system. The proposed scheme was implemented in a 3200 W system and subjected to various shading patterns, including single panel shading, corner shading, long and wide shading, and random shading. The proposed scheme was simulated in the MATLAB Simulink environment and compared with static 4 × 4 PV array configurations, including the series parallel (SP), bridge link (BL), honeycomb (HC), and total cross tied (TCT) configurations. The comparative performance was assessed in terms of mismatch power loss, fill factor, and efficiency. The proposed system is suitable for all shading patterns and was proved to be very efficient even in the worst shading, where 1353 W was saved.

The pollution caused by gas flaring is hazardous to the health of flora, fauna, and humans settled around the flaring site. Gas flaring also incurs economic loss as natural gas, an energy source, is wasted in flares. Furthermore, the unreliable electrical infrastructure is a roadblock for oil and gas companies attempting to achieve their production targets. This paper presents a framework to design hybrid energy systems (HES) which utilize the gas flare waste along with the locally available renewable energy sources to generate electricity. A novel dispatch strategy to suit the requirements of the oil and gas fields has been used for real-time simulations and optimization of the HES. As a test case, six different hybrid energy configurations, modelled for two gas flaring sites, Lakwa and Geleky in Assam—India, were analyzed and compared on the basis of economic and environmental factors. The best suitable configuration comprised 2000 kW solar photovoltaic (PV) panel sets, one 200 kW gas microturbine, two 30 kW gas microturbines, and grid connection. The proposed system economically outperformed the existing power system in the area by 35.52% in terms of the net present cost. Moreover, it could save 850 tons of carbon dioxide emissions annually, and it has a renewable fraction of 93.7% in the total energy generation. Owing to these merits, the presented technique would be a promising option for generation of electricity from flare gas waste and to mitigate pollution.

The most common method for assessment of a photovoltaic (PV) system performance is by comparing its energy production to reference data (irradiance or neighboring PV system). Ideally, at normal operation, the compared sets of data tend to show a linear relationship. Deviations from this linearity are mainly due to malfunctions occurring in the PV system or data input anomalies: a significant number of measurements (named as outliers) may not fulfill this, and complicate a proper performance evaluation. In this paper a new data analysis method is introduced which allows to automatically distinguish the measurements that fit to a near-linear relationship from those which do not (outliers). Although it can be applied to any scatter-plot, where the sets of data tend to be linear, it is specifically used here for two different purposes in PV system monitoring: (1) to detect and exclude any data input anomalies; and (2) to detect and separate measurements where the PV system is functioning properly from the measurements characteristic for malfunctioning. Finally, the data analysis method is applied in four different cases, either with precise reference data (pyranometer and neighboring PV system) or with scattered reference data (in plane irradiance obtained from application of solar models on satellite observations).

The goal of this study was to examine the interlinkage of renewable energy, technology innovation, human capital, and governance on environment quality by using a panel quantile regression in Asian emerging economies over the period of 1990–2019. The results indicated that higher economic growth, population density, technological innovation in renewable energy, and exploitation of natural resources have significantly raised CO2 emissions in emerging Asia. Furthermore, larger capital, more use of renewable energy, green technology, and human capital development can improve environmental sustainability in Asia. As for governances, proxied by corruption rates, no evidence indicated that it has resulted in more damage, unlike earlier studies have suggested. The findings indicated that the three channels exposed in the Kuznets hypothesis can serve as a reference for proposals for environmental policies (scale of consumption, energy composition, and choice of technologies). There are opportunities to reduce CO2 emissions through investments in human development, investing in new technologies to increase efficiency in energy (generation and consumption), increasing working capital (GCF), and migrating to more environmentally friendly energy. The negative link between carbon dioxide emissions and economic growth, increases in population density, and exploitation of natural resources can compromise the achievement of sustainable environmental goals.