Regenerative Sources Research Articles

Solar–Wind System for the Remote Objects of Railway Transport Infrastructure

The article deals with adding the power of a local object to a solar–wind system when consuming electricity from the grid within the power limit. The parameter’s calculation technique for the different values of degree of power increase was considered. The load schedule, the electricity consumption, use of installed power, boundary conditions of generation, and ensuring energy balance were taken into account. Furthermore, data from the renewable source’s generation archive for the location of the object were used. The control of the power consumed by the object was carried out on the taken values of added and total load power with binding to photovoltaic generation. The added power reference on some time intervals was carried out according to the actual renewable generation power value. This increases the degree of use of the battery capacity and energy from renewable sources. The reference of the added power with the state of battery charge formation was carried out according to the forecast. One cycle of deep battery discharge at the evening peak was used to extend the battery life. For the accepted conditions with the average monthly values of renewable energy sources generation with an increase in power by 1.6 times, there was a decrease in electricity consumption by 1.57–4 times.

Optimization strategy based on robust model predictive control for RES-CCHP system under multiple uncertainties

The economic operation of renewable energy sources (RES) integrated with a combined cooling, heating, and power system significantly improves energy utilization and reduces environmental crises. However, multiple uncertainties in RES generation and load consumption predictions cause an imbalance between supply and demand, negatively impacting system efficiency and economics. To address this limitation, an integrated uncertainty rolling optimization framework for combining the probability distribution of prediction and uncertainty optimization is established. Under this framework, an optimization strategy based on a robust model predictive control is proposed for handling the multiple uncertainties of source-load. Here, the probability distributions of RES generation and load consumption predictions are determined using the Gaussian process regression method, and a minimum–maximum rolling optimization model is developed. Under the uncertain scenarios of RES generation and load consumption, the optimization model is converted into a tractable form to obtain a robust schedule that minimizes operating costs. The over-conservatism of robust optimization can be mitigated by adjusting the uncertainty budget. Many case studies are further conducted to confirm the effectiveness of the proposed method. Results show that the operating costs decreased by 11.5% compared with the traditional model predictive control strategies in an uncertain scenario.

Adaptive coordination control strategy of renewable energy sources, hydrogen production unit, and fuel cell for frequency regulation of a hybrid distributed power system

Owing to the significant number of hybrid generation systems (HGSs) containing various energy sources, coordination between these sources plays a vital role in preserving frequency stability. In this paper, an adaptive coordination control strategy for renewable energy sources (RESs), an aqua electrolyzer (AE) for hydrogen production, and a fuel cell (FC)-based energy storage system (ESS) is proposed to enhance the frequency stability of an HGS. In the proposed system, the excess energy from RESs is used to power electrolysis via an AE for hydrogen energy storage in FCs. The proposed method is based on a proportional-integral (PI) controller, which is optimally designed using a grey wolf optimization (GWO) algorithm to estimate the surplus energy from RESs (i.e., a proportion of total power generation of RESs: Kn). The studied HGS contains various types of generation systems including a diesel generator, wind turbines, photovoltaic (PV) systems, AE with FCs, and ESSs (e.g., battery and flywheel). The proposed method varies Kn with varying frequency deviation values to obtain the best benefits from RESs, while damping the frequency fluctuations. The proposed method is validated by considering different loading conditions and comparing with other existing studies that consider Kn as a constant value. The simulation results demonstrate that the proposed method, which changes Kn value and subsequently stores the power extracted from the RESs in hydrogen energy storage according to frequency deviation changes, performs better than those that use constant Kn. The statistical analysis for frequency deviation of HGS with the proposed method has the best values and achieves large improvements for minimum, maximum, difference between maximum and minimum, mean, and standard deviation compared to the existing method.

Biogas and Biohydrogen Production Using Spent Coffee Grounds and Alcohol Production Waste

In this study, alternative uses for lignocellulosic waste by considering them a source of eco-friendly and renewable energy generation with the application of the anaerobic digestion of treated and untreated waste for biogas and biohydrogen generation were investigated. The diluted sulfuric acid method was used for both the substrates and inoculum. Hydrogen production was absent when untreated spent coffee grounds (SCG) and alcohol waste (AW) were both used with the inoculum at pH 5.5 and pH 7.5. Meanwhile, the highest biogas yield of 320 dm3 kg V.S−1 was obtained when using AW at pH 7.5, with a 190 dm3 kg V.S−1 yield of methane. Instead, hydrogen production was observed when initially 4% (w/v) and 6% (w/v) SCG-containing hydrolysates were used as the substrates at pH 5.5, yielding 2.9 ± 0.09 dm3 kg V.S−1 and 3.85 ± 0.12 dm3 kg V.S−1, respectively. The further optimization of pretreatment technologies and pH control could lead to increased and prolonged hydrogen production.

Topology Optimization of the Network with Renewable Energy Sources Generation Based on a Modified Adapted Genetic Algorithm

The article presents an adaptive genetic algorithm developed by the authors, which makes it possible to optimize the topology of a power network with distributed generation. The optimization was based on bioinspired methods. The objects of the study were a 15-node circuit of a power net-work with photovoltaic stations and a 14-node IEEE augmented circuit with distributed generation sources (three wind farms and two photovoltaic plants). The simulation of the modes of electric power systems was performed using the Pandapower library for the Python programming language, which is in the public domain. Three types of electric load of consumers were considered, reflecting the natures of electricity consumption in the nodes of real electric power systems, the results of numerical studies were presented. The proposed genetic algorithm used two different functions of interbreeding, the function of mutation, selection of the best individuals and mass mutation (complete population renewal). At the end of each iteration of the algorithm operation, statistical dependencies were de-rived that characterized its work: the best (minimal losses) and average adaptability in the population, a list of the best individuals throughout all iterations, etc. The verification was carried out in comparison with the results obtained by a complete search of possible radial configurations of the system, and it showed that the developed genetic algorithm had fast convergence, high accuracy and was able to work correctly with different configurations of electrical circuits, generation and load structures. The algorithm can be used in conjunction with renewable energy sources generation forecasting systems for the day ahead when planning the operating modes of power units in order to minimize the costs of covering electricity losses and improve the quality of electricity supplied.

Interfacing Standalone Loads With Renewable Energy Source and Hybrid Energy Storage System Using a Dual Active Bridge Based Multi-Port Converter

Batteries used for providing backup power in renewable energy sources (RES) fed standalone power systems often suffer from a limited lifetime because of high charging and discharging currents arising from sudden changes in load and/or generation. To prevent this, supercapacitors (SCs) are used to supply the high-frequency (HF) power surges. In this article, a new way of interfacing hybrid energy storage systems (HESSs) (Battery + SC) with RES and loads by employing a current fed dual active bridge (DAB) converter based multi-port converter (MPC) is proposed. The proposed approach enables the MPC to regulate the load voltage while tracking the maximum power point (MPP) of the RES and protecting the battery from transients arising from variations in load and/or renewable generation. The SC is used for tracking MPP so that the transient changes in RES generation do not cause a sudden rise/fall in the battery current. The employed MPC structure is designed in such a way that most of the power processing takes place in one stage only resulting in lower losses. The number of switches is reduced by merging the power conversion stages, which helps in keeping the cost low. Experimental results on a laboratory prototype under various static and dynamic conditions are presented.

Advancements in energy storage technologies for smart grid development

<span>In the modern world, the consumption of oil, coal natural gas, and nuclear energy has been causing by a serious environmental problem and an ongoing energy crisis. The generation and consumption of renewable energy sources (RESs) such as solar and wind tidal, can resolve the problem but the nature of the RESs is fluctuating and intermitted. This evolution brings a lot of challenges in the management of electrical grids. The paper reviewed the advancements in energy storage technologies for the development of a smart grid (SG). More attention was paid to the classification of energy storage technologies based on the form of energy storage and based on the form of discharge duration. The evaluation criteria for the energy storage technologies have been carried out based on technological dimensions such as storage capacity, efficiency, response time, energy density, and power density, the economic dimension such as input cost and economic benefit; and the environmental dimension such as emission and stress on ecosystem, social demission such as job creation and social acceptance were also presented in this paper.</span>

Environmental and techno-economic analysis of the integration of biogas and solar power systems into urban wastewater treatment plants

This study analyses the environmental and economic benefits of integrating renewable energy sources (RES), biogas and solar energy into urban wastewater treatment plants (WWTPs). The energy intensity (kWh/m3) of the selected 456 WWTPs in Turkey was evaluated according to type and treatment process. The energy intensity of primary WWTPs (0.066–0.335 kWh/m3) is lower than that of secondary (0.075–1.361 kWh/m3) and advanced WWTPs (0.147–0.988 kWh/m3). RES integration is investigated using energy system optimization software for a sample of 25 WWTPs. Six scenarios were developed based on different CO2 emission penalties (0 and 16 USD/ton) and prices for selling electricity to the grid (0.000, 0.050, and 0.133 USD/kWh) to demonstrate the impact of market-based instruments. RES integration is cost-effective for secondary and advanced WWTPs with a flow capacity above 1 million m3/y. Market-based instruments are found to significantly influence the decision to integrate, generate and use renewable electricity at WWTPs. The RES integration can meet up to 88% of the annual energy demand of the WWTPs at an electricity selling price of 0.133 USD/kWh. When no market-based instruments are implemented, RES generation can reach up to 23% of the WWTPs' annual energy demand while reducing CO2 emissions by 15%.

Effect of nickel concentration on biohydrogen production: Organic solid waste vs. glucose

In recent years, alternative renewable energy generation sources have been investigated, highlighting the dark fermentation process due to it’s potential to obtain hydrogen-rich gas, which can be used as an energy source. Different trace metals intervene in this biological process. Nickel is one of the most important because it is a component of the [Ni–Fe] hydrogenase enzyme that catalyzes the oxidation of H2 in numerous bacteria. The aim of this study was to evaluate the effect of nickel on biohydrogen production from organic solid waste (OSW). The experimental setup was carried out in batch tests using OSW as the substrate, glucose as a reference compound and the valuation of Ni2+ doses on the operation in a Sequencing Batch Reactor. The results of the batch tests showed that when using glucose as a substrate, 2 mg Ni2+/g VSinoculum generated the highest hydrogen production (774 ± 7.3 mL H2/L/d) and highest yield (55.8 ± 3.4 mL H2/g of glucose), which was 34.4% higher than the control. Testing of different concentrations of nickel using OSW as a carbon source showed that the highest production was obtained without Ni2+ addition since the nickel concentration in the residue was 0.17 ± 0.06 mgNi/gVS; consequently, hydrogen production was not affected by the lack of Ni. The addition of 0.5 mg Ni2+/g VSinoculum decreased acetate and butyrate production and increased caproate production.

Blockchain-Based Trustworthy Energy Dispatching Approach for High Renewable Energy Penetrated Power Systems

Renewable energy sources (RES) and low-carbon technology users play a vital role in modern power systems. However, RES generation is easily affected by the environment. Meanwhile, the load, such as electric vehicles (EVs) and prosumers, accounts for most low-carbon technology users. Their power is usually superimposed on peak loads without dispatching, which also exacerbates the instability of the power system. Current optimal dispatching mechanisms mainly rely on centralized organizations, while their dispatching process is not open and transparent. In this article, we propose a blockchain-based trustworthy dispatching approach for the distribution network in high renewable energy penetrated power systems. We first develop an optimal dispatching model considering EVs’ charging behavior and the prosumers’ economic benefits. With the model, prosumers can be dispatched to balance power and consume renewable energy, reducing the impact of disorderly charging on the grid and the abandonment of RES generation. An orderly charging iteration optimization (OCIO) algorithm is proposed to implement orderly EV charging while considering the charging cost and the period. We also propose a modified particle swarm optimization (mPSO) algorithm to publish dispatching tasks based on real-time power balance. Furthermore, blockchain is applied as an open and transparent ledger to record each entity’s power generation and consumption information, ensuring that the dispatching process is trustworthy. Finally, the effectiveness of the dispatching approach is verified in the modified IEEE 33-bus test system and Ethereum-based smart contracts.

Exploring potential storage-based flexibility gains of electric vehicles in smart distribution grids

Flexibility is one of the most important solutions for facilitating the variability of renewable energy sources (RESs) in a distribution network. It is predicted that electric vehicles (EVs) can play an effective role in improving it in the distribution networks. So, this paper presents multiobjective scheduling of batteries of EVs in parking lots (EVPLs) to improve the storage-based flexibility of smart distribution networks (SDNs). The proposed formulation minimizes the energy cost and the voltage deviation function and maximizes the system flexibility (SF) as multiobjective functions that will be optimized subject to the AC load flow, RES and EV constraints, and the allowable limits of the flexibility and operation indices. The resulting model is in the form of a nonlinear programming (NLP) model. Therefore, an equivalent linear programming (LP) formulation is obtained for the original problem to achieve the global optimum result. The stochastic programming approach is used to model uncertainties of the load, active power generation of RESs, price of energy, and EV parameters. The flexible power management is formulated as one of the objective functions of the proposed multiobjective framework, which is solved by using the ε-constraint method, reaching the best possible compromise solution by a fuzzy decision-maker. The proposed framework is tested by using a 33-bus radial test distribution network in the GAMS software environment to evaluate the EVs capability in improving the flexibility indices. Based on the numerical results, it is observed that the proposed scheme with optimal energy management of EVs is able to obtain a high flexibility for SDN. It can also reduce energy losses in terms of network operation and provide a rather smooth voltage profile.

Load Frequency Control of Microgrid System by Battery and Pumped-Hydro Energy Storage

Energy security is one of the main factors in the development and diffusion of microgrid applications. In networks operating without storage, the operation of their systems is greatly affected by sudden load demand and intermittent generation fluctuations. The main purposes of using energy storage systems in microgrids are stabilizing the intermittent generation of renewable energy sources locally, to ensure that energy production matches energy demands, participating in the frequency regulation process, maintaining the energy balance between generation and demand in renewable energy microgrids, and increasing energy reliability. This study investigates the frequency and power balance of an isolated microgrid system, by including storage systems (battery and pump-hydro). Realistic data for wind and solar sources are used for the optimal tuning of the proportional-integral controller, using the integral of the absolute error criterion multiplied by time, with a Quasi-Newton method. Simulation studies have been carried out, to investigate the performance of the microgrid system, by including the hydroelectric power plant system with pump storage for 24 h, under various operating conditions. The results reveal that by including the storage units in the system, it exhibits a more consistent and smooth dynamic performance, using renewable energy efficiently.

Solar Panel Monitoring System Using IOT

Abstract: The invention of the smart grid goes beyond the traditional notion of a one-way power supply. Developed countries have already begun to adopt smart meters, devices and renewable energy sources. Developing and countries still face power shortages on a daily basis. The integration of IoT and energy systems has revolutionized the world in terms of energy efficiency and real-time monitoring. This paper describes an experimental study of how IoT can power the current/ voltage and power generation of self-contained renewable energy sources. Solar modules can be monitored. This document also describes how to modify the tilt angle of the solar panel to improve the efficiency of the solar panel. Solar modules are monitored via a network system with NodeMCU, Atmega328 IC, Arduino. By carrying out the proposed work at a photovoltaic (PV) power plant, you can simplify the monitoring of solar panels. In addition, monitoring power generation can significantly improve the health of PV systems. Keywords: IoT based Solar Panel, Solar monitoring, NodeMCU,

Dynamic Simulation and Performance Enhancement Analysis of a Renewable Driven Trigeneration System

Research activity in the field of combined cooling heating power (or trigeneration) systems with high renewable energy source (RES) contributions has increased rapidly over the last few years, in line with the European Union legislation about energy communities. However, technical challenges arise regarding the synergetic, sustainable and optimal integration of RES in local energy systems. In the present study, the operation of a trigeneration system located in the student residences of Democritus University of Thrace in Greece is examined. The system involves a combination of highly promising renewable and storage technologies, including solar thermal energy and biomass for heat generation, hot water tanks for thermal energy storage, absorption refrigeration for cooling, along with Organic Rankine Cycle and photovoltaic systems for electricity generation. System modeling and simulation have been implemented in Dymola environment with the use of Modelica equation-based modeling language. The accuracy of the model response has been validated against available measurements. Specific design and control measures have been proposed, simulated in a transient fashion and evaluated in terms of (i) RES generation, (ii) solar fraction and (iii) temporal flexibility. The measures examined, including the placement of a Li-ion battery, resulted in an increase of 24.6% in the heating demand solar contribution and of 7.9% in the renewable energy generated for the electricity demand, over the examined periods.

Contract design in electricity markets with high penetration of renewables: A two-stage approach

The interplay between risk aversion and financial derivatives has received increasing attention since the advent of electricity market liberalization. One important challenge in this context is how to develop economically efficient and cost-effective models to integrate renewable energy sources (RES) in the electricity market, which constitutes a relatively new and exciting field of research. This paper proposes a game-theoretical equilibrium model that characterizes the interactions between oligopolistic generators in a two-stage electricity market under the presence of high RES penetration. Given conventional generators with generation cost uncertainty and renewable generators with intermittent and stochastic capacity, we consider a single futures contract market that is cleared prior to a spot market where the energy delivery takes place. We introduce physical and financial contracts to evaluate their performance and assess their impact on the electricity market outcomes and examine how these depend on the level of RES penetration. Since market participants are usually risk averse, a coherent risk measure is introduced to deal with both risk neutral and risk averse generators. We derive analytical relationships between contracts, study the implications of uncertainties, test the performance of the proposed equilibrium model and its main properties through numerical examples. Our results show that overall electricity prices, generation costs, profits, and quantities for conventional generators decrease, whereas quantities and profits for RES generators increase with RES penetration. Hence, both physical and financial contracts efficiently mitigate the impact of uncertainties and help the integration of RES into the electricity system. However, each type of contract has different quantitative impacts on the market outcomes. Moreover, risk aversion increases profit and decreases generators’ risk under different levels of competition by shielding them from the risk associated with cost, demand, and RES uncertainties.

Day‐ahead flexibility enhancement via joint optimization for new energy vehicle fleets and electric vehicle charging/hydrogen refuelling stations

Power systems are striving for the decarbonization goal for long-term sustainability. As a result, the renewable energy sources (RES) have been playing an increasingly important role in the generation portfolio. Power system flexibility maintaining the power balance under uncertain and variable RES generation has become a major concern during the energy transition. This paper proposes to apply new energy vehicles (NEV) including electric vehicles (EVs) and fuel cell vehicles (FCVs) as day-ahead flexibility resources to make revenue by providing comprehensive capacity/energy flexibility in the ancillary service market. First, the detailed joint optimized operational strategies of the NEV fleet and the EV charging/hydrogen refuelling stations are formulated. Second, the design and service clearing methodology of the ancillary service market for flexibility enhancement is introduced. A game-theoretic model is applied to determine the equilibrium price for both the demand and suppliers (namely NEV fleets) of operational flexibility. Third, case studies using IEEE benchmark systems are provided to validate the proposed methods. The results demonstrate that the joint optimization of NEV fleets, charging stations, and hydrogen refuelling stations can improve the power system operational flexibility, reduce the charging expense of NEV owners, and reduce the carbon emission by utilizing the green hydrogen.

25RENEWABLE ENERGY: THE CATALYST FOR A SUSTAINABLE ENERGY DISTRIBUTION SECTOR IN SOUTH AFRICA

The purpose of this article, with practical focus, is to analyse the potential of Renewable Energy (RE) as the catalyst for a sustainable energy distribution sector in South Africa (SA) and promote collaboration between the manufacturers, government, and all relevant stakeholders. The research design was a systematic literature review. It used a qualitative research method, through a questionnaire, to evaluate the knowledge and views of professionals from the energy distribution sector, managers or leaders in the energy sector, and energy sector experts. The sample size selected was between 350 and 400 participants. The literature reviewed noted that photovoltaic (PV) energy was one of the primary RE sources for sustainable energy generation. Furthermore, installing capacity and investment continued to grow throughout SA. Of note was the value-added through distributed RE systems in respect of electricity provision. The energy poverty in SA was high, and the impact of the Covid-19 pandemic further contributed to the challenges experienced. The general conclusions were that due to global warming and increased large-scale pollution, the use of RE for power generation had become evident. The article offered the potential opportunities of RE as the catalyst for the sustainable energy distribution sector in SA. Criteria was developed to include or exclude relevant scientific literature, by identifying subject relevance, type of technology, geographic scope, intervention scale, and data type. Keywords: Photovoltaic, Poverty, Renewable Energy, Sustainable Energy, reduction INTRODUCTIONDue to advances in information and communication technologies, the world faces a strong evolution, placing knowledge technology based on productivity, competition and power. The world is more interconnected than ever (Vezzoli et al., 2019). Renewable energy sources, such as solar energy (photovoltaic and solar thermal), hydroelectric

CFD Investigation on The Jet-Engine Inspired Wind Turbine

The Malaysian Government has set a more ambitious target to achieve higher penetration of Renewable Energy (RE) in the Malaysian energy mix which was 31% by 2025. Compared to the penetration of solar and wind power specifically in the European region, whose sharing was more than 50% of total generation, Malaysia currently only has 2% of its energy coming from RE generation sources, which mostly was provided by solar photovoltaic. In Malaysia’s energy sources point of view, wind RE-based power generation system was foreseen a promising potential provided the technology was suitably designed for low wind conditions. Therefore, the potentiality of the Jet-Engine inspired Wind Turbine operating under low-speed wind environment by mean of Computational Fluid Dynamics (CFD) numerical approach were explored in This study. The main objectives were to develop a reliable numerical model for accessing the capability of the Jet-Engine inspired Wind Turbine and to regulate its performance with influence of curly shroud on the induced flow. The conventional shrouded Wind Turbine has been modified which consist of a stator and a rotor blade covered by curly-shaped shroud adapting the concept of Jet-Engine. A constant wind speed of 5 m/s which was the average wind speed in Malaysia, and tip speed ratio (TSR) varies from 2 to 6 were specified in the simulation. The investigation discovered that the curly-shaped shroud gave an impact to the performance of the Wind Turbine as it can be reviewed from the comparison of the power coefficient on the Jet-Engine inspired Wind Turbine with shroud and without shroud. It was found that the shrouded Wind Turbine improved the power coefficient by 8.6% which was from 0.35 to 0.38. The effect of the curly shroud was also analysed by obtained the velocity and pressure contour from the ANSYS Fluent, where there was a swirl formation at the shroud as the air mixed at different angle, which causes the pressure drop and inlet velocity increased.

Fault detection and power quality analysis of wind turbine system using integrated systems

Growth in the need for electric energy and fossil fuel scarcity endorses renewable energy generation sources. The generation cost of electric power utilizing wind turbines is cost-effective and straightforward compared to other renewable energy sources (RES). Recently, hasty research and developments have been presented in wind turbines (WT) by researchers globally. Although wind-based energy production is more content, planting the WT is challenging. Maintaining the WT from fault incidence is highly crucial. The fault in the WT distresses the power quality of the produced energy. This condensed power quality affects the transmission systems, substations, and loading end of the renewable source. Also, gear malfunctioning is the primary reason for most of the downtime in wind turbines. This work successfully proposed and implemented a deoxyribonucleic acid (DNA) sequencing-based control technique to reduce the drive train vibration. Therefore, fault detection and monitoring in WTs play an active part in power production and quality maintenance. In this work, a vibration-grounded WT gearbox fault observing scheme is proposed to increase the power quality. Precisely, a wavelet is executed to chart the vibration gesture. Also, the current sensor gesture is implemented to discover the power quality variances associated with the WT's vibration magnitude.

Techno-economic analysis of Power-to-Gas plants in a gas and electricity distribution network system with high renewable energy penetration

Distributed generation, based on the exploitation of Renewable Energy Sources (RES), has increased in the last few decades to limit anthropogenic carbon dioxide emissions, and this trend will increase in the future. However, RES generation is not dispatchable, and an increasing share of RES may lead to inefficiencies and even problems for the electricity network. Flexible resources are needed to handle RES generation in order to support the delicate electricity generation and demand balance. Energy conversion technologies (P2X, Power to X) allow the flexibility of energy systems to be increased. These technologies make a connection between different energy sectors (e.g., electricity and gas) possible, and thus create new synergies within an overall multi-energy system. This paper analyzes how the P2G technology can be used at the distribution network level (both gas and electricity) to optimize the use of RES. In fact, in order to coordinate P2X resources, it is necessary to take into account the whole multi-energy scenario, and not just the electrical side: it therefore becomes fundamental to recognize the pros and cons that Balancing Service Providers (BSPs), composed of a number of P2G plants (representing the Balancing Responsible Providers, BRPs), may have when offering services to an electricity network. Moreover, the convenience of the decarbonization of the gas grid has been evaluated through the calculation of the levelized cost of Synthetic Natural Gas (LCSNG) for cost scenarios for the years 2030 and 2050, considering different assumptions about the cost of the surplus utilization of RES. The results show that LCSNG may vary from 47 to 319 €/MWh, according to the different configurations, i.e., only in the best-case scenario is the SNG cost comparable with the cost of natural gas, and hence does the P2G technology result to be profitable.