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In this research study, a newly proposed hybrid device of Wave Energy Converters (WEC) is investigated by considering computational fluid dynamic (CFD)-based numerical wave tanks (NWTs). The open-source CFD code solver, OpenFOAM (Open Field Operation and Manipulation) is implemented, which is numerically solved the Reynolds-averaged Navier–Stokes (RANS) equations to simulate the two-phase flow. The hybrid system consists of an Oscillating Water Column (OWC) and a point absorber (Wavestar) device installed in a shared platform. The main goal is to recognize how wave diffractions caused by the adjacent floating body could affect the rate of power absorption by the Fixed-OWC. This aim is followed by a 2D numerical analysis of three different installation configurations, variable intervals between the Wavestars' buoy and the Fixed-OWCs' front wall, in four different wavelengths with and without Power Take-Off (PTO). Finally, the efficiency characteristics of the integrated system such as free surface velocity and air pressure within the chamber, besides floating body motions are investigated and compared for the hybrid system. Although the overall assessment for 28 different case studies reveals an efficiency reduction in some cases, the superiority of this hybrid plan is recording several incremental efficiency rates.

Abstract In this study, the external surface of a finned tube was coated by 13X zeolite powder, and the CO2 adsorption equilibrium and dynamics were investigated experimentally. A slurry consisting of dionized water, 13X zeolite powder, and Acrylic latex emulsion (ALE) was used to coat the finned tube. The finned tube was coated by deep coating method. The equilibrium isotherms were measured at the range of 20–90 °C and fitted well by the dual-site Langmuir model. The average difference between the model and the results obtained from the experiments is about 2.5%. The nitrogen adsorption/desorption at 77 K was used for characterization of adsorbents. A 11% reduction was observed in pore volume and surface area. The dynamic test showed that the desorption of adsorbed CO2 takes place in about 14 s which is an order of magnitude faster than the fastest developed method. A conservative criterion was developed for estimating adsorbent working capacity. This criterion showed that the working capacities of the adsorbent are about 80% of its ideal values.

Abstract This study presents an optimal power management for a microgrid (MG) in distribution market environment. The MG operator is able to have interactions with the distribution market operator (DMO) and adjacent MG (AMG) operator to supply its local loads. The DMO regulates the electricity market, and assigns the electricity price and power profile for the MG. The motivation behind the use of The DMO is that it works as an entity between MG and independent system operator (ISO) in order to guarantee a flexible operation by reducing power fluctuation and reduce the unintentional peak loads in low market price hours. The unused power capacity in AMG is used during the islanded hours through an additional interconnection point connected to the MG. Using this method reduces the need for installing new generation resources, which will be a practical and economical solution for MG developer. This MG which is able to provide power from distribution market and the AMG with two interconnection points is named dependent MG (DMG). A market-based stochastic model containing distribution market constraints and AC power flow formulations employs conditional value at risk (CVaR) methodology to capture the loads and wind uncertainties. The effectiveness of the presented model is evaluated on a 20 kV test system using different case studies. In this test system, the operator is the owner of all generation units. The numerical analysis explicate that presented model reduces the operation cost of DMG with the aim of responsive loads, unused power capacity, energy storage system (ESS) and power generation units. The market-based scheduling also provides operational flexibility for distribution system by adjusting flexibility limit of market constraints. It is also shown that changing risk preferences level changes the power generation pattern in ESS and causes a costly operation of resources in risk-averse strategy. The competence of this model is significant when the preventive maintenance (PM) program is carried out, and the DMG should rely on its flexible resources and AMG’s available power capacity, which could reduce the load shedding.

Diminishing fuel resources and stringent emission mandates have demanded cleaner combustion and increased fuel efficiency. Three water addition rates, i.e., 2, 4, and 6 wt% in biodiesel-diesel blend (B5) was investigated herein. Combustion characteristics of the emulsified fuel blends were compared in a naturally-aspirated diesel engine at full load and different engine speeds. More specifically, biodiesel was produced from waste cooking oil (WCO) and to further increase waste utilization, recycled biodiesel wastewater was used as additive in B5. The result obtained showed that low-level water addition (i.e., 2 and 4 wt%) in B5 led to different results from those obtained using higher water addition rates (i.e., >5 wt%) reported by the previous studies. In more details, the findings of the present study revealed that low level water addition in B5 could considerably reduce CO, HC, CO2, and NOx emissions. Among water-containing B5 fuel emulsions, the optimal water addition level in terms of engine performance parameters and emissions was found at 4 wt%. In particular, the emitted CO2, HC, and NOx were decreased by over 8.5%, 28%, and 24%, respectively, at maximum speed of 2500 rpm.

Power to gas units and gas turbines have provided considerable opportunities for bidirectional interdependency between electric power and natural gas infrastructures. This paper proposes a series of multi-step strategy with surrogate Lagrange relaxation for operation co-optimization of an integrated power and natural gas system. At first, the value of coordination capacity is considered as a contract to avoid dysfunction in each system. Then, the uncertainties and risks analysis associated with wind speed, solar radiation, and load fluctuation are implemented by generating stochastic scenarios. Finally, before employing surrogate Lagrange relaxation, the non-linear and non-convex gas flow constraint is linearized by two-dimension piecewise linearization. In the proposed procedure, constraints for energy storages and renewable energy sources are included. Two case studies are employed to verify the effectiveness of the proposed method. The surrogate Lagrange relaxation approach with coordination branch & cut method enhances the accuracy of convergence and can effectively reduce the decision-making time.

Abstract This paper proposes a stochastic framework to augment the integration of variable renewable energy sources (VRESs) in power system scheduling. In this way, the fast-response capability of gas-fired generator units (GFGUs) and vehicle-to-grid (V2G) capability of electric vehicles (EVs) can play important roles in large-scale integration of VRESs. However, the growth of GFGUs utilization can increase the grade of interdependency between power and natural gas systems. In this condition, the power system tends to demand more reliability and flexibility from the natural gas system, which creates new challenges in power system scheduling. The likely significant growth of EVs can solve this challenge and reduce the correlation between power and natural gas systems, bringing new opportunities for power system scheduling. However, a considerable literature in the field of operation of GFGUs and EVs has only focused on using the hourly discrete time model (HDTM). Undoubtedly, the major limitation of HDTM is its inability to handle the fast sub-hourly dispatch of GFGUs and energy storage capability of EVs. Accordingly, in this paper, this limitation has been solved by the operation of both energy systems with a continuous time model (CTM). The reliability test system with a ten-node gas transmission system has been analysed to show the effectiveness of the proposed problem.

The development of smart energy systems is a crucial enabler of the transition towards a decarbonized renewable energy (RE)-based society with universal energy access as it provides flexibility to integrate variable RE sources. This paper analyzes the development of new RE-based smart energy systems while introducing energy technologies and effective methods for energy systems development, recent progress of energy systems by using RE, practical government measures in pioneer countries for energy systems, development with quantitative data for these countries, and PEST (political, economic, socio-cultural and technological) analysis. Our findings show that the development of smart energy systems requires appropriate policies and that thorough collaboration between all national executive agents like national and local governments and citizens in this regard is crucial. Smart energy system development needs to be tailored to local conditions, and due consideration must be given new technologies and methods for development, correct policies, investment, collaboration national/local and their citizens, societal support, and citizens acceptance.

Abstract Electric spring (ES) as a breakthrough in power electronics has led to a revolution in demand-side management. This paper presents flexible power management (FPM) of a networked microgrid (MG) in the presence of renewable energy sources (RESs) and flexibility sources (FSs). The FSs include the novel topology of the integrated unit of ES with electric vehicles (EVs) parking (IUEE) and incentive-based demand response program (DRP). The proposed FPM model is formulated as an optimization problem that minimizes the difference between the expected energy cost and the expected profit of FSs' flexibility subject to the AC optimal power flow (AC-OPF), RESs, FSs, and MG flexibility constraints. In the proposed model, flexibility pricing is performed for both upward and downward flexibility services in which the expected flexibility profit is proportional to the product of the FSs' flexibility and flexibility incentive price (FIP). Further, this paper uses a stochastic programming to model uncertain parameters associated with load demand, energy prices, maximum RES generation capacity, and EVs’ parameters. Finally, the potential of the proposed FPM model in improving the economic, operational and flexibility conditions of the MG is investigated through implementation of the proposed model on the 32-bus radial MG.