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Abstract Effect of inclination angle to the thermal performance of a heat pipe photovoltaic/thermal system (HP-PV/T) system was rarely reported. In the present study, a HP-PV/T system was firstly constructed in an Enthalpy Difference Laboratory, where inclination angle was experimentally managed as the only variable. Meanwhile, a comprehensive numerical model for the HP-PV/T system was developed to validate the experiments. Particularly, a 3D model for the inclined heat pipe was also firstly involved. The simulation results show that liquid film thickness within the condenser or the evaporator stabilizes at a constant value at inclining condition. The relative filmwise thermal resistance of the condenser decreases first and then increases with inclination angle; while the evaporator shows an opposite trend to the condenser. The overall thermal resistance of solar heat pipe is mainly determined by the evaporator while the evaporator is mainly determined by the effective height of the liquid pool. The experimental and simulation results both indicate that the optimum inclination angle is 40°. The proposed model agrees well with the experimental results at big inclination angles (≥20°), it is practicable to reveal the influence of inclination angle to the thermal performance of a HP-PV/T system.

Abstract The high penetration of Renewable Energy Sources (RES) makes the power system unreliable due to its uncertain nature and to deal with this uncertainties installation of an Energy Storage System (ESS) is suggested. In this paper, the quantifying impact of ESS capacity on power system network reliability and relieving the congestion is analyzed. The proposed reliability assessment and congestion relief problem is formulated by considering generation cost and demand interruption cost for N-1 contingency criteria. The proposed algorithm manages the optimal charging and discharging of ESS to mitigate the uncertainties associated with RES and relieving the congestion. The impact of ESS capacity on reliability indices Expected Energy not Supplied (EENS) and Expected interruption Cost (ECOST) for Generating Companies (GENCOs), Transmission Companies (TRANSCOs), customers, and entire power system are calculated. The appropriate size of ESS is selected by the trade-off between investment cost of ESS and percentage change in EENS and ECOST value for the entire power system, GENCOs, TRANSCOs, and customers. The effectiveness of the proposed approach is tested on the modified IEEE RTS 24 bus system. The problem is modeled in the Generic Algebraic Solver (GAMS) environment and solved using CONOPT as an NLP solver.

Abstract Forecasting the future price of crude oil, which has an important role in the global economy, is considered as a hot matter for both investment companies and governments. However, forecasting the price of crude oil with high precision is indeed a challenging task because of the nonlinear dynamics of the crude oil time series, including chaotic behavior and inherent fractality. In this study, a new forecasting model based on support vector regression (SVR) with a wrapper-based feature selection approach using multi-objective optimization technique is developed to deal with this challenge. In our model, features based on technical indicators such as simple moving average (SMA), exponential moving average (EMA), and Kaufman’s adaptive moving average (KAMA) are utilized. SMA, EMA, and KAMA indicators are obtained from Brent crude oil closing prices under different parameters. The features based on SMA and EMA indicators are formed by changing the period values between 3 and 10. The features based on the KAMA indicator are obtained by changing the efficiency ratio (ER) period value, which is considered as fractality efficiency, between 3 and 10. The features are selected by the wrapper-based approach consisting of multi-objective particle swarm optimization (MOPSO) and radial basis function based SVR (RBFSVR) techniques considering both the mean absolute percentage error (MAPE) and Theil’s U values. The obtained empirical results show that the proposed forecasting model can capture the nonlinear properties of crude oil time series, and that better forecasting performance can be obtained in terms of precision and volatility than the other current forecasting models.

Abstract This paper aims to offer an efficient, simple and accurate cubic-order subparametric finite element technique utilizing 2-D automated mesh generator for microwave applications. The proposed technique utilizes the best discretization procedure, the finest quadrature rule and an excellent subparametric finite element algorithm for obtaining the numerical solutions of the Helmholtz equation. The high-quality automated mesh generator MATLAB code developed for the present work using HOmesh2d.m and CurvedHOmesh2d.m are provided. This approach utilizes up to cubic-order triangular mesh for arbitrary waveguide structures. The meshes with one side curved cubic-order triangular elements are proposed with parabolic arcs for curved waveguide structures. For regular waveguide structures with sharp edges having singularities, the utilization of unstructured cubic-order triangular meshes with refinement for the technique is proposed. The method is demonstrated for six different waveguide structures and the outcomes obtained are compared with the best available numerical or analytical results. The results show that the proposed technique produces an efficient and most accurate finite element results for the finite element analysis performed for waveguide structures with singularities and curved geometries as there is no curvature loss. Thus, the proposed subparametric finite element technique with the automated mesh generator is verified to yield a viable approach for getting the most precise numerical result for the 2-D Helmholtz equation in distinct waveguide cross-sections. Therefore, this approach can be used to produce the most efficient energy transfer for microwave applications.

Abstract This contribution experimentally evaluates and compares the performance of an ORC (organic Rankine cycle) system for stationary bottoming WHR (waste heat recovery) application operating with two different working fluids, SES36 and R245fa. The test rig is a regenerative cycle equipped with a single screw expander modified from a standard compressor characterized by a nominal shaft power of 11 kW. A total of 36 and 43 steady-state points are collected for SES36 and R245fa respectively, over a wide range of operating conditions by changing the expander rotational speed, the pump frequency and the cooling condenser flow rate. The performances of the ORC components are individually evaluated. A maximum expander isentropic efficiency of 60% is reached using SES36 at 3000 rpm, and a value of 52% is reached with R245fa at 3000 rpm. However, for a given pressure ratio the expander output power is higher with R245fa than with SES36. The overall performance of the ORC unit are investigated in terms of first and second law efficiencies and net output power for the two fluids. The results experimentally demonstrate the correlation between the working fluid critical temperature and the ORC unit working characteristics for low temperature waste heat recovery applications. Open experimental data are provided for both fluids.

Abstract The primary objective of CDEED (combined dynamic economic emission dispatch) problem is to determine the optimal power generation schedule for the online generating units over a time horizon considered and simultaneously minimizing the emission level and satisfying the generators and system constraints. The CDEED problem is bi-objective optimization problem, where generation cost and emission are considered as two competing objective functions. This bi-objective CDEED problem is represented as a single objective optimization problem by assigning different weights for each objective functions. The weights are varied in steps and for each variation one compromise solution are generated and finally fuzzy based selection method is used to select the best compromise solution from the set of compromise solutions obtained. In order to reflect the test systems considered as real power system model, the security constraints are also taken into account. Three new versions of DHS (differential harmony search) algorithms have been proposed to solve the CDEED problems. The feasibility of the proposed algorithms is demonstrated on IEEE-26 and IEEE-39 bus systems. The result obtained by the proposed CSADHS (chaotic self-adaptive differential harmony search) algorithm is found to be better than EP (evolutionary programming), DHS, and the other proposed algorithms in terms of solution quality, convergence speed and computation time.

Abstract We present an analytical model of a ground collector which uses thermal trap material instead of glazing on its top. The effects of different parameters e.g., the depth of the heat retrieval plane, thickness of the thermal trap material and the use of various materials such as concrete, sand and bricks above the heat retrieval plane are studied. The proposed system is compared with a conventional system.