Due to the poor thermal characteristics of the air, the absorber roughness of solar air collectors is commonly artificially increased in order to enhance the heat transfer to the air stream. However, this is also accompanied by an undesirable increase in the pumping power due to increased friction losses. As a result, several authors have experimentally investigated several ways of maximizing the heat transfer while minimizing the friction losses of different absorbers, resulting in the development of semi-empirical functions relating the Nusselt number (a measure of heat transfer) and the friction factor (a measure of friction losses) to the Reynolds number and the roughness parameters considered for each absorber. The present paper reviews, considering the publications from the last ten years, these semi-empirical functions. Moreover, the optimum roughness parameters and operating conditions of the absorbers were estimated by finding the maximum values of two performance parameters (... [more]

This paper presents a novel integrated permanent magnet (PM) in-wheel motor (IWM) driving system for electric vehicles (EVs), in order to overcome the disadvantages of electromagnetic vibration and cogging torque in the topology scheme, on the basis of maintaining high output torque. Firstly, the transient magnetic field of the integrated PM motor is analyzed using the improved analytical subdomain model and finite element (FE) model. The harmonic component of magnetic force density (MFD) is obtained with no-load condition. Furthermore, the vertical dynamic model for the dynamic vibration absorber is established to investigate the influence of the magnetic force harmonic on the vibration response of the stator and rotor. On this basis, the multi-objective optimization design of the pole−slot structure parameters is carried out by using the adaptive weighted particle swarm optimization (AWPSO) algorithm. Finally, the optimization results are compared and verified by FE analysis. The inv... [more]

Distributed energy resource (DER) systems have elicited increasing attention and applications because of their excellent economic and environmental performance. However, uncertainties exist in such systems, preventing their potential advantages to be realized. In this study, an interval optimization-based model for the optimal design of DER systems is proposed, considering uncertainties in energy prices, renewable energy intensity, and load demands. Uncertainties are described as interval numbers, and the uncertain optimization model is transformed into a deterministic optimization problem using the order relationship and probability degree of interval numbers. The proposed model is applied to a typical hospital in Lianyungang, China, and its effectiveness is verified. One deterministic case and three uncertain cases are designed. The effects of uncertainties on system configuration and economic performance are also analyzed, and the optimal operation strategy under the three uncertain... [more]

Energy management and control of hybrid microgrids is a challenging task due to the varying nature of operation between AC and DC components which leads to voltage and frequency issues. This work utilizes a metaheuristic-based vector-decoupled algorithm to balance the control and operation of hybrid microgrids in the presence of stochastic renewable energy sources and electric vehicles charging structure. The AC and DC parts of the microgrid are coupled via a bidirectional interlinking converter, with the AC side connected to a synchronous generator and portable AC loads, while the DC side is connected to a photovoltaic system and an electric vehicle charging system. To properly ensure safe and efficient exchange of power within allowable voltage and frequency levels, the vector-decoupled control parameters of the bidirectional converter are tuned via hybridization of particle swarm optimization and artificial physics optimization. The proposed control algorithm ensures the stability o... [more]

Hybrid Electric Vehicles (HEVs) have been proven to be a promising solution to environmental pollution and fuel savings. The benefit of the solution is generally realized as the amount of fuel consumption saved, which by itself represents a challenge to develop the right energy management strategies (EMSs) for HEVs. Moreover, meeting the design requirements are essential for optimal power distribution at the price of conflicting objectives. To this end, a significant number of EMSs have been proposed in the literature, which require a categorization method to better classify the design and control contributions, with an emphasis on fuel economy, providing power demand, and real-time applicability. The presented review targets two main headlines: (a) offline EMSs wherein global optimization-based EMSs and rule-based EMSs are presented; and (b) online EMSs, under which instantaneous optimization-based EMSs, predictive EMSs, and learning-based EMSs are put forward. Numerous methods are in... [more]

Sunlight is a natural resource that can be harnessed by the photovoltaic conversion of sunlight into electricity-utilizing solar cells. The production of most common solar cells consists of a homojunction of a p-type and n-type silicon. The p—n junction is realized by the diffusion of impurities through one surface of the wafer. Silicon wafers have a typical dimension of 156 × 156 mm2 and a thickness of 0.15−0.2 mm. Groups of 50−100 solar cells are electrically connected and encapsulated to form a module. The required area for interconnection does not contribute to power generation, and the performance of larger area devices usually suffers from higher resistive losses. In the present work, a theoretical model of the geometric arrangement of the top contact metallic electrodes branched network in a photovoltaic cell is developed. The network structure of the electrodes is obtained from applying the constructal design methodology by the minimization of the overall resistance. As a resul... [more]

In this paper, the VVO (Volt/Var optimization) is proposed using simplified linear equations. For fast computation, the characteristics of voltage control devices in a distribution system are expressed as a simplified linear equation. The voltage control devices are classified according to the characteristics of voltage control and represented as the simplified linear equation. The estimated voltage of distribution networks is represented by the sum of the simplified linear equations for the voltage control devices using the superposition principle. The voltage variation by the reactive power of distributed generations (DGs) can be expressed as the matrix of reactance. The voltage variation of tap changing devices can be linearized into the control area factor. The voltage variation by capacitor banks can also be expressed as the matrix of reactance. The voltage equations expressed as simplified linear equations are formulated by quadratic programming (QP). The variables of voltage con... [more]

With the reform of electricity markets, demand response (DR) plays an important role in providing flexibility to the markets. Block bidding market is a new market mode, which is based on the concept of “the same quality, the same price”. The mechanism has great effects in reducing start-stop related costs. In this paper, we propose a double-sided non-cooperative game model in block bidding markets with a DR program. The model combines the advantages of block bidding and the simplicity of hourly bidding. In the model, one side is the non-cooperative game of supply-side power firms, and we propose a novel supply function bidding model based on block duration and load capacity to maximize each firm’s profit. The other side is the demand-side different types of customers, and we propose a DR model that combines hourly-various prices with the block bidding mechanism to maximize each customer’s payoff. The overall market optimization problem is solved by a distributed iterative algorithm, wh... [more]

The purpose of this article is to develop a methodology to apply to multi-objective optimization algorithms aimed at energy efficiency in buildings, considering aspects such as incremental cost, energy consumption, greenhouse gas emissions and energy efficiency levels of lighting and air conditioning system, according to the mandatory technical regulation in public buildings in Brazil. Presenting a solution to assist in the decision making of engineers, architects or building managers for the optimal arrangements’ choice for lighting and air conditioning equipment, considering each built environment and project profile. For the validation process, a basic building was created with 15 rooms spread over three floors, according to the most common construction parameters in the North of Brazil. First, different combinations of objective-function candidates were investigated to compose the multi-objective algorithm fitness function, analyzing its performance in two central scenarios: (1) ad... [more]

This study tackles the analysis of fixed external solar shading systems. The geometry of a building and of the shading system has been parametrically defined and a genetic optimization analysis has been carried out to identify an architectural solution that would allow the increase of energy savings, through a suitable window-to-wall ratio and an accurate design of the shading device. A multi-objective analysis has been performed with the aim of minimizing the energy consumption for space heating, cooling and artificial lighting, while ensuring the visual comfort of the occupants. The main goal of the study is to explore the influence of climatic context on the optimal design of shading devices. The analysis has been performed for three different latitudes across Europe. In all analyzed cases, a reduction of the annual energy consumption could be achieved, up to 42% if the optimal shading configuration is used. Moreover, the possibility of integrating the shading system with photovolta... [more]

To explore the flow mechanism and improve the performance of supersonic tandem rotor blades, the supersonic rotor Rotor37 is taken as the prototype and redesigned to an original supersonic tandem rotor. Then, based on the Kriging model, the physical programming method, and improved particle swarm optimization algorithm, a multi-objective optimization methodology is developed and applied to achieve the multi-objective optimization of the supersonic tandem rotor blades. Compared with Rotor37, the mass flow and surge margin of the original tandem rotor obviously increased. However, the efficiency of the original tandem rotor was slightly lower than Rotor37. After multi-objective optimization, compared with the original tandem rotor, the total pressure ratio and efficiency of the optimized tandem rotor significantly increased, and the efficiency increased by 1.6%. Further, the surge margin increased by 2.75%. The range and intensity of the high-loss region in the middle section of the opti... [more]

A modified closed binary Brayton cycle model with variable isothermal pressure drop ratios is established by using finite time thermodynamics in this paper. A topping cycle, a bottoming cycle, two isothermal heating processes and variable-temperature reservoirs are included in the new model. The topping cycle is composed of a compressor, a regular combustion chamber, a converging combustion chamber, a turbine and a precooler. The bottoming cycle is composed of a compressor, an ordinary regenerator, an isothermal regenerator, a turbine and a precooler. The heat conductance distributions among the six heat exchangers are optimized with dimensionless power output as optimization objective. The results show that the double maximum dimensionless power output increases first and then tends to be unchanged while the inlet temperature ratios of the regular combustion chamber and the converging combustion chamber increase. There also exist optimal thermal capacitance rate matchings among the wo... [more]

In the last century, the refrigerant R744 (carbon dioxide) has become an environmentally friendly solution in commercial refrigeration despite its particular issues related to the low critical temperature. The use of transcritical cycles in warm and hot countries reveals the necessity of adopting different configurations and technologies to improve this specific cycle. Among these, subcooling methods are well-known techniques to enhance the cooling capacity and the Coefficient of Performance (COP) of the cycle. In this work, an R600a dedicated mechanical subcooling system has been experimentally tested in an R744 transcritical system at different operating conditions. The results have been compared with those obtained using a suction-to-liquid heat exchanger (IHX) to determine the degree of improvement of the mechanical subcooling system. Using the experimental tests, a computational model has been developed and validated to predict the optimal subcooling degree and the cubic capacity... [more]

Renewable energy use can mitigate the effects of climate change. Solar energy is amongst the cleanest and most readily available renewable energy sources. However, issues of cost and uncertainty associated with solar energy need to be addressed to make it a major source of energy. These uncertainties are different for different locations. In this work, we considered four different locations in the United States of America (Northeast, Northwest, Southeast, Southwest). The weather and cost uncertainties of these locations are included in the formulation, making the problem an optimization-under-uncertainty problem. We used the novel Better Optimization of Nonlinear Uncertain Systems (BONUS) algorithm to solve these problems. The performance and economic models provided by the System Advisory Model (SAM) system from NREL were used for this optimization. Since this is a black-box model, this adds difficulty for optimization and optimization under uncertainty. The objective function and con... [more]

For high-voltage and extra-high-voltage consumers, the electricity cost depends not only on the power consumed but also on the contract capacity. For the same amount of power consumed, the smaller the difference between the contract capacity and the power consumed, the smaller the electricity cost. Thus, predicting the future power demand for setting the contract capacity is of great economic interest. In the literature, most works predict the future power demand based on a symmetric loss function, such as mean squared error. However, the electricity pricing structure is asymmetric to the under- and overestimation of the actual power demand. In this work, we proposed several loss functions derived from the asymmetric electricity pricing structure. We experimented with the Long Short-Term Memory neural network with these loss functions using a real dataset from a large manufacturing company in the electronics industry in Taiwan. The results show that the proposed asymmetric loss functio... [more]

As one of the most essential earth-moving equipment, cable shovels significantly influence the efficiency and economy in the open-pit mining industry. The optimal digging trajectory planning for each cycle is the base for achieving effective and energy-saving operation, especially for robotic excavation, in which case, the digging trajectory can be precisely tracked. In this paper, to serve the vision of cable shovel automation, a two-phase multi-objective genetic algorithm was established for optimal digging trajectory planning. To be more specific, the optimization took digging time and energy consumption per payload as objects with the constraints of the limitations of the driving system and geometrical conditions. The WK-55-type cable shovel was applied for the validation of the effectiveness of the multi-objective optimization method for digging trajectories. The digging performance of the WK-55 cable shovel was tested in the Anjialing mining site to establish the constraints. Bes... [more]

Nowadays, electricity market paradigms are constantly changing. On the one hand, the deployment of non-dispatchable renewable energy sources is bringing out the necessity of representing hourly dynamics in medium-term fundamental models. On the other, the promotion of new interconnection capacity and the integration of markets (as is the case of the European market) makes necessary the simultaneous modeling of multiple electricity systems. Thus, the large size of power markets, together with the consideration of uncertainty in some inputs, make it computationally intractable to work rigorously on an hourly detailed time span. Temporal aggregation, integer programming relaxation or less accurate generation modeling are usually employed to obtain reasonable computation times. However, the application of these techniques often leads to infeasible or suboptimal operational outputs. This paper proposes a new soft-linking methodology to meet reliable results from medium-term models, such as... [more]

Submersible pumps are now in high demand due to the sporadic occurrence of recent torrential rains. The current study was carried out to investigate the hydraulic characteristics of a submersible axial-flow pump with a swept impeller and to optimize the impeller and diffuser shapes of the pump to enhance the hydraulic performance. Three-dimensional Reynolds-averaged Navier−Stokes equations were solved with the shear stress transport turbulence model. The governing equations were discretized using the finite volume method, and unstructured tetrahedral and hexahedral meshes were used in the grid system. The optimal grid system was selected through a grid dependency test. A performance test for the submersible axial-flow pump was carried out experimentally, and the results of the numerical analysis were validated against the experimental results. The hydraulic efficiency and the total head were used as objective functions. For the first optimization, a multi-objective optimization was car... [more]

Interfacial interactions and wettability alteration remain as the main recovery mechanism when modified water is applied seeking to obtain higher oil recoveries. Fluid-fluid interaction could lead to the development of the called viscoelastic layer at the interface in oil-brine systems. This interfacial layer stabilizes thanks to the slow chemical interaction between oil polar compounds and salts in the brine. This study investigates the role of sulfate presence in injection brine that could possible lead to develop the interfacial viscoelastic layer and hence to contribute to the higher oil recovery. Furthermore, polymer flooding is performed in tertiary mode after brine flood to investigate/unlock the synergies and potential benefits of the hybrid enhanced oil recovery. Brine optimization is performed using the composition of two formation brines and four injection brines. Moreover, interfacial tension measurements and oil drop snap-off volume measurements are performed in parallel w... [more]

Nowadays, owing to the growing interest in renewable energy, Photovoltaic systems (PV) are responsible of supplying more than 500,000 GW of the electrical energy consumed around the world. Therefore, different converters topologies, control algorithms, and techniques have been studied and developed in order to maximize the energy harvested by PV sources. Maximum Power Point Tracking (MPPT) methods are usually employed with DC/DC converters, which together are responsible for varying the impedance at the output of photovoltaic arrays, leading to a change in the current and voltage supplied in order to achieve a dynamic optimization of the transferred energy. MPPT algorithms such as, Perturb and Observe (P&O) guarantee correct tracking behavior with low calibration parameter dependence, but with a compromised relation between the settling time and steady-state oscillations, leading to a trade off between them. Nevertheless, proposed methods like Particle Swarm Optimization- (PSO) based t... [more]

Integrating distributed generation into power grids creates various technical challenges for network operation. Volatility of renewable energy resources may increase the probability of blackouts. In order to restore networks fast, securely and reliably after blackouts, within the research project RestoreGrid4RES’s network restoration strategies, the related issues caused by distributed generation are investigated and novel methods to face those challenges are developed. This paper focuses on (i) algorithms to identify possible restoration paths, (ii) key performance indicators for the assessment of grid restoration options and (iii) an evaluation of the results for network restoration strategies.

Resource allocation problems are at the core of the smart grid where energy supply and demand must match. Multi-objective optimization can be applied in such cases to find the optimal allocation of energy resources among consumers considering energy domain factors such as variable and intermittent production, market prices, or demand response events. In this regard, this paper considers consumer energy demand and system-wide energy constraints to be individual objectives and optimization variables to be the allocation of energy over time to each of the consumers. This paper considers a case in which multi-objective optimization is used to generate Pareto sets of solutions containing possible allocations for multiple energy intensive consumers constituted by commercial greenhouse growers. We consider the problem of selecting a final solution from these Pareto sets, one of maximizing the social welfare between objectives. Social welfare is a set of metrics often applied to multi-agent sy... [more]

An effective way to enlarge the utilization of renewable energy consists in creating a correct interface between producers, consumers, and storage devices, i.e., a so-called “energy hub”. This opens a difficult challenge, especially in the urban areas where the availability of room for the installation of renewable plants is limited. This paper considers a university campus in the center of Lisbon that requires a significant amount of electricity and natural gas to support the internal activities. The idea is to fulfil part of the energy consumption of the campus with the excess of energy supplied by solar systems installed in the surrounding residential buildings. The goal is to find the number and type of solar equipment that maximize the reduction of annual energy costs of both residents and campus, where the campus is seen as a virtual storage. Results of the optimization show that, considering the best-exposed 100 buildings in a radius of 500 m around the campus, the campus can re... [more]

The effects of climate change seriously affect agriculture at different latitudes of the planet because periods of drought are intensifying and the availability of water for agricultural irrigation is reducing. In addition, the energy cost associated with pumping water has increased notably in recent years due to, among other reasons, the maximum demand charges that are applied annually according to the contracted demand in each facility. Therefore, very efficient management of both water resources and energy resources is required. This article proposes the integration of water-energy management in a virtual power plant (VPP) model for the optimization of energy costs and maximum demand charges. For the development of the model, a problem related to the optimal operation of electricity generation and demand resources arises, which is formulated as a nonlinear mixed-integer programming model (MINLP). The objective is to maximize the annual operating profit of the VPP. It is worth mentio... [more]

This research paper introduces a mathematical model to predict the performance of photovoltaic−thermal systems (PV-T), based on a thin layer flexible panel and an air pipe, by using the Trnsys® software tool to simulate energetic systems. The main advantage of these types of panels is their easy portability, making them ideal to address thermal needs in several scenarios. In the military field, there is an important concern about the use of sustainable energy; for instance, cooling facilities for infantry tents used in their deployments. In this research, a PV-T panel to cover electrical power needs for an infantry’s hangar unmanned air vehicle (UAV) is introduced. The proposed thermal model, based on the novelty of inertial mass (lump) as an approach to real panel behavior, has been validated through the comparison between Trnsys’ model simulation data, a real weather station, and data obtained in a test bed. Genopt’s simulation software is used to fit the model, allowing for the pred... [more]