Reliability is an important issue in electricity distribution systems, with strict regulatory policies and investments needed to improve it. This paper presents a mixed integer linear programming (MILP) model for clustering electrical customers, maximizing system reliability and minimizing outage costs. However, the evaluation of reliability and its corresponding nonlinear function represent a significant challenge, making the use of mathematical programming models difficult. The proposed heuristic procedure overcomes this challenge by using a linear formulation of reliability indicators and incorporating them into the MILP model for clustering electrical customers. The model is mainly defined on a density-based heuristic that constrains the set of possible medians, thus dealing with the combinatorial complexity associated with the problem of empowered p-medians. The proposed model proved to be effective in improving the reliability of real electrical distribution systems and reducing... [more]

Maximum power point tracking (MPPT) through an effective control strategy increases the efficiency of solar panels under rapidly changing atmospheric conditions. Due to the nonlinearity of the I−V characteristics of the PV module, the Sliding Mode Controller (SMC) is considered one of the commonly used control approaches for MPPT in the literature. This paper proposed a Backstepping SMC (BSMC) method that ensures system stability using Lyapunov criteria. A fuzzy inference system replaces the saturation function, and a modified SMC is used for MPPT to ensure smooth behavior. The proposed Fuzzy BSMC (FBSMC) parameters are optimized using a Particle Swarm Optimization (PSO) approach. The proposed controller is tested through various case studies on account of MPP’s dependence on temperature and solar radiation. The controller performance is assessed in partial shading conditions as well. The simulation results show that less settling time, a small error, and enhanced power extraction capa... [more]

This paper is concerned with the optimal design of axial probes, commonly used in the Non-Destructive Testing (NDT) of tube boiling in steam generators. The goal is to improve the low-frequency Foucault-current imaging of these deposits by designing a novel probe. The approach uses a combination of an inverse problem solver with global optimization to find the optimal probe characteristics by minimizing a function of merit defined using image processing techniques. The evaluation of the function of merit is computationally intensive and a surrogate optimization approach is used, incorporating a multi-particle search algorithm. The proposed design is validated through numerical experiments and aims to improve the accuracy and efficiency of identifying deposits in steam generator tubes.

Microalgal biomass is a promising alternative and renewable substrate for bioenergy production. The main problem for its commercial application is to obtain and keep a high level of production by providing microalgae with appropriate conditions for growth. The aim of this study was to determine optimal culture conditions such as temperature, photoperiod, and pH. The amount of biomass by gravimetry, optical density by spectrophotometry, and productivity were analyzed. Suitable values of cultivation parameters allowed for the increased growth and biomass productivity of Arthrospira platensis (4.24 g·L−1), Chlamydomonas reinchardtii (1.19 g·L−1), Chlorella vulgaris (2.37 g·L−1), and Dunaliella salina (4.50 g·L−1) and optical density for Ch. reinchardtii and C. vulgaris. These species had maximum biomass productivity of 0.72, 0.12, 0.36, and 0.77 g·L−1·d−1, respectively. Productivity was determined by cultivation temperature and for Ch. reinchardtii also by pH.

The shape design of the Tubular Linear Synchronous Motor (TLSM) is a critical engineeri ng optimization problem which was handled as single- and multi-objective optimization frameworks. However, the different practical constraints for the TLSM design must be efficiently guaranteed. This paper proposes a developed multi-objective shape design of the TLSM to maximize the operating force and minimize the flux saturation. In this regard, a Multi-objective Grey Wolf Optimizer (MGWO) is developed, including an outside archive with a predetermined size that is integrated for storing and retrieving Pareto optimal solutions. Using this knowledge, the grey wolf social structure would then be established, and, in the multi-objective searching environments, grey wolf hunting behavior would then be replicated. The superiority and effectiveness of the developed MGWO is assessed in comparison to the Multi-objective Flower Pollination Algorithm (MFPA), Multi-objective Lichtenberg Algorithm (MOLA), and... [more]

The antlion optimizer (ALO) algorithm is used in this article for maximum power point tracking (MPPT) of a solar array. The solar array consists of a single module, while there are 20 cells in the module. The voltage and current ratings of each cell are 2 V and 2.5 A, making a 100 W array in ideal condition. However, the voltage and current characteristics of the PV cell are unable to achieve maximum power. Therefore, the ALO was used for MPPT. The results of the ALO are compared with the traditional metaheuristic approaches, perturb and observe (P&O) and flower pollination (FP) algorithms. Comparison of the ALO with the stated algorithms is conducted for two cases: when solar irradiance is 1000 W/m2 and when it drops to 200 W/m2 at first then reaches 1000 W/m2. The change of irradiance is performed to simulate the partial shading condition. The simulation results depict that maximum power for the first case using the ALO reaches 91.3 W in just 0.05 s, while the P&O and PFA reach 90 W... [more]

The need for a low-cost interface between the grid and small (<250 kW) renewable distributed energy resources (DERs) is growing in importance as the number of small DERs continues to grow. In this study, a system architecture was proposed to investigate paths to an affordable interconnection for small renewable DERs.Then, a low-cost communication interface between a smart meter and smart inverter was installed using a commercially available bridge device. The interface device was selected based on an assessment concluding that it would be able to support the emerging advanced metering infrastructure (AMI) network. Next, messages were passed across the experimental end-to-end communication interface to test their speed and reliability. Success was based on whether the key functions defined in the standard IEEE 2030.5 were executed or not, which include set points, disconnect/reconnect, and Volt-VAr optimization. The results of the testing provided detailed insights into the benefits... [more]

The cyclic injection of CO2, referred to as the huff-n-puff (HnP) method, is an attractive option to improve oil recovery from unconventional reservoirs. This study evaluates the optimization of the CO2 HnP method and provides insight into the aspects of CO2 sequestration for unconventional reservoirs. Furthermore, this study also examines the impact of nanopore confinement, fluid composition, injection solvent, diffusivity parameters, and fracture properties on the long-term recovery factor. The results from over 500 independent simulations showed that the optimal recovery is obtained for the puff-to-huff ratio of around 2.73 with a soak period of fewer than 2.7 days. After numerous HnP cycles, an optimized CO2 HnP process resulted in about 970-to-1067-ton CO2 storage per fracture and over 32% recovery, compared to 22% recovery for natural depletion over the 30 years. The optimized CO2 HnP process also showed higher effectiveness compared to the N2 HnP scenario. Additionally, for rese... [more]

University buildings have high energy requirements due to their size, numerous users, and activities, which considerably contribute to environmental contamination. Implementing energy-saving solutions in these structures has a favorable influence on the economics and the conservation of energy resources. A higher education building’s energy behavior can be simulated using software to identify the optimal strategies that result in energy savings. In this research, Autodesk Revit, Autodesk Insight, and Green Building Studio are among the programs utilized to examine the energy efficiency of the university building in four European cities. Following the development of several energy-saving scenarios for the building, the offered solutions are evaluated based on their annual energy consumption, energy costs, and CO2 emissions. Finally, multicriteria analysis techniques such as the AHP and PROMETHEE are applied to choose the best scenario for each instance. The study’s findings indicate th... [more]

In this work, an induced pre-saturation tower (IPST) for oil−water separation was built on a semi-industrial scale, based on experimental results obtained on a laboratory scale prototype. The main strategy for generating these criteria was to increase the efficiency of the bench scale prototype, which is limited by conditions of low levels of automation and control, with the use of a biosurfactant as an auxiliary collector. The validation of the developed criteria allowed the construction of an IPST with three stages, all fed with previously saturated effluents. The IPST was built in stainless steel, with multistage centrifugal pumps and adapted to generate microbubbles without the use of saturation tanks or compressors. The most relevant operational parameters were selected using a fractional factorial design, while a central composite rotatable design (CCRD) followed by the application of the desirability function allowed to optimize the conditions for partial and global variables, t... [more]

This paper presents a multi-objective design optimization of a power transformer to find the optimal geometry of its core and the low- and high-voltage windings, representing the minimum power losses and the minimum core and copper weights. The optimal design is important because it allows manufacturers to build more efficient and economical transformers. The approach employs a manufacturer’s design methodology, which is based on the usage of the laws of physics and leads to an analytical transformer model with the advantage of requiring a low amount of computing time. Afterward, the multi-objective design optimization is defined along with its constraints, and they are solved using the Non-Sorting Genetic Algorithm III (NSGA-III), which finds a set of optimal solutions. Once an optimal solution is selected from the Pareto front, it is necessary to fine-tune it with the 3D Finite Element Analysis (FEA). To avoid the large computing times needed to carry out the 3D Finite Element (FE) m... [more]

This work uses design optimization of a power electronics converter to achieve the best levelized cost of energy in a PV application. The methodology uses detailed models of power electronics’ active and passive components to determine the cost and performances of the solid-state energy conversion and connect them to the system-level vision. The deterministic algorithm used for converter sizing allows taking into account a large number of variables and constraints. Methodology, models, and some illustrations of the results are provided in this paper. A sensitivity analysis was also conducted on the cost model.

Increasing sales of conventional fuel-based vehicles are leading to an increase in carbon emissions, which are dangerous to the environment. To reduce these, conventional fuel-based vehicles must be replaced with alternative fuel vehicles such as hydrogen-fueled. Hydrogen can fuel vehicles with near-zero greenhouse gas emissions. However, to increase the penetration of such alternative fuel vehicles, there needs to be adequate infrastructure, specifically, refueling infrastructure, in place. This paper presents a comprehensive review of the different optimization strategies and methods used in the location of hydrogen refueling stations. The findings of the review in this paper show that there are various methods which can be used to optimally locate refueling stations, the most popular being the p-median and flow-capture location models. It is also evident from the review that there are limited studies that consider location strategies of hydrogen refueling stations within a rural set... [more]

The operating parameters of the active direct methanol fuel cell (DMFC) are essential factors that affect cell performance. However, it is challenging to maintain the optimal maximum output power density due to the system’s complexity, the operating conditions variation, and the correlations between those parameters. This paper proposes an adaptive joint optimization method for fuel cell operating parameters. The methods include the adaptive numerical simulation of the operation parameters and the optimization for fuel cell performance. Based on orthogonal tests, a BP neural network is used to build a performance evaluation model that can quantify the influence of the operating parameters on fuel cell performance. The optimal combination of operating parameters for the fuel cell is obtained by a whale optimization algorithm (WOA) through the evaluation model. The experimental results show that the evaluation model could respond accurately and adaptively to the cell operating conditions... [more]

Offshore wind farms (OWF) are establishing their position to be the next strategy to expand the growth horizon of wind power production. For proper integration of OWFs into the existing grid, the voltage source converter (VSC)-based high voltage direct current (HVDC) transmission is being vastly utilized. For the stable operation of the existing grid, these VSC-HVDC-connected OWFs need to abide by the fault ride through (FRT) grid codes. Though there are many proposed solutions to tackle the FRT problem of the onshore wind farms, all of them cannot be applied to the OWFs. The OWFs cannot respond to the onshore faults depending solely on local measurements. Additionally, there are very few techniques available for FRT capability enhancement of the doubly fed induction generator (DFIG)-based OWFs. One notable solution is the use of the DC chopper resistor across the HVDC line. No intelligent controller is yet to be reported for better control of the DC chopper resistor. To enhance the pe... [more]

Urban areas have been responsible for the majority of the European Union (EU)-wide primary energy demand and CO2 emissions. To address this issue, the European Union introduced the concept of Positive Energy Districts (PEDs). PEDs are required to have an annual positive primary energy balance. However, if directly addressed in the literature, this energy balance only includes annually fixed primary energy factors and often neglects grid impacts. To bridge this gap, this work proposes a mathematical optimisation approach for PEDs, working towards an open-source model. The model’s main novelty is an hourly primary energy balance constraint. The performed case study on the island La Palma for both an urban and a rural neighbourhood show that the PED concept has a higher net present value (NPV) than solely buying electricity from the grid in all feasible cases. Depending on the space available for PV installations, the NPV increases between 29 and 31% and 25−27% for the rural and urban PED... [more]

Among surrounding information-gathering devices, cameras are the most accessible and widely used in autonomous vehicles. In particular, stereo cameras are employed in academic as well as practical applications. In this study, commonly used webcams are mounted on a vehicle in a dual-camera configuration and used to perform lane detection based on image correction. The height, baseline, and angle were considered as variables for optimizing the mounting positions of the cameras. Then, a theoretical equation was proposed for the measurement of the distance to the object, and it was validated via vehicle tests. The optimal height, baseline, and angle of the mounting position of the dual camera configuration were identified to be 40 cm, 30 cm, and 12°, respectively. These values were utilized to compare the performances of vehicles in stationary and driving states on straight and curved roads, as obtained by vehicle tests and theoretical calculations. The comparison revealed the maximum erro... [more]

Conventional energy production based on fossil fuels causes emissions that contribute to global warming. Accurate energy system models are required for a cost-optimal transition to a zero-emission energy system, which is an endeavor that requires a methodical modeling of cost reductions due to technological learning effects. In this review, we summarize common methodologies for modeling technological learning and associated cost reductions via learning curves. This is followed by a literature survey to uncover learning rates for relevant low-carbon technologies required to model future energy systems. The focus is on (i) learning effects in hydrogen production technologies and (ii) the application of endogenous learning in energy system models. Finally, we discuss methodological shortcomings of typical learning curves and possible remedies. One of our main results is an up-to-date overview of learning rates that can be applied in energy system models.

In this paper, we investigate implications of running a cooling system of two silicagel/water adsorption chillers powered by a district heating network. The devices are connected in series, i.e., the heating water output from the primary chiller is directed to the secondary one. In consequence, the secondary device must deal with an even lower driving temperature and with temperature fluctuations caused by the primary device. We have evaluated three factors that influence the operation of those coupled devices: synchronization of their operating cycles, selection of their cycle time allocations (CTAs), and changing the heating water mass flow rate. Numerical analyses indicate that the performance of the secondary chiller drops significantly if the coupled devices that use the same CTA run asynchronously. The decrease is largest if the shift between the operating cycles is x=0.375 and x=0.875. We found that it is possible to reduce the negative influence of the asynchronous operation by... [more]

In this paper, the design procedure and optimization process of a multi-phase flux-switching permanent magnet (FSPM) generator for wind power generation system is investigated. Two different optimization methods—stepwise optimization and global optimization—are implemented and applied to the optimization of the proposed nine-phase FSPM generator-based wind power system. Both the advantages and disadvantages of two optimization methods are compared and analyzed. The results indicate that the stepwise optimization can achieve good effects on individual optimization objectives, whereas the global optimization can not only achieve a good optimization effect on a single objective, but also can find design point on the Pareto front, which can effectively optimize different multi-objects. The electromagnetic performance of the nine-phase FSPM generator is verified by experiments on a prototyped machine and the measured results show that the proposed generator exhibits the favorable characteri... [more]

This paper deals with the problem of finding the optimal location and sizing of Energy Storage Systems in DC-electrified railway lines. These devices increment the use of the regenerated energy produced by the trains in the braking phases, as they store the energy to later provide to the catenary the excess of regenerated energy, that otherwise would be lost in the rheostats. However, these infrastructures require a high initial investment that, in some cases, may question their profitability. We propose a multi-method ensemble meta-heuristic to obtain the optimal solution to the problem, with a high level of accuracy. Specifically, the Coral Reefs Optimization with Substrate Layers (CRO-SL) is proposed, an evolutionary-type approach able to run different search procedures within the same population. We will evaluate the performance of the CRO-SL in the problem, and we will show that it performs better than the best known existing meta-heuristics for this problem.

Urban distribution in medium-sized cities faces a major challenge, mainly when deliveries are difficult in the city center due to: an increase of e-commerce, weak public transportation system, and the promotion of urban sustainability plans. As a result, private cars, public transportation, and freight transportation compete for the same space. This paper analyses the current state for freight logistics in the city center of Pamplona (Spain) and proposes alternative transportation routes and transportation modes in the last-mile city center distribution according to different criteria evaluated by residents. An analytic hierarchy process (AHP) was developed. A number of alternatives have been assessed considering routes and transportation modes: the shortest route criterion and avoiding some city center area policies are combined with traditional van-based, bike, and aerial (drone) distribution protocols for delivering parcels and bar/restaurant supplies. These alternatives have been e... [more]

To optimize the performance of the transcritical CO2 two-stage compression refrigeration system, the energy analysis and the exergy analysis are conducted. It is found that higher COP, lower compression power, and less exergy destruction can be achieved when the auxiliary gas cooler is applied. Moreover, the discharge temperature of the compound compressor (HPS) can be reduced by decreasing the temperature at the outlet of the auxiliary gas cooler (Tagc,out). When the Tagc,out is reduced from 30 to 12 °C, the discharge temperature of the compound compressor (HPS) can be decreased by 13.83 °C. Furthermore, the COP and the exergy efficiency can be raised by enhancing the intermediate pressure. Based on these results, the optimizations of system design and system operation are put forward. The application of the auxiliary gas cooler can improve the performance of the transcritical CO2 two-stage compression refrigeration system. Operators can decrease the discharge temperature of the compo... [more]

The implementation of district heating networks into cities is a main topic in policy planning that looks for sustainable solutions to reduce CO2 emissions. However, their development into cities is generally limited by a high initial investment cost. The development of optimization methods intended to draft efficient systems using heating consumption profiles into a prescribed geographic area are useful in this purpose. Such tools are already referred to in the scientific literature, yet they are often restricted to limit the computational load. To bridge this gap, the present contribution proposes a multi-period mixed integer linear programming model for the optimal outline and sizing of a district heating network maximizing the net cash flow based on a geographic information system. This methodology targets a large range of problem sizes from small-scale to large-scale heating networks while guaranteeing numerical robustness. For sake of simplicity, the developed model is first appl... [more]

Green hydrogen technology has recently gained in popularity due to the current economic and ecological trends that aim to remove the fossil fuels share in the energy mix. Among various alternatives, biogas reforming is an attractive choice for hydrogen production. To meet the authorities’ requirements, reforming biogas-enriched natural gas and sole biogas is tempting. Highly effective process conditions of biogas reforming are yet to be designed. The current state of the art lacks proper optimization of the process conditions. The optimization should aim to allow for maximization of the process effectiveness and limitation of the phenomena having an adverse influence on the process itself. One of the issues that should be addressed in optimization is the uniformity of temperature inside a reactor. Here we show an optimization design study that aims to unify temperature distribution by novel arrangements of catalysts segments in the model biogas reforming reactor. The acquired numerical... [more]