In long-distance gas transmission pipelines, there are many booster compressor stations consisting of parallel compressors that provide pressure for the delivery of natural gas. So, it is economically important to optimize the operation of the booster compressor station. The booster compressor station optimization problem is a typical mixed integer nonlinear programming (MINLP) problem, and solving it accurately and stably is a challenge. In this paper, we propose an improved salp swarm algorithm based on good point set, adaptive population division and adaptive inertia weight (GASSA) to solve this problem. In GASSA, three improvement strategies are utilized to enhance the global search capability of the algorithm and help the algorithm jump out of the local optimum. We also propose a constraint handling approach. By using semi-continuous variables, we directly describe the on or off state of the compressor instead of using auxiliary binary variables to reduce the number of variables a... [more]

This paper proposes a modified quasi-opposition-based grey wolf optimization (mQOGWO) method to solve complex constrained optimization problems. The effectiveness of mQOGWO is examined on (i) 23 mathematical benchmark functions with different dimensions and (ii) four practical complex constrained electrical problems that include economic dispatch of 15, 40, and 140 power generating units and a microgrid problem with different energy sources. The obtained results are compared with the reported results using other methods available in the literature. Considering the solution quality of all test cases, the proposed technique seems to be a promising alternative for solving complex constrained optimization problems.

Latent heat storage technology is widely used in solar power generation. Aiming to enhance the energy utilization rate to a greater extent, an innovative fan-shaped structure has been proposed to construct the metal fins of the shell-and-tube thermal storage device. The enthalpy method is used to simulate the heat storage process and focuses on the influence of inlet conditions on heat transfer. The influence of the fin structure on the melting properties of phase change material has been studied. The results show that increasing inlet temperature and inlet flow rate is a convenient and effective way to improve energy efficiency. As the inlet temperature is increased from 343 K to 358 K, the total heat storage and energy efficiency are improved by 13.4% and 10.2%, respectively, and the melting time is reduced by 36.2%. As the flow rate is increased from 3 L/min to 9 L/min, the complete melting time is reduced by 33.4%. Energy efficiency peaks at a flow rate of 5 L/min. Reasonable optim... [more]

Catalytic upgrading of vapors from pyrolysis of triglycerides materials is a promising approach to achieve better conversions of hydrocarbons and production of liquid biofuels. Catalytic cracking often shows incomplete conversion due to distillation of initial reaction products and the addition of a second catalytic reactor, whereas pyrolytic vapors are made in contact to a solid catalyst was applied to improve the physical-chemical properties and quality of bio-oil. This work investigated the effect of catalyst content and reaction time by catalytic upgrading from pyrolysis vapors of residual fat at 450 °C and 1.0 atmosphere, on the yields of reaction products, physicochemical properties (density, kinematic viscosity, refractive index, and acid value), and chemical composition of organic liquid products (OLP), over a catalyst fixed bed reactor, in semi pilot scale. Pellets of red mud chemically activated with 1.0 M HCl were used as catalysts. The thermal catalytic cracking of residual... [more]

Refrigeration systems based on cooling towers and chillers are widely used equipment in industrial buildings, such as shopping centers, gas and oil refineries and power plants, among many others. Cooling towers are used to recover the heat rejected by the refrigeration system. In this work, the refrigeration is composed of cooling towers dotted with ventilators and compression chillers. The growing environmental concerns and the current scenario of scarce water and energy resources have lead to the adoption of actions to obtain the maximum energy efficiency in such refrigeration equipment. This backs up the application of computational intelligence to optimize the operating conditions of the involved equipment and cooling processes. In this context, we utilize multi-objective optimization algorithms to determine the optimal operational setpoints of the cooling system regarding the cooling towers, its fans and the included chillers. We use evolutionary multi-objective optimization to pr... [more]

Photovoltaic (PV) systems have been used extensively worldwide over the past few years due to the mitigation of fossils fuels; it is the best source because of its eco-friendly nature. In PV systems, the main research area concerns its performance under partial shading (PS) and complex partial shading (CPS) conditions. PV sources perform perfectly under ideal conditions, but under practical conditions, their performance depends upon many factors, including shading conditions, temperature, irradiance, and the angle of inclination, which can bring a photovoltaic or solar system into a PS or CPS condition. In these conditions, many power peaks appear, and it is hard to find the global peak among many local peaks. The ability to track the maximum power peak and maintain it to avoid fluctuations depends on the maximum power point tracking (MPPT) technique used in a photovoltaic system. This article is based on the implementation of a hybrid algorithm, combining Harris hawk’s optimization (H... [more]

The aim of this work is to optimize biogas production from thermophilic dry anaerobic digestion (AD) of the organic fraction of municipal solid waste (OFMSW) by comparing various operational strategies to reduce ammonia inhibition. A pilot-scale plug flow reactor (PFR) operated semi-continuously for 170 days. Three scenarios with different feedstock, namely solely OFMSW, OFMSW supplemented with structural material, and OFMSW altered to have an optimal carbon-to-nitrogen (C/N) ratio, were tested. Specific biogas production (SGP), specific methane production (SMP), the biogas production rate (GPR), and bioenergy recovery were evaluated to assess the process performance. In addition, process stability was monitored to highlight process problems, and digestate was characterized for utilization as fertilizer. The OFMSW and the structural material revealed an unbalanced content of C and N. The ammonia concentration decreased when the optimal C/N ratio was tested and was reduced by 72% if com... [more]

The cogeneration of power and heat was investigated for Biomass Boiler−Organic Rankine Cycle (BB−ORC) plants with the characteristics of typical units, such as the 1 MWel Turboden ORC 10 CHP. The thermodynamic analysis of the ORC unit was undertaken considering forty-two (42) dry and isentropic candidate pure working fluids. Only subcritical Rankine cycles were considered, and the pinch point temperature differences for the evaporation and condensation heat exchangers were kept constant at 10 °C in all cases. The study provides an original and unique screening of almost all pure working fluids that are considered appropriate in the literature under the same operation and optimization conditions and compiles them into a single reference. In its conclusions, the study provides useful fluid selection and design guidelines, which may be easily followed depending on the optimization objective of the ORC designer or operator. In general, hydrocarbons are found to lie in the optimum middle ra... [more]

Against a background of the energy internet and low-carbon electricity, regional integrated energy system (RIES) has become a key way to achieve sustainable energy development, leading to reduced operating costs and system carbon emissions, and improved system operating efficiency. This paper puts forward a low-carbon economic dispatching optimization method for RIES with a heating network and power-to-gas (P2G). First, the heating network model and the mathematical model of P2G were constructed. Second, the carbon trading mechanism was introduced, the objective function being: to minimize the sum of the system operating cost and carbon trading cost; and ensure that the balance of cooling, heating, electric power, and the operating constraints—of RIES and the heating network—were comprehensively considered. Finally, the CPLEX optimization software simulation was used. The results show that the proposed method can take into account both low-carbon and economic factors, and can provide a... [more]

The main problem of fluid sampling during well testing of reservoirs with near-critical fluids (gas condensate and volatile oil) is due to the fact that even a small pressure drawdown usually leads to the formation of a two-phase mixture in the bottom hole area, and it is almost impossible to take representative samples with downhole samplers or a formation tester. Sampling via test-separator and the current non-separation methods are also imperfect. An alternative method—MIKS (Multiphase IsoKinetic Sampling)—of gas condensate well testing was proposed, which is based on emulsifying a multiphase flow to particles of about 1−10 μm. Thereby MIKS would eliminate the problem of particle slippage in a homogeneous flow and enables high-quality sampling directly from the flowmeter line. The initial formation fluid is characterized by the maximum value of the condensate-gas ratio (CGR). Therefore, first, the well effluent would be adjusted to the mode with the maximum CGR using a choke manifol... [more]

Eco-driving algorithms optimize the speed profile to reduce the energy consumption of a vehicle. This paper presents an eco-driving algorithm for battery electric powertrains that applies a split loss integration approach to incorporate the component losses. The algorithm consistently uses loss models to overcome the drawbacks of efficiency maps, which cannot represent no-load losses at zero torque. The use of loss models is crucial since the optimal solution includes gliding, during which there are no-load losses. An analysis shows, that state-of-the-art nonlinear programming algorithms cannot represent these no-load losses at zero torque with a small modeling error. To effectively compute the powertrain losses with only a small error in comparison to the measurement data, we introduce a tailored combination of nonlinear inequality constraints that interleave two polynomial fits. This approach can properly represent reality. We parameterize the algorithm and validate the vehicle model... [more]

This paper presents an energy-saving strategy that was applied to a parallel variable frequency pump system of a water circulation pumping station. Firstly, the mathematical model of shaft power consumption for the parallel pump system was established using quadratic polynomial fitting, with some constraints configured according to the system’s water supply demands. Then, the algorithm program was designed with the goal of minimizing the energy consumption through the application of an improved differential evolution algorithm. Additionally, the energy consumption model and constraints were integrated and simplified in order to adapt to the algorithm calculation. In the end, the algorithm was implemented according to the pump design parameters and supply targets of the pumping station. Meanwhile, a comparison was done between the differential evolution (DE) algorithm and the genetic algorithm (GA). Furthermore, an experimental test was conducted in an aluminum company in order to verif... [more]

The scramjet of hypersonic vehicles faces severe high-temperature challenges, but the heat sink available for scramjet cooling is extremely finite. It is necessary to optimize its power and thermal management system (PTMS) with a finite heat sink of hydrocarbon fuel. This paper proposes a two-level optimization method for the PTMS of hypersonic vehicles at Mach 6. The PTMS is based on a supercritical carbon dioxide (SCO2) closed Brayton cycle, and its heat sink is airborne hydrocarbon fuel. System-level optimization aims to obtain the optimal system parameters for the PTMS. The minimum fuel weight penalty and the minimum heat sink consumption of fuel are the optimization objectives. The segmental (SEG) method is used to analyze the internal temperature distribution of fuel−SCO2 heat exchangers in the system-level optimal solution set. This ensures the selected optimal solutions meet the requirement of a pinch temperature difference greater than or equal to 10 °C. Further, the component... [more]

With the increasing interdependence among energies (e.g., electricity, natural gas and heat) and the development of a decentralised energy system, a novel retail pricing scheme in the multi-energy market is demanded. Therefore, the problem of designing a customised multi-energy pricing scheme for energy retailers is investigated in this paper. In particular, the proposed pricing scheme is formulated as a bilevel optimisation problem. At the upper level, the energy retailer (leader) aims to maximise its profit. Microgrids (followers) equipped with energy converters, storage, renewable energy sources (RES) and demand response (DR) programs are located at the lower level and minimise their operational costs. Three hybrid algorithms combining metaheuristic algorithms (i.e., particle swarm optimisation (PSO), genetic algorithm (GA) and simulated annealing (SA)) with the mixed-integer linear program (MILP) are developed to solve the proposed bilevel problem. Numerical results verify the feas... [more]

A multilayer soil structure model is fundamental to design grounding systems. A new method is presented to invert the structure parameters of horizontal multilayer soil. The structure parameters of soil are determined by analyzing the kernel function of the integral equation of the apparent resistivity. The essence of the proposed method avoids the difficulties encountered in general optimization methods; namely, the calculation of the apparent resistivity and its derivative.

Gas Brayton cycles have been considered the next promising power cycles for microreactors. Especially the open-air and closed supercritical CO2 (S-CO2) Brayton cycles have received attention due to their high thermal efficiency and compact component sizes when compared to the steam Rankine cycle. In this research, the performances of the open-air and closed S-CO2 Brayton cycle at microreactor power range are compared with polytropic turbomachinery efficiency. When optimizing the cycle, three different optimization parameters are considered in this paper: maximum efficiency, maximum cycle specific work, and maximum of the product of both indicators. For the air Brayton cycle, the maximum of the product of both indicators allows to consider both efficiency and specific work while optimizing the cycle. However, for the S-CO2 Brayton cycle, the best performing conditions follow either maximum efficiency or the maximum cycle specific work conditions. In general, the S-CO2 power cycle should... [more]

The design of moisture-durable building enclosures is complicated by the number of materials, exposure conditions, and performance requirements. Hygrothermal simulations are used to assess moisture durability, but these require in-depth knowledge to be properly implemented. Machine learning (ML) offers the opportunity to simplify the design process by eliminating the need to carry out hygrothermal simulations. ML was used to assess the moisture durability of a building enclosure design and simplify the design process. This work used ML to predict the mold index and maximum moisture content of layers in typical residential wall constructions. Results show that ML, within the constraints of the construction, including exposure conditions, does an excellent job in predicting performance compared to hygrothermal simulations with a coefficient of determination, R2, over 0.90. Furthermore, the results indicate that the material properties of the vapor barrier and continuous insulation layer... [more]

Many repeated manual feature adjustments and much heuristic parameter tuning are required during the debugging of machine learning (ML)-based transient stability assessment (TSA) of power systems. Furthermore, the results produced by ML-based TSA are often not explainable. This paper handles both the automation and interpretability issues of ML-based TSA. An automated machine learning (AutoML) scheme is proposed which consists of auto-feature selection, CatBoost, Bayesian optimization, and performance evaluation. CatBoost, as a new ensemble ML method, is implemented to achieve fast, scalable, and high performance for online TSA. To enable faster deployment and reduce the heavy dependence on human expertise, auto-feature selection and Bayesian optimization, respectively, are introduced to automatically determine the best input features and optimal hyperparameters. Furthermore, to help operators understand the prediction of stable/unstable TSA, an interpretability analysis based on the S... [more]

This paper presents a current literature review (from the years 2017−2022) on issues related to the application of power system stabilizers (PSSs) for damping electromechanical swings in power systems (PSs). After the initial selection of papers found in the databases used, over 600 publications were qualified for this review, of which 216 were subjected to detailed analysis. In the review, issues related to the following problems are described: applications of classic PSSs, applications of new stabilizer structures based on new algorithms (including artificial intelligence), development of new methods for tuning PSSs, and operation of PSSs in PSs with high power generation by renewable sources. Describing individual papers, the research methods used by the authors (simulations, measurement methods, and a combination of both) are specified, attention is paid to the waveforms presented in the papers, and reference is made to the types of PSs in which PSSs (large multimachine, reflecting... [more]

The valorization of chicken manure via pyrolysis can give biowaste a second life to generate value and contribute to the circular economy. In the present study, the thermal degradation and pyrolysis characteristics of chicken manure pyrolysis were investigated via thermogravimetric analyses (TGA) coupled with optimization methods. Thermogravimetric data were obtained for the samples at five heating rates of 5, 10, 20, 30 and 50 °C/min over a range of temperature under inert conditions. The manure devolatilization process was initiated at between 328 and 367 °C to overcome the global activation energy barrier. The determined activation energy of the manure via Flynn−Wall−Ozawa (FWO), Kissinger−Akahira−Sunose (KAS), Friedman and Kissinger methods was in the range of 167.5−213.9 kJ/mol. By using the particle swarm optimization (PSO) method, the pyrolytic kinetic parameters of the individual component present in the manure were calculated, in which the activation energy for cellulose (227.... [more]

To investigate the effects of different passage structures on the aerodynamic performance of the transonic fans, this paper develops a reliable and practical quasi-3D optimization method for the hub based on the experimental data of Stage 67. In the method, the hub profile of Stage 67 can be optimized without changing the geometrical data of the blades. The optimization results show that stream tube diffusion characteristics depend on the hub profile’s curvature in the boundary layer near the hub. In the front part of the hub, the end wall with a concave construction can enhance the expansion of the stream tubes near the root of the rotor blade, which helps control the diffusion flow of viscous fluid effectively to decrease the low-energy fluid’s energy degradation and radial secondary flow in the boundary layer. In the latter part of the hub, the end wall with a convex construction facilitates the shrinkage of stream tubes to decrease the secondary flow loss and separated flow loss by... [more]

To solve the problem of evenly mixing flocculant and sewage, a new type of two-chamber mechanical pipe mixer was numerically calculated and its working principle was studied by means of the internal flow field. The single factor numerical simulation and analysis of some of the structural parameters in the mixer were carried out to determine the influence of different parameters on the results. Latin hypercube sampling was used to design 100 sets of test tables for the four variables of the branch pipe diameter, sewage flow rate, the installation height of the impeller, and the angle of the deflector. The results were optimized using the SVR-DE algorithm. After optimization, the variation coefficient of export flocculant mixing uniformity was 16.02%, which was increased by 74.94% compared with the initial 63.921%. The power consumption of the impeller was reduced by 8.30%. The concentration curves of the flocculant at different positions of the outlet tube could quickly converge to the... [more]

Gas and downhole water sink-assisted gravity drainage (GDWS-AGD) is a new process of enhanced oil recovery (EOR) in oil reservoirs underlain by large bottom aquifers. The process is capital intensive as it requires the construction of dual-completed wells for oil production and water drainage and additional multiple vertical gas-injection wells. The costs could be substantially reduced by eliminating the gas-injection wells and using triple-completed multi-functional wells. These wells are dubbed triple-completion-GDWS-AGD (TC-GDWS-AGD). In this work, we design and optimize the TC-GDWS-AGD oil recovery process in a fictitious oil reservoir (Punq-S3) that emulates a real North Sea oil field. The design aims at maximum oil recovery using a minimum number of triple-completed wells with a gas-injection completion in the vertical section of the well, and two horizontal well sections—the upper section for producing oil (from above the oil/water contact) and the lower section for draining wat... [more]

This manuscript proposes a novel approach for determining phase and neutral-current-ripple RMS in grid-connected four-leg inverters with the neutral inductor. The harmonic pollution is determined for any arbitrary pulse width modulation (PWM) technique and a generic value of the neutral inductor. Thanks to the proposed approach, it is possible to describe the neutral inductor in a parametric way with respect to phase inductors and obtain a wide range of results, ranging from a direct neutral connection (no neutral inductor) to a conventional three-phase inverter (no fourth wire) for any value of modulation index and common mode injection. The results permit one to compare different design choices in multiple scenarios effectively. The findings were validated by numerical simulations and experimental tests employing the most popular PWM techniques, such as space vector PWM (SVPWM) and discontinuous PWM (DPWM).

Since the power grid grows and the necessity for higher system efficiency is due to the increasing number of renewable energy penetrations, power system operators need a fast and efficient method of operating the power system. One of the main problems in a modern power system operation that needs to be resolved is optimal power flow (OPF). OPF is an efficient generator scheduling method to meet energy demands with the aim of minimizing the total production cost of power plants while maintaining system stability, security, and reliability. This paper proposes a new method to solve OPF by using incremental particle swarm optimization (IPSO). IPSO is a new algorithm of particle swarm optimization (PSO) that modifies the PSO structure by increasing the particle size, where each particle changes its position to determine its optimal position. The advantage of IPSO is that the population increases with each iteration so that the optimization process becomes faster. The results of the researc... [more]