This research proposed an optimal control approach for a smart grid electrical system with photovoltaic generation, where the control variables are voltage and frequency, which aims to improve the performance through addressing the need for a balance between the minimization of error and the operational cost. The proposed control scheme incorporates the latest advancements in heuristics and hierarchical control strategies to provide an efficient and effective solution for the smart grid electrical system control. Implementing the optimal control scheme in a smart power grid is expected to bring significant benefits, such as the reduced impact of renewable energy sources, improved stability, reliability and efficiency of the power grid, and enhanced overall performance. The optimal coefficient values are found by minimizing the cost functions, which leads to a more efficient system performance. The voltage output response of the system in a steady state is over-damped, with no overshoot... [more]

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.

Biodiesel as a fuel has been shown to positively impact the environment; replacing or reducing the dependence on fossil fuels while providing a viable alternative. The use of waste oils, such as non-edible or used oils, can reduce competition with food, loss of resources, and the resulting higher prices. In this study, biodiesel was obtained by a transesterification reaction using used cooking oil from fast-food restaurants as the feedstock and catalysts from waste glass and animal bones as the silica and calcium oxide sources, respectively. Utilizing waste or non-edible oils for the production of biodiesel can lessen the competition with food sources while achieving environmental and ethical biofuel standards. Additionally, employing readily available waste oils and catalysts prepared from waste material is an economical and low-cost process compared to the use of conventional expensive feedstock and catalyst. The catalyst characterization for the prepared CaO−SiO2 catalyst was perfor... [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]

The study presents an optimal control approach for managing a hybrid Photovoltaic/Wind Turbine/Battery system in an isolated area. The system includes multiple energy sources connected to a DC bus through DC/DC converters for maximum power point tracking. The proposed hybrid MPPT approach (HMPPT) manages the energy production from different sources, while the power flow method is used to balance the load and renewable power. The study shows that integrating the HMPPT algorithm and power flow approach results in improved system performance, including increased power generation and reduced stress on the batteries. The study also proposes an accurate sizing method to further improve system efficiency. The study demonstrates the effectiveness of the proposed approach by presenting results for twelve different days with varying weather conditions. The results show that the proposed approach effectively manages the energy production and load, resulting in optimal system performance. This stu... [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]

Particle swarm optimisation (PSO) is one of the widely adopted meta-heuristic methods for solving real-life problems. Its practical utility can be further enhanced by improving its performance. In order to acheive this, academics have presented several variants of the original PSO over the past few years, including the quantum PSO (QPSO), bare-bones PSO (BB-PSO), hybrid PSO, fuzzy PSO, etc. In this paper, the performance of PSO is improved by proposing a fragmented swarm optimisation approach known as the PSO. The PSO is tested and compared with PSOs over 14 different benchmarking cost functions to validate its efficacy. The analysis is also carried out to see the impact of α on its performance. It is observed that the average value of the cost function over 50 simulations obtained using the fragmented swarm approach is lower than that obtained using the standard PSO in 12 out of 14 benchmark functions. Similarly, the fragmented approach outperforms the standard PSO in 13 out of 14 ben... [more]

The use of biobased heterogeneous catalysts made from agricultural waste for producing biodiesel has gained attention for its potential to create a sustainable and low-cost process. The blending of two or more biomass residues to create more viable biobased catalysts is still in its early stages. In this study, a Biobased Composite Heterogeneous Catalyst (CHC) was made by blending the shells of periwinkle (PWS), melon seed-husk (MSH), and locust bean pod-husk (LBP) at a mixing ratio of 67:17:17 using Simplex Lattice Design Mixture, that was then calcined for 4 h at 800 °C. The chemical, structural, and morphological components of the CHC were characterized via XRF, XRD, SEM-EDX, BET, TGA/DSC, and FTIR to assess its catalytic potential. The CHC was employed to synthesize biodiesel from palm kernel oil, and the process optimization was conducted using the Taguchi approach. The XRF analysis showed that the catalyst had 69.049 of Calcium (Ca) and 9.472 of potassium (K) in their elemental a... [more]

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]

With the gradual depletion of fossil energy sources and the improvement in environmental protection attention, efficient use of energy and reduction in carbon emissions have become urgent issues. The integrated electricity and heating energy system (IEHS) is a significant solution to reduce the proportion of fossil fuel and carbon emissions. In this paper, a stochastic optimization model of the IEHS considering the uncertainty of wind power (WP) output and carbon capture power plants (CCPs) is proposed. The WP output in the IEHS is represented by stochastic scenarios, and the scenarios are reduced by fast scenario reduction to obtain typical scenarios. Then, the conventional thermal power plants are modified with CCPs, and the CCPs are equipped with flue gas bypass systems and solution storage to form the integrated and flexible operation mode of CCPs. Furthermore, based on the different load demand responses (DRs) in the IEHS, the optimization model of the IEHS with a CCP is construct... [more]

The paper presents the methodology that should be used to optimize hybrid power system configurations, i.e., the chosen microgrid scenario. The methodology was developed with the aim of evaluating the different production capacities of a system and comparing them with alternative connections to the main grid. It has a step-by-step structure and includes part of the steps performed by simulations in a computer program. It provides us with not only a basic but also a representative idea of an actual microgrid configuration, which is further used as support in the system’s design. An algorithm has been developed to check the energy flows and correct the selling price. The program HOMER Pro is used as the program support in performing the hybrid optimization simulation. In the analysis, it was found that the maximum share of generation from renewable energy sources in relation to the power grid is 143%, while the share of renewable energy sources in the generated energy is 65.3%. Greenhous... [more]

The influence of the improvement of the finned tube radiator unit structure on the fluid flow and heat transfer effect of the locomotive was studied. A saw-toothed fin structure with aluminum instead of copper was proposed to keep the position and size of the flat copper hot water pipe unchanged. CFD simulation analysis was carried out by ICEPAK17.0, under the conditions of an ambient temperature of 24.6 °C, atmospheric pressure of 85,040 Pa and air density ρ = 0.94 kg/m3, to compare the changes of velocity field, temperature field, turbulence field and field synergy angle. The sawtooth structure of the new heat sink increases the turbulence effect of the fluid, reduces the thickness of the outer boundary layer of the water pipe, and strengthens the heat transfer effect of the radiator. Finally, the baffle height, wing window width and sawtooth angle of the sawtooth structure were selected, and the heat transfer coefficient and pressure under three conditions of low, medium and high we... [more]

To achieve the ambitious targets of net-zero greenhouse gas emissions by 2050, there is a need for change in all parts of society, industry, and mobility, as well as in all energy sectors. For this purpose, sector coupling plays a crucial role, e.g., in the form of coupling the electricity with the heat sector using power-to-heat systems. In this article, the effects of the integration of intermittent wind energy via a direct cable, as well as the integration of a boiler into district heating systems powered by a biomass plant and/or a gas boiler, are investigated. Sector coupling in the district heating networks is achieved via the integration of a boiler connected to a local grid station and the use of two air-to-water and two water-to-water heat pumps, which are solely powered by electricity produced by local wind turbines. Furthermore, this work evaluates the economic impacts of the exploding energy prices on the sustainability of district heating systems. Our analysis shows that d... [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]

The reactive power control mechanisms at the smart inverters will affect the voltage profile, active power losses and the cost of reactive power procurement in a different way. Therefore, this paper presents an assessment of the cost−benefit relationship obtained by enabling nine different reactive power control mechanisms at the smart inverters. The first eight reactive power control mechanisms are available in the literature and include the IEEE 1547−2018 standard requirements. The ninth control mechanism is an optimum reactive power control proposed in this paper. It is formulated to minimise the active power losses of the network and ensure the bus voltages and the reactive power of the smart inverter are within their allowable limits. The Vestfold and Telemark distribution network was implemented in DIgSILENT PowerFactory and used to evaluate the reactive power control mechanisms. The reactive power prices were taken from the default payment rate document of the National Grid. Sim... [more]

Energy systems are undergoing a profound transition worldwide, substituting nuclear and thermal power with intermittent renewable energy sources (RES), creating discrepancies between the production and consumption of electricity and increasing their dependence on greenhouse gas (GHG) intensive imports from neighboring energy systems. In this study, we analyze the concurrent electrification of the mobility sector and investigate the impact of electric vehicles (EVs) on energy systems with a large share of renewable energy sources. In particular, we build an optimization framework to assess how Evs could compete and interplay with other energy storage technologies to minimize GHG-intensive electricity imports, leveraging the installed Swiss reservoir and pumped hydropower plants (PHS) as examples. Controlling bidirectional EVs or reservoirs shows potential to decrease imported emissions by 33−40%, and 60% can be reached if they are controlled simultaneously and with the support of PHS fa... [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]

Optimization methods are increasingly used for the design process of electrical machines. The quality of the optimization result and the necessary simulation effort depend on the optimization methods, machine models and optimization parameters used. This paper presents a multi-stage optimization environment for the design optimization of induction machines. It uses the strategies of simulated annealing, evolution strategy and pattern search. Artificial neural networks are used to reduce the solution effort of the optimization. The selection of the electromagnetic machine model is made in each optimization stage using a methodical model selection approach. The selection of the optimization parameters is realized by a methodical parameter selection approach. The optimization environment is applied on the basis of an optimization for the design of an electric traction machine using the example of an induction machine and its suitability for the design of a machine is verified by a compari... [more]

Given the large amount of energy required in the building sector, an interesting opportunity to reach future sustainable energy systems is the path towards low energy buildings. This work proposes an approach for optimally integrating building-scale energy technologies (both traditional and renewable) to enhance the transformation of the existing buildings (often energetically inefficient) in low-carbon systems. The approach promotes a transition sustainable from both the economic and environmental perspectives. Both operation and design optimization are considered with the aim of suggesting the best set of capacity of the technologies to be installed taking into account the expected operations. The building-scale technologies are integrated with proper storage units: Li-ion batteries and thermal storage (latent heat, that requires low installation space). As a dispatchable renewable technology, a biogas small-scale combined heat and power unit is included in the system. Once the key r... [more]

Transmission system operators impose several grid-code constraints on large-scale wind farms to ensure power system stability. These constraints may reduce the net profit of the wind farm operators due to their inability to sell all the power. The violation of these constraints also results in an imposition of penalties on the wind farm operators. Therefore, an operation strategy is developed in this study for optimizing the operation of wind farms using an energy storage system. This facilitates wind farms in fulfilling all the grid-code constraints imposed by the transmission system operators. Specifically, the limited power constraint and the reserve power constraint are considered in this study. In addition, an optimization algorithm is developed for optimal sizing of the energy storage system, which reduces the total operation and investment costs of wind farms. All parameters affecting the size of the energy storage systems are also analyzed in detail. This analysis allows the wi... [more]

Electric vehicles’ (EVs) technology is currently emerging as an alternative of traditional Internal Combustion Engine (ICE) vehicles. EVs have been treated as an efficient way for decreasing the production of harmful greenhouse gasses and saving the depleting natural oil reserve. The modern power system tends to be more sustainable with the support of electric vehicles (EVs). However, there have been serious concerns about the network’s safe and reliable operation due to the increasing penetration of EVs into the electric grid. Random or uncoordinated charging activities cause performance degradations and overloading of the network asset. This paper proposes an Optimal Charging Starting Time (OCST)-based coordinated charging algorithm for unplanned EVs’ arrival in a low voltage residential distribution network to minimize the network power losses. A time-of-use (ToU) tariff scheme is used to make the charging course more cost effective. The concept of OCST takes the departure time of E... [more]

Nowadays, many organizations and individual users are employing cloud services extensively due to their efficiency, reliability and low cost. A key aspect for cloud data centers is to achieve management methods to reduce energy consumption, increasing the profit and reducing the environmental impact, which is critical in the deployment of leading-edge technologies today such as blockchain and digital finances, IoT, online gaming and video streaming. In this review, various clustering, optimization, and machine learning methods used in cloud resource allocation to increase the energy efficiency and performance are analyzed, compared and classified. Specifically, on the one hand, we discuss how clustering methods and optimization techniques are widely applied in energy management due to their capacity to provide solutions for energy consumption reduction. On the other hand, we study how multi-objective optimization methods focus on reducing energy consumption as well as service level agr... [more]

Sustainable Development Goals were established by the United Nations General Assembly to ensure that everyone has access to clean, affordable, and sustainable energy. Third-generation biodiesel derived from algae sources can be a feasible option in tackling climate change caused by fossil fuels as it has no impact on the human food supply chain. In this paper, the combustion and emission characteristics of Azolla Pinnata oil biodiesel-diesel blends are investigated. The multi-objective response surface methodology (MORSM) with Box−Behnken design is employed to decrease the number of trials to conserve finite resources in terms of human labor, time, and cost. MORSM was used in this study to investigate the interaction, model prediction, and optimization of the operating parameters of algae biodiesel-powered diesel engines to obtain the best performance with the least emission. For engine output prediction, a prognostic model is developed. Engine operating parameters are optimized using... [more]

This study focuses on the sizing and optimization of a micro-grid with storage, which is destined to supply the load of an economic activity zone (EAZ) in Sidi Bouzid, Tunisia. To solve this problem, a genetic algorithm is established and programmed into MATLAB. The objective functions are considered by providing three minimums, namely Greenhouse Gas emissions (GHG), Life Cycle Cost (LCC) and Embodied Energy (EE), for three values of loss of power supply probability (LPSP) previously fixed. The sizing and optimization results are found and evaluated using a time series exchange of energy during a year to determine the optimal component size of a photovoltaic/wind/battery system (PV/WT/Bat). The simulation results show that the lowest ratio of LPSP values corresponds to the higher GHG, EE, LCC, photovoltaic panels area (APV), battery storage capacity (Cn), wind turbines area (AWT) and vice versa. This means that demanding higher energy reliability leads to higher energy cost and polluti... [more]