The problem of partial shading has serious effects on the performance of photovoltaic (PV) systems. Adding a bypass diode in shunt to each PV module avoids hot-spot phenomena, but causes multi-peaks in the power−voltage (P−V) characteristics of the PV array, which cause traditional maximum power point tracking (MPPT) techniques to become trapped in local peaks. This problem has forced researchers to search for smart techniques to track global peaks and prevent the possibility of convergence at local peaks. Swarm optimization techniques have been used to fill this shortcoming; unfortunately, however, these techniques suffer from unacceptably long convergence time. Cuckoo search (CS) is one of the fastest and most reliable optimization techniques, making it an ideal option to be used as an MPPT of PV systems under dynamic partial shading conditions. The standard CS algorithm has a long conversion time, high failure rate, and high oscillations at steady state; this paper aims to overcome... [more]

In this paper, the motion of the n-vortex system as it collapses to a point in finite time is studied. The motion of vortices is described by the set of ordinary differential equations that we are able to solve analytically. The explicit formula for the solution demands the initial location of collapsing vortices. To find the collapsing locations of vortices, the algebraic, nonlinear system of equations was built. The solution of that algebraic system was obtained using Newton’s procedure. A good initial iterate needs to be provided to succeed in the application of Newton’s procedure. An unconstrained Leverber−Marquart optimization procedure was used to find such a good initial iterate. The numerical studies were conducted, and numerical evidence was presented that if in a collapsing system n=50 point vortices include a few vortices with much greater intensities than the others in the set, the vortices with weaker intensities organize themselves onto the vortex sheet. The collapsing lo... [more]

To ensure broad application of renewable and energy-efficient energy systems in buildings and neighborhoods, profitable business models are vital. Energy supply contracting helps building residents to overcome the barrier of high upfront investment costs while additionally reducing risks related to energy-saving mechanisms. This study examines profitability for energy contractors in a variety of business cases that simultaneously ensure energy cost savings for the residents. A mixed-integer linear optimization model is developed for a neighborhood energy community, consisting of three buildings with diverse usages. In the process, the optimum capacities of building-attached and building-integrated photovoltaics, a heat pump and a gas-fired mini combined heat and power unit are determined to cover the energy community’s electricity and heat load. Results show that cross-domain contracting within energy communities is highly profitable for both, the contractor and the residents, while th... [more]

In recent years, the development of hybrid powertrain allowed to substantially reduce the CO2 and pollutant emissions of vehicles. The optimal management of such power units represents a challenging task since more degrees of freedom are available compared to a conventional pure-thermal engine powertrain. The a priori knowledge of the driving mission allows identifying the actual optimal control strategy at the expense of a quite relevant computational effort. This is realized by the off-line optimization strategies, such as Pontryagin minimum principle—PMP—or dynamic programming. On the other hand, for an on-vehicle application, the driving mission is unknown, and a certain performance degradation must be expected, depending on the degree of simplification and the computational burden of the adopted control strategy. This work is focused on the development of a simplified control strategy, labeled as efficient thermal electric skipping strategy—ETESS, which presents performance simila... [more]

Energy power flows are an important factor to be calculated and, thus, are needed to be enhanced in an electrical generation system. It is very necessary to optimally locate the Flexible Alternating Current Transmission Systems (FACTS) devices and improve the Available Transfer Capability (ATC) of the power transmission lines. It relieves the congestion of the system and increases the flow of power. This research study has been accomplished in two stages: optimization of location of FACTS device by the novel Sensitivity and Power loss-based Congestion Reduction (SPCR) method and the calculation of ATC using the proposed Metaheuristic Evolutionary Particle Swarm Optimization (MEEPSO) technique. The Thyristor Controlled Series Capacitor (TCSC) is used as a FACTS device to control the reactance of power transmission line. The effectiveness of the proposed methods is validated, utilizing the six bus as well as 30 bus system. The acquired outcomes are contrasted with conventional ACPTDF and... [more]

Due to the large number of grid connection of distributed power supply, the existing scheduling methods can not meet the demand gradually. The proposed virtual power plant provides a new idea to solve this problem. The photovoltaic power prediction provides the data basis for the scheduling of the virtual power plant. Prediction intervals of photovoltaic power is a powerful statistical tool used for quantifying the uncertainty of photovoltaic power generation in power systems. To improve the interval prediction accuracy during the non-stationary periods of photovoltaic power, this paper proposes a probabilistic ensemble prediction model, which combines the modules of data preprocessing, non-stationary period discrimination, feature extraction, deterministic prediction, uncertainty prediction, and optimization integration into a general framework. More specifically, in the non-stationary period discrimination module, the method of discriminating the difference of the power ratio differe... [more]

Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques.

The need of clean energy is constantly increasing, and Building Integrated PhotoVoltaic (BIPV) technologies represent valuable assets to expand even further the photovoltaic market. Thanks to BIPVs. a new concept of local electric microgrid will probably emerge as this kind of technology can turn buildings from energy wells to energy sources. Luminescent Solar Concentrator (LSC) panels are perfect to achieve this goal, indeed, contrary to standard flat PhotoVoltaic (PV) modules, they can be exploited in transparent or semi-transparent building façades. Thus, the purpose of this work was the optimization of the performance of LSC panels for BIPV applications. Being an application-oriented study, we paid particular attention to the scalability of the assembling process and the use of LSC slabs functionalized only with widely available organic commercial dyes and high-performance commercial silicon solar cells. The electrical and optical performance of the LSC panels were firstly simulate... [more]

During the day, photovoltaic (PV) systems are exposed to different sunlight conditions in addition to partial shading (PS). Accordingly, maximum power point tracking (MPPT) techniques have become essential for PV systems to secure harvesting the maximum possible power from the PV modules. In this paper, optimized control is performed through the application of relatively newly developed optimization algorithms to PV systems under Partial Shading (PS) conditions. The initial value of the duty cycle of the boost converter is optimized for maximizing the amount of power extracted from the PV arrays. The emperor penguin optimizer (EPO) is proposed not only to optimize the initial setting of duty cycle but to tune the gains of controllers used for the boost converter and the grid-connected inverter of the PV system. In addition, the performance of the proposed system based on the EPO algorithm is compared with another newly developed optimization technique based on the cuttlefish algorithm... [more]

Green hydrogen for mobility represents an alternative to conventional fuel to decarbonize the transportation sector. Nevertheless, the thermodynamic properties make the transport and the storage of this energy carrier at standard conditions inefficient. Therefore, this study deploys a georeferenced optimal transport infrastructure for four base case scenarios in France and Germany that differs by production distribution based on wind power potential and demand capacities for the mobility sector at different penetration shares for 2030 and 2050. The restrained transport network to the road infrastructure allows focusing on the optimum combination of trucks operating at different states of aggregations and storage technologies and its impact on the annual cost and hydrogen flow using linear programming. Furthermore, four other scenarios with production cost investigate the impact of upstream supply chain cost, and eight scenarios with daily transport and storage optimization analyse the... [more]

The power distribution strategy of hybrid power sources is an important issue for fuel cell vehicles. A good power distribution control strategy can realize the optimal control of the vehicle energy, which can save energy and improve the operating conditions of the power source. Therefore, this article proposes a power distribution strategy. First, in order to solve the problems existing in the existing fuel cell model and the lithium-ion battery model, an improved hybrid power system model with better dynamic performance was established in the Simulink. Second, in order to ensure the durability of the power system, operation constraints are added to the distribution strategy. Finally, the power allocation is regarded as a nonlinear programming optimization problem and solved by a nonlinear programming algorithm. The nonlinear programming algorithm selects the BFGS algorithm. The simulation results of other control strategies in MATLAB show that the proposed power distribution strategy... [more]

The method for preliminary powertrain design is presented in the paper. Performance of the EV is realized by motor torque−speed curve and gear ratio optimization. The typical two-zone mechanical characteristic of a PMSM traction motor is included in the optimization program. The longitudinal vehicle model is considered in the paper. Some examples try to show the calculation possibilities in application to existing vehicles: Tesla Model S and Mini Cooper SE.

Wind power has significant randomness. Probabilistic prediction of wind power is necessary to solve the problem of safe and stable power grid dispatching with the integration of large-scale wind power. Therefore, this paper proposes a novel nonparametric probabilistic prediction model for wind power based on extreme learning machine-quantile regression (ELM-QR). Firstly, the ELM-QR models of multiple quantiles are established, and then the new comprehensive index (NCI) is optimized by particle swarm optimization (PSO) to obtain the weighting coefficients corresponding to the lower and upper bounds of the prediction intervals. The final prediction interval is obtained by integrating the outputs of ELM-QR models and the weighting coefficients. Finally, case studies are carried out with the real wind farm operation data, simulation results show that the proposed algorithm can obtain narrower prediction intervals while ensuring high reliability. Through sensitivity analysis and comparison... [more]

Offshore wind energy, as one of the featured rich renewable energy sources, is getting more and more attention. The cable connection layout has a significant impact on the economic performance of offshore wind farms. To make better use of the wind resources of a given sea area, a new method for optimal construction of offshore wind farms with different types of wind turbines has emerged in recent years. In such a wind farm, the capacities of wind turbines are not identical which brings new challenges for the cable connection layout optimization. In this work, an optimization model named CCLOP is proposed for such wind farms. The model incorporates both the cable capital cost and the cost of power losses associated with the cables in its objective function. To get an optimized result, a Voronoi diagram based adaptive particle swarm optimization with local search is proposed and applied. The simulation results show that the proposed method can help find a solution that is 12.74% outperfo... [more]

As carriers of green energy, proton exchange membrane fuel cells (PEMFCs) and photovoltaic (PV) cells are complex and nonlinear multivariate systems. For simulation analysis, optimization control, efficacy prediction, and fault diagnosis, it is crucial to rapidly and accurately establish reliability modules and extract parameters from the system modules. This study employed three types of particle swarm optimization (PSO) algorithms to find the optimal parameters of two energy models by minimizing the sum squared errors (SSE) and roots mean squared errors (RMSE). The three algorithms are inertia weight PSO, constriction PSO, and momentum PSO. The obtained calculation results of these three algorithms were compared with those obtained using algorithms from other relevant studies. This study revealed that the use of momentum PSO enables rapid convergence (under 30 convergence times) and the most accurate modeling and yields the most stable parameter extraction (SSE of PEMFC is 2.0656, RM... [more]

Owing to the increases of energy loads and penetration of renewable energy with variability, it is essential to determine the optimum capacity of the battery energy storage system (BESS) and demand response (DR) within the microgrid (MG). To accomplish the foregoing, this paper proposes an optimal MG operation approach with a hybrid method considering the game theory for a multi-agent system. The hybrid method operation includes both BESS and DR methods. The former is presented to reduce the sum of the MG operation and BESS costs using the game theory, resulting in the optimal capacity of BESS. Similarly, the DR method determines the optimal DR capacity based on the trade-off between the incentive value and capacity. To improve optimization operation, multi-agent guiding particle swarm optimization (MAG-PSO) is implemented by adjusting the best global position and position vector. The results demonstrate that the proposed approach not only affords the most economical decision among age... [more]

The increasing necessity of challenging wellbore structures and drilling optimization for improved hole cuttings cleaning has been growing along time. As a result, operator companies have been researching and applying different hole cleaning techniques. Some of these are applied as traditional rules of thumb but are not always suitable for the new and up-coming challenges. This may result in inefficient hole cleaning, non-productive times, pipe stocking and low rate of penetration (ROP), among other problems. Here are presented some results and improvements for hole cleaning optimization obtained by the different research groups. The different authors mainly focus on specific cuttings transport parameters and sometimes combination of some of them. For this reason, there has not been a study that takes into account all of the different factors at the same time to accurately predict the cuttings bed height, formation and erosion, critical fluid velocity and properties and other key param... [more]

The article deals with the optimization of the azimuthal tracking mechanism for a photovoltaic (PV) platform, which uses linear actuators as actuation elements for both movements (diurnal and elevation). In the case of diurnal movement, where the platform’s angular field of orientation is large, a mechanism with a relatively simple structure is used for amplifying the actuator’s stroke and avoiding the risk of the system locking itself (by limiting the values of the transmission angle). The optimization study targets the mechanical device, the control device, and the bi-axial tracking program (embodied by the laws of motion in time for the platform’s diurnal and elevation angles) with the purpose of obtaining a high input of solar radiation, with a minimal energy consumption to achieve tracking. The study is carried out by using a virtual prototyping platform, which includes Computer Aided Design (CAD), Multi-Body Systems (MBS), and Design for Control (DFC) computer applications. The m... [more]

Power imbalances such as power shortfalls and photovoltaic (PV) curtailments have become a major problem in conventional power systems due to the introduction of renewable energy sources. There can be large power shortfalls and PV curtailments because of PV forecasting errors. These imbalances might increase when installed PV capacity increases. This study proposes a new scheduling method to reduce power shortfalls and PV curtailments in a PV integrated large power system with a battery energy storage system (BESS). The model of the Kanto area, which is about 30% of Japan’s power usage with 60 GW grid capacity, is used in simulations. The effect of large PV power integration of 50 GW and 100 GW together with large BESS capacity of 100 GWh and 200 GWh has been studied. Mixed integer linear programming technique is used to calculate generator unit commitment and BESS charging and discharging schedules. The simulation results are shown for two months with high and low solar irradiance, wh... [more]

Due to the high complexity of detailed sector-coupling models, a perfect foresight optimization approach reaches complexity levels that either requires a reduction of covered time-steps or very long run-times. To mitigate these issues, a myopic approach with limited foresight can be used. This paper examines the influence of the foresight horizon on local energy systems using the model DISTRICT. DISTRICT is characterized by its intersectoral approach to a regionally bound energy system with a connection to the superior electricity grid level. It is shown that with the advantage of a significantly reduced run-time, a limited foresight yields fairly similar results when the input parameters show a stable development. With unexpected, shock-like events, limited foresight shows more realistic results since it cannot foresee the sudden parameter changes. In general, the limited foresight approach tends to invest into generation technologies with low variable cost and avoids investing into d... [more]

The Hyperloop is a concept for the high-speed ground transportation of passengers traveling in pods at transonic speeds in a partially evacuated tube. It consists of a low-pressure tube with capsules traveling at both low and high speeds throughout the length of the tube. When a high-speed system travels through a low-pressure tube with a constrained diameter such as in the case of the Hyperloop, it becomes an aerodynamically challenging problem. Airflow tends to get choked at the constrained areas around the pod, creating a high-pressure region at the front of the pod, a phenomenon referred to as the “piston effect.” Papers exploring potential solutions for the piston effect are scarce. In this study, using the Reynolds-Average Navier−Stokes (RANS) technique for three-dimensional computational analysis, the aerodynamic performance of a Hyperloop pod inside a vacuum tube is studied. Further, aerofoil-shaped fins are added to the aeroshell as a potential way to mitigate the piston effec... [more]

Vibration and noise reduction are very important in electric vehicle driving motors. In this study, topology optimization of housing was performed to reduce vibration in a specific frequency caused by electromagnetic force generated by a permanent magnet synchronous motor (PMSM). The vibration induced by the electromagnetic force of the motor was calculated using electromagnetic-structural coupled analysis. Then, the magnitude of the acceleration for a specific frequency at which peak occurs in the rectangular and circular shape housing concept design model was reduced by using the topology optimization method. As a result, the rectangular and circular shape housing design reduced 92.9% and 96.0%, respectively. Finally, the vibration was effectively reduced while maintaining the electromagnetic characteristics of the motor, for which topology optimization was conducted while not changing the rotor or stator shape design (electromagnetic design factor) but by changing the motor housing... [more]

The power requirements of grids have risen as artificial intelligence and electric vehicle technologies have been used. Thus, the installation of distributed generators (DGs) has become an essential factor to streamline power grids. The objective of this study is to optimize the capacity and location of DGs. For this purpose, an objective function was defined, which takes into account the fault current and the levelized cost of energy, and a modified particle swarm optimization method was applied. Then, we analyzed a case of a single line-to-ground fault with a test feeder (i.e., the IEEE 30 bus system) with no DGs connected, as well as a case where the DGs are optimally connected. The effect of the optimally allocated DGs on the system was analyzed. We discuss an optimal layout method that takes the economic efficiency of the DG installation into account.

Research on energy storage systems (ESS) is actively aiming to mitigate against the unreliability of renewable energy sources (RES), and ESS operation and management has become one of the most important research topics. Since installing ESS for each user requires high investment cost, a study on cloud ESS gains attention recently. Cloud ESS refers to an ESS that is logically shared by multiple users as if they have their own ESS in their premises. In this paper, we propose a new cloud ESS sharing technique that allows capacity P2P transactions among users. Since cloud ESS is a virtual facility that is linked to an actual ESS, it is easy for users to sell the unused storage capacity to other users or to buy additional capacity from other users during operation. We also propose a system that encourages users to completely entrust the cloud ESS operator and share the extra benefit with the operator and other users. To verify the proposed method, we demonstrate the benefit of capacity P2P... [more]

The treatment of growing production of municipal sewage sludge has become a significant global problem. Drying of digested sewage sludge is a promising alternative to sludge disposal at dumping sites. The research objective of this study was to find the optimal heat source for a sludge drying plant in a large municipal sewage treatment plant (people equivalent: 250,000). Two boundary heat supply cases were analyzed in the paper: cogeneration of heat and power (CHP) units, internal combustion (IC) engines fired with natural gas, and plant supplied with a gas boiler. The aim of the research was to find the optimal size of the cogeneration unit cooperating with the gas boiler as heat sources for a given drying plant case with the maximum net present (NPV) value as the objective function. The results of the conducted optimization show higher profitability of cases with larger cogeneration unit. For the basic assumptions, the maximum NPV is obtained for the largest analyzed CHP unit: 1300 k... [more]