This paper presents the research of optimization of road lighting energy consumption by utilizing the fact of human twilight and night vision (mesopic vision) dependency on luminance level and lamp’s light spectral composition. The research was conducted for a suburban street illuminated by smart LED road luminaires with a luminous flux control system with which different luminance levels can be achieved on the road. This road is an access road leading to a town located on the outskirts of Warsaw which is the capital of Poland and a large metropolitan area. Therefore, the traffic here is quite heavy on this road in the morning and in the evening and it is very light at other times of the day. In accordance with EN 13201 standard, lighting control can be applied to illuminate this road. This paper compares energy consumption for different lighting scenarios of the road in question. In the first scenario, the road luminance is compliant with M4, M5, and M6 lighting class requirements dep... [more]

Crosswind has an adverse impact on the performance of an indirect dry cooling system. In order to mitigate the adverse influence, this study redistributed the circulating cooling water among air-cooled heat exchanger sectors so that the performance of the indirect dry cooling system could be improved. An evolution strategies algorithm combined with numerical effectiveness-based heat exchanger model was established to minimize the operation costs of the whole system. Based on a 660 MW practical power plant, optimal circulating cooling water operation strategies under varied crosswind speeds and ambient temperatures were calculated to show its application. According to the calculated results, the performance of the indirect dry cooling system could be enhanced by optimizing circulating cooling water distribution under any crosswind speed, especially under high ambient wind speeds. There is a slight promotion of the coal savings with a rise in ambient temperature: improvements of about 5%... [more]

The recent revolution in electric mobility is both crucial and promising in the coordinated effort to reduce global emissions and tackle climate change. However, mass electrification brings up new technical problems that need to be solved. The increasing penetration rates of electric vehicles will add an unprecedented energy load to existing power grids. The stability and the quality of power systems, especially on a local distribution level, will be compromised by multiple vehicles that are simultaneously connected to the grid. In this paper, the authors propose a choice-based pricing algorithm to indirectly control the charging and V2G activities of electric vehicles in non-residential facilities. Two metaheuristic approaches were applied to solve the optimization problem, and a comparative analysis was performed to evaluate their performance. The proposed algorithm would result in a significant revenue increase for the parking operator, and at the same time, it could alleviate the o... [more]

The Chinese government has launched a guideline for carbon emissions up to the peak (CEUP) in the 2030 target. The electric power sector has to make its own contributions to the national CO2 emissions mitigation target. In this study, a patron−client interactive optimized (PCIO) model is proposed to investigate the regional energy−water−carbon nexus optimization under the policy background of the CEUP target. Inner Mongolia, the largest energy base in China, which is also facing the prominent contradiction including the energy production and serious environmental problems, is chosen as a case study. Multiple uncertainties, including the fuel price uncertainty and output of the wind and solar power, are considered to make the optimization process more realistic. Results show that coal-fired power will gradually be substituted by the gas, wind, and solar power in Inner Mongolia to reach the CEUP target. The CO2 capture and storage technology and air-cooling systems will play important ro... [more]

Distributed energy resources (DERs), including renewable energy resources (RESs) and electric vehicles (EVs), have a significant impact on distribution systems because they can cause bi-directional power flow in the distribution lines. Thus, the voltage regulation and thermal limits of the distribution system to mitigate from the excessive power generation or consumption should be considered. The focus of this study is on a control strategy for DERs in low-voltage DC microgrids to minimize the operating costs and maintain the distribution voltage within the normal range based on intelligent scheduling of the charging and discharging of EVs, and to take advantage of RESs such as photovoltaic (PV) plants. By considering the time-of-use electricity rates, we also propose a 24-h sliding window to mitigate uncertainties in loads and PV plants in which the output is time-varied and the EV arrival cannot be predicted. After obtaining a request from the EV owner, the proposed optimal DER contr... [more]

Offshore wind is considered a crucial part in the future energy supply. However, influenced by weather conditions, the maintenance of offshore wind turbine system (OWTs) equipment is challenged by poor accessibility and serious failure consequences. It is necessary to study the optimized strategy of comprehensive maintenance for offshore wind farms, with consideration of the influences of incomplete equipment maintenance, weather accessibility and economic relevance. In this paper, a Monte Carlo algorithm-improved factor is presented to simulate the imperfect preventive maintenance activity, and waiting windows were created to study the accessibility of weather conditions. Based on a rolling horizon approach, an opportunity group maintenance model of an offshore wind farm was proposed. The maintenance correlations between systems and between equipment as well as breakdown losses, maintenance uncertainty, and weather conditions were taken into account in the model, thus realizing coordi... [more]

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]