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With further penetration of low-carbon energy conversion, microgrids (MGs) have become a necessary tool for expanding the consumption of renewable energies. In this paper, an optimal operation model for a microgrid-based multi-agent system is proposed. The goal is to save the total energy cost, which is expressed as a sum of locally observable convex functions. Therefore, improving the operational efficiency of microgrids is the key to promoting renewable energy development. This paper develops a three-layer multi-agent system model considering energy storage system and power thermal load demand response to solve the energy management problem of microgrids. In order to investigate the effect of energy storage system and demand response in microgrids, this paper designs three simulation cases, namely infrastructure case, energy storage case and demand response case. In order to prove the effectiveness of the proposed method, this paper uses the proposed method to solve three cases and compare the result with other meta-heuristic algorithms. The comparison results show that: (1) the multi-agent system model can realize the joint optimization of "resource, network, load and storage". (2) The introduction of energy storage and demand response system in microgrids can stabilize the output. Renewable energy units promote the use of renewable energy and reduce the overall operating cost of microgrids. Moreover, the results clearly demonstrate that the proposed algorithm has far better performance than other optimization methods. Also, the analysis obtained from the results shows that the cost is reduced by 1.82%. PV and WT output increased by 14.54% and 2.42%. In addition, their standard deviation decreases after ESS participation. The proposed approach is very effective through a simulation case study, which shows high potential for applications. [ABSTRACT FROM AUTHOR]

This paper investigates conversion of a Nordic oil-heated townhouse into carbon-neutral by different energy efficiency (EE) improvements and an off-grid system including solar photovoltaics (PV), wind power, and battery and hydrogen energy storage systems (BESS and HESS). A heat-pump-based heating system including waste heat recovery (WHR) from the HESS and an off-grid electrical system are dimensioned for the building by applying models developed in MATLAB and Microsoft Excel to study the life cycle costs (LCC). The work uses a measured electrical load profile, and the heat generation of the new heating system and the power generation are simulated by commercial software. It is shown that the EE improvements and WHR from the HESS have a positive effect on the dimensioning of the off-grid system, and the LCC can be reduced by up to €2 million. With the EE improvements and WHR, the component dimensioning can be reduced by 22%–41% and 13%–51% on average, respectively. WHR can cover up to 57% of the building's annual heat demand, and full-power dimensioning of the heat pump is not reasonable when WHR is applied. Wind power was found to be very relevant in the Nordic conditions, reducing the LCC by 32%. [Display omitted] • Energy efficiency improvements notably reduce dimensioning of system components. • Waste heat from FC and electrolyzer covers up to 57% of the annual heat demand. • A full-power-dimensioned GSHP does not reduce the fuel cell dimensioning. • Seasonal storage on a small scale makes the system not economically viable. • Small-scale wind power is expensive, but it significantly reduces the system LCC. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze through simulation how the energy efficiency of a single electrolysis stack at various loads is affected by shunt currents and to determine the energy-optimal load distribution between lines in a multiline electrolysis system under various magnitudes of shunt current losses. A dynamic energy and mass balance model of an industrial 3 MW , 16 bar alkaline water electrolyzer (AWE) process was developed using MATLAB. The optimization goal is to determine the power supply for each AWE line so that it can meet any hydrogen demand while minimizing the global specific energy consumption (SEC). The Particle Swarm Optimization (PSO) algorithm is used to minimize the objective function. According to the results of the single stack investigation, shunt current reduction could significantly improve the energy efficiency of partial-load operation. In addition, the optimization study revealed that whenever two or more lines are required to run in order to satisfy the hydrogen demand, the global SEC is minimized when the lines operate at equal loads. [ABSTRACT FROM AUTHOR]

With the objective to reduce fossil fuels consumption and greenhouse gas emissions, the integration of solar thermal energy into energy-intensive processes represents the most effective solution. This paper investigates the best solar integration scenarios to an industrial dryer unit through an exergy analysis. The exergetic balance for each subsystem is conducted, and a sensitivity parametric analysis was carried out. The optimization using the Genetic Algorithm was then conducted to define the optimum solar operating conditions. The exergetic evaluation showed an important exergy destruction at the dryer and combustion chamber, accounting for 58% and 42% of the inlet exergy flow, respectively. The sensitivity analysis outcomes showed that the exergy efficiency is clearly increased by increasing both drying temperature, decreasing the inlet moisture content, with preheating the combustion air temperature. Considering these variables, the optimization problem enabled enhancing the exergy efficiency by 40% and 30% for the overall process and flash dryer, respectively, when increasing drying temperature to 850 °C, an inlet moisture content of 14.9% and a preheated air combustion of 150 °C. Finally, the solar field could be integrated to the industrial dryer to preheat the ambient air for the combustion chamber to the setpoint temperature of 150 °C. [ABSTRACT FROM AUTHOR]

The aim of this paper is to introduce a novel solar tracking alternative whose principle is based on continuous tests comparing the produced thermal energy corresponding to the new apparent sun position with the electrical energy consumption required to drive the solar collector to the new position. Accordingly, the sun-tracking occurs whenever the net energy gain, the gap between thermal production and electrical consumption, is higher than an optimal threshold which reflects the required limits from which the sun-tracking process should begin. The proposed approach was investigated through modeling and optimization. Furthermore, to check the accuracy of the theoretical model, a series of comparisons were also performed, which have shown a reasonable agreement between the simulation results and the available data in the literature. The findings have revealed that there is an optimal threshold to start the sun-tracking process depending on the sun-tracking mode, sky clearness and season. In terms of comparison with conventional sun-tracking systems, it has been proven that, even though the suggested sun-tracking approach enhances slightly the net energy during typical clear sunny days, the improvement of the net energy gain becomes more significant under partly cloudy conditions. • Investigation of a new sun-tracking approach based on net energy gain. • Dual-axis and polar sun-tracking modes are the most thermally efficient. • Current approach enhanced sun-tracking performance notably on partly cloudy days. • This approach exhibits its most usefulness when combined with N–S tracking mode. [ABSTRACT FROM AUTHOR]

With the development of fluid transmission and distribution network in the direction of intelligent pipe network, it is urgent to solve the power supply problem of many instruments in the pipe network. However, solving the problem of power supply for intelligent pipe network systems in remote areas and poor site conditions is a challenging task, and the power supply problem can be solved if the fluid energy in the pipe network can be harvested to power instruments such as sensors. Valve is essential equipment in pipe network system, and installing impeller in their spool can harvest fluid energy for power generation. In this paper, in order to improve the ability of the impeller to harvest fluid energy, the blade profile is optimized by parametrically defined method based on the Isight platform. The energy harvesting under different parameters is obtained through CFD simulation software, the Kriging model is established according to the sample data, and the NSGA-II algorithm is used to optimize. After optimization, the impeller shaft power is increased by 7.22%, the energy harvesting efficiency is increased by 7.50%, and the optimal blade profile is obtained. The ability of the impeller to harvest fluid energy is significantly improved. [ABSTRACT FROM AUTHOR]

Filling phase change material (PCM) in the glazed system is crucial to achieving thermal inertia enhancement and solar radiation regulation. However, most previous investigations focused on the energy performance of the PCM glazed system (PCMGS) in typical periods, and the optimization of PCMGS was mainly conducted by control variables to obtain the optimal value of a single parameter, which cannot accurately guide for the long-term application of PCMGS. In this paper, a global optimization program coupled with a numerical model of PCMGS and differential evolution algorithm (DEA) was developed. The annual energy performance of PCMGS was simulated as the objective function to obtain the optimal values of 11 parameters. Subsequently, the climatic applicability of PCMGS was demonstrated by comparing the annual energy performance with that of the traditional double-glazed system (TDGS). The results indicate that the objective function value converges to optimal after 2000 iterations. PCMGS performs preeminent adaptability in hot regions, followed by intermediate regions. The energy consumption of the building when PCMGS is used is reduced by 13.80% and 1.58% respectively compared to the TDGS. However, in cold regions, PCMGS reveals deplorable adaptability, as the energy consumption increased by 36.58% compared to the TDGS. [ABSTRACT FROM AUTHOR]

Renewable energy is the cornerstone of our future energy needs. In particular, solar energy is being utilized at a faster pace than ever. Floating Solar Photovoltaics (FSPV) has recently gained traction as a suitable alternative of land-based large scale PV installation. It is a promising technology to utilize water surfaces for placing solar plants. Not only it utilizes the water as real estate but it has several other advantages as well. For example, FSPV can use the existing transmission and distribution infrastructure that is the part of hydroelectric power plants. In this paper, we evaluate an FSPV plant and its integration with the existing hydroelectric power station of a small reservoir in Pakistan. We have investigated the 500 kV, 132 kV and 11 kV voltage levels for the integration of FSPV plant. Moreover, we have devised a hydro-solar optimization model for the efficient utilization of energy. The combined system consisting of hydroelectric and 200 MWp FSPV produces more than 3.5% additional power overall when compared with production of only hydroelectric power. More importantly the FSPV generation coincides with the daily mid-day peak load thus works as a peaker plant for the national grid. • Combination of FSPV and Hydroelectric is utilized for peak load demand hours. • Reservoir area feasibility and elevation study for installation of FSPV on hydroelectric reservoir is carried out. • Evaluation of various grid integration options are carried out. • Optimization model is presented for FSPV and hydroelectric combination. [ABSTRACT FROM AUTHOR]

This paper introduces an optimization procedure of a modified Savonius rotor with different convex and concave sides to maximize the power efficiency. A series of transient computational fluid dynamics (CFD) simulations are performed to find the peak coefficients of power ( C p ) of each blade geometry. Then, a global response surface model is created according to the Kriging Method, which defines the relationship between optimization objective C p and the design parameters. A Particle Swarm Optimization (PSO) algorithm is applied to finding the optimal design based on the response surface model. The optimal C p is 0.2580 and is 4.41% higher than the traditional design. Comprehensive comparisons of torque, power and flow structures between the optimal and the traditional designs are performed to illustrate the mechanism of how the blade shapes improve the rotor performance. It is find found that the optimal blade shape has stronger tip vortices and recovery flows, which contributes to an increase in the performance of the rotor. [ABSTRACT FROM AUTHOR]

As one of the most important parts of the solar power tower plant, the receiver plays an important role in the high-efficiency operation of the solar power tower system. Obtaining the maximum available energy in the receiver is highly desired in real-world operations. In this paper heat transfer and exergy transfer methods are used to model the energy transfer process in a collector tube. Different from common analysis methods, in order to ensure the molten salt to obtain the maximum available energy, an objective function is proposed to convert the task into a constrained optimization problem. The gravitational search (GS) algorithm is employed to search for the optimal solution of the proposed objective function. Numerical results indicate that the proposed optimization method can find the optimal operation parameters under different conditions. The heat transfer and exergy transfer characteristics along the collector tube under the optimal working condition are revealed, which quantifies the available energy along the collector tube, as well as reveals the location of energy degradation in the tube. The research findings will provide a beneficial reference for the effective use of the solar energy. [ABSTRACT FROM AUTHOR]

Oscillating water column based wave energy extracting system has a low efficiency due to the poor performance of its principal power extracting component, the bidirectional turbine. In the present work, flow over a bidirectional impulse turbine was simulated using CFD technique and optimized using multiple surrogates approach. The surrogates being problem dependent may produce unreliable results, if a wrong surrogate is selected. Hence, multiple surrogates such as response surface approximation, radial basis function, Kriging and weighted average surrogates were incorporated in this problem. Same design points were used to generate multiple optima via multiple surrogates to enhance the robustness of the optimization process. Numbers of guide vanes and rotor blades were chosen as the design variables, and the objective was to maximize the blade efficiency. Reynolds-averaged Navier–Stokes equations were solved for analyzing the flow physics. The computed results were used to train the surrogates and find the optimal points via hybrid genetic algorithm. The surrogates were further applied to find the optimal flow parameters by changing flow velocity and turbine speed. The relative efficiency enhancement through our present approach was about 16%. Detailed methodologies, analysis of the results and surrogate applicability have been presented in this paper. [ABSTRACT FROM AUTHOR]

To address the increase of electricity demand, the need for reducing carbon dioxide, and the reduction of available fossil fuel resources, renewable energy sources are being recruited. Specifically energy generated by photovoltaic (PV) cells is becoming one of the most promising alternatives. In this context, this paper presents an optimization model for the scheduling problem where conventional and photovoltaic sources of energy are scheduled to be delivered to satisfy energy demand. The optimization model is formulated as a Linear Program (LP) with a bounded number of variables and constraints. The respective solution can be obtained in polynomial time and provides the optimal combination or schedule of energy generated from different sources (conventional, renewable and battery storage) such that the total demand is satisfied and the profit is maximized. Numerical results demonstrate the effectiveness and the generality of the scheme. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the optimization of a solar photovoltaic thermal (PV/T) water collector which is based on exergy concept is carried out. Considering energy balance for different components of PV/T collector, we can obtain analytical expressions for thermal parameters (i.e. solar cells temperature, outlet water temperature, useful absorbed heat rate, average water temperature, thermal efficiency, etc.). Thermal analysis of PV/T collector depends on electrical analysis of it; therefore, five-parameter current–voltage (I–V) model is used to obtain electrical parameters (i.e. open-circuit voltage, short-circuit current, voltage and current at the point which has maximum electrical power, electrical efficiency, etc.). In order to obtain exergy efficiency of PV/T collector we need exergy analysis as well as energy analysis. Considering exergy balance for different components of PV/T collector, we obtain the expressions which show the exergy of the different parts of PV/T collector. Some corrections have been done on the above expressions in order to obtain a modified equation for the exergy efficiency of PV/T water collector. A computer simulation program has been developed in order to obtain the amount of thermal and electrical parameters. The simulation results are in good agreement with the experimental data of previous literature. Genetic algorithm (GA) has been used to optimize the exergy efficiency of PV/T water collector. Optimum inlet water velocity and pipe diameter are 0.09 m s−1, 4.8 mm, respectively. Maximum exergy efficiency is 11.36%. Finally, some parametric studies have been done in order to find the effect of climatic parameters on exergy efficiency. [Copyright &y& Elsevier]

Abstract: This paper deals with the feasibility of RES-based systems for electricity supply in four different Greek Islands. Three specific typical loads were selected to be covered, where the grid connection was considered as optional. An optimization procedure in terms of energy efficiency and economical feasibility has also been applied, using the HOMER software for the energy part and a hand-made calculation procedure for the financial aspects. It is found that an off-grid project is not economically feasible and the grid connection is necessary only for the sale of excess electricity (not as a backup source). Finally, the relationship between environmental potential and produced energy is found to be linear, with almost constant behaviour for solar systems. [Copyright &y& Elsevier]

Abstract: Water supply systems (WSS) frequently present high-energy consumption values, which correspond to the major expenses of these systems. Energy costs are a function of its real consumption and of the variability of the daily energy tariff. This paper presents a model of optimization for the energy efficiency in a water supply system. The system is equipped with a pump station and presents excess of available energy in the gravity branch. First, a water turbine is introduced in the system in order to use this excess of hydraulic available energy. Then, an optimization method to define the pump operation planning along the 24h of simulation, as well as the analysis of the economic benefits resulting from the profit of wind energy to supply the water pumping, while satisfying the system constraints and population demands, is implemented, in order to minimize the global operational costs. The model, developed in MATLAB, uses linear programming and provides the planning strategy to take in each time step, which will influence the following hours. The simulation period considered is one day, sub-divided in hourly time steps. The rules obtained as output of the optimization procedures are subsequently introduced in a hydraulic simulator (e.g. EPANET), in order to verify the system behaviour along the simulation period. The results are compared with the normal operating mode (i.e. without optimization algorithm) and show that energy cost''s savings are achieved dependently of the initial reservoir levels or volume. The insertion of the water turbine also generates significant economical benefits for the water supply system. [Copyright &y& Elsevier]

Abstract: Urban planning has a considerable impact on the future energy efficiency of buildings and planners lack useful tools to support their decisions. This paper is intended to contribute to fill this gap by presenting a new method based on a genetic algorithm which is able to search for optimum urban forms in mid-latitude climates (35−50°). Here, more energy efficient urban forms are defined as those which have high building absorptance in winter and low summer building absorptance. These forms can be designed by choosing among regular tri-dimensional building geometries with fixed floor space index, which can be parameterized by adjusting the following variables: number of floors, building length ratio, grid azimuth, and aspect ratio on both directions. The results obtained show that adequate urban planning, based on the consideration of the local radiation conditions as a function of latitude, may result in significantly better building thermal performance. In particular, it is concluded that the highest latitudes are more restrictive in terms of optimal solutions: pavilions (cross-sectional square blocks) are best solutions for latitude of 50° and terraces (blocks infinite in length) are preferred for 45°. For lower latitudes, all urban forms are possible. In terms of grid angle with the cardinal direction, it is concluded that the angle should stay between −15° and +15°, except for the latitude of 50° where it can ranges from −45° to +45°. For slabs and terraces urban forms, the spacing between blocks in the north–south direction should be maximized, quantified by a building-height-to-street-width (aspect) ratio which decreases with the increase of latitude, ranging from 0.6 for a latitude of 35°, to 0.4 for a latitude of 45°. For pavilions, the north–south aspect ratio is independent of latitude and should stay close to 0.7. The pavilion is the urban form which allows for a larger number of floors. [Copyright &y& Elsevier]