Search

Achieving precision in the prediction of buildings' dynamic heat load is crucial for the advancement of smart heating systems. This research highlights the urgent need to enhance the accuracy of models predicting dynamic heat load. Through literature review, distinguished machine learning and regression algorithms were chosen to formulate prediction models. These models employ a data time-step adaptive strategy, a physics-guided loss function, and fundamental principles of heat transfer. Optimization algorithms of a mathematical nature were utilized to fine-tune the parameters and the framework of long short-term memory (LSTM) and multi-layer perceptron (MLP) models. An analytical comparison was undertaken between physics-guided models and those not guided by physics. Principal conclusions are: 1) Pelican optimization algorithm (POA)-LSTM model emerges as superior in heat load prediction accuracy of an office building, with percentage errors for actual and simulated datasets ranging from −6.7 % to 5.8 % and −5.2 %–4.5 %, respectively, and the mean absolute percentage error (MAPE) standing at 2.3 % and 1.3 %. 2) The linear regression model exhibits the lowest precision, with a MAPE of 17.5 % and 4.0 % for the 7-day prediction results in the actual and simulated datasets, respectively. These findings provide support for improving heat load prediction in heating systems. • The authors have implemented a total of 20 physically-guided models for predicting building thermal load, among which the POA-LSTM model demonstrates the highest accuracy. • The disparities in thermal load prediction accuracy between the physically-guided machine learning models and the physically-guided mathematical regression models have been identified. • The accuracy of thermal load prediction was compared between the five physical guidance models proposed in this paper and the five non-physical guidance models mentioned in other papers. [ABSTRACT FROM AUTHOR]

In an integrated electricity-gas system (IEGS), gas-fired units with flexibility response capabilities address the uncertainty associated with renewable energy by swiftly adapting their output, which may result in uncertain fluctuations in the gas withdrawal of gas-fired units, potentially posing risks to the security of IEGS. Hence, it is necessary to efficiently evaluate the dynamic security region (DSR) of natural gas systems in IEGS by considering the real-time dynamic characteristics of natural gas systems, which are not satisfactorily handled in state-of-the-art works. To bridge this gap, this paper first conceptionally verifies the necessity of the DSR and establishes its mathematical model. Then, a dimensionality reduction method is proposed for the efficient solution and visualization of the high-dimensional DSR evaluation model. A fast evaluation (FE) algorithm is developed to address the difficulties of the nonconvex dynamic constraints in the reduced DSR model. Finally, the necessity and notable advantages of the proposed DSR model and FE are verified based on small and relatively large test systems in comparison with common security region models and algorithms. To the best of our knowledge, this is the first paper that comprehensively presents models and efficient algorithms regarding the DSR of natural gas systems in IEGS. • This paper proposes the novel dynamic security region (DSR) of the natural gas system with natural gas system dynamics. • A dimensionality reduction method for the efficient solution and visualization of the high-dimensional DSR is proposed. • A fast evaluation (FE) algorithm is developed to address the nonconvex dynamic constraints in the DSR model. • Case studies confirm the necessity and effectiveness of the DSR, dimensionality reduction method, and FE. [ABSTRACT FROM AUTHOR]

Urban building layout has an important influence on the formation of shadows on building façades, and photovoltaic (PV) power generation performance is greatly affected by shadows. However, there is limited research on detailed modeling of the power generation of photovoltaic systems on facades with different building layouts. In this paper, according to different urban building layouts, an annual dynamic shadow model of the building and a mathematical model of PV array power generation were established and validated. Then the model was used to calculate the annual power generation hour by hour, optimize the PV array topology, and analyze the shadow shading ratio and PV power generation performance of different building layouts. The results show that 95 % of the best topologies of all partially shaded façades in the four layouts are Total-Cross-Tied (Vertical and Horizontal); the highest annual shading ratio is layout 4 with a value of 60.161 %, the largest annual power generation is layout 3, but layout 4 has the highest broad generation efficiency, with layouts 1, 2, and 3 lower than it by 4.29 %, 0.20 %, and 0.11 %, respectively. This paper provides new ideas for the early design of building layouts and the performance research of PV systems. • Yearly dynamic shadow and detailed PV models developed for urban layouts. • Optimized PV topologies under year-round dynamic shading. • 95 % optimal topologies are Total-Cross-Tied (Vertical and Horizontal). • Compared annual PV output and broad efficiency across building layouts. • Layout 4 excels in broad generation efficiency, leading by 4.29 %. [ABSTRACT FROM AUTHOR]

This paper considers an optimal control problem of large-scale gas supply systems. Solving this problem, we must take into account line packing in systems modeling. For unsteady-state gas flow modeling, a lumped-parameter model is proposed. On the base of this model the paper elaborates a system of ordinary differential equations to imitate unsteady-state gas flow in pipeline system of selectable configuration and provides the integration algorithm using the global gradient method. Adduced an example of calculating a circuitous gas supply system demonstrates the adequacy of the proposed model. The paper includes the mathematical formulation of a technical diagnostics problem of large pipeline system equipment in case of unsteady-state gas flow. The estimation of technical state is reduced to the constrained optimization problem. On the base of the lumped parameters model, we propose an algorithm of the solution of this problem and use it for identification of the gas supply system of selectable configuration. The numerical experiments demonstrate that the algorithm converges with good speed. The paper contains a description of an optimal control concept of large-scale pipeline system. Stated ideas can be applied in case of the system collapse. • For unsteady-state gas flow modeling a lumped-parameter model is proposed. • A method for integrating this system is recommended. • A method for estimating parameters of gas transportation system model is proposed. • A concept of large pipeline system control is described. [ABSTRACT FROM AUTHOR]

Energy consumed by HVAC (heating, ventilating and air conditioning) systems represents a considerable part of the energy consumed in buildings. This paper focuses on achieving energy efficiency, through automatic control strategies, of HVAC systems in the biopharmaceutical industry, a sector little covered by previous studies, mainly focused on residential and commercial buildings. The system under study is an air handling unit (AHU). The main contributions of this research are the obtaining of a dynamic, multivariable, and non-linear model of the AHU, proposing a relatively simple structure and the procedure to estimate its parameters; a non-linear static model of the power consumption of its bank of electrical resistors, also simple, but useful to guide the PID tuning toward energy efficiency; and the approximation to the model of a PID controller whose control low is unknown. The methods proposed to obtain the models and to perform the simulations are also provided. Results for a close-to-reality simulation scenario that suggests the possibility of reducing the power consumed by the resistor bank by 29 % are presented. The use of an industrial PI control algorithm, instead of the classical textbook algorithm, also distinguishes this work from others. • Energy-efficient control of AHUs with cascade control loops requires energy efficiency and effectiveness of internal loops. • Mathematical models and simulations allow to increase the efficiency of control systems by re-tunning its controllers. • To use Hammertein-Wiener models with a proper experiment design is a simple way to capture the dynamics of complex systems. • It is necessary to validate the control algorithms of industrial controllers with experimental data. • Proper tuning of PID loops in AHUs with electric heating, temperature and humidity control, allows energy saving over 20%. [ABSTRACT FROM AUTHOR]

Crystallization fouling is an ongoing concern for many heat transfer systems, and simulating fouling formation under various flow and heat transfer conditions is crucial for predicting fouling resistance and improving energy efficiency. This paper proposes a mesoscopic model for predicting crystallization fouling in narrow rectangle channels accounting for the realistic crystal growth. A hybrid lattice Boltzmann and finite difference model is established to predict the coupled process of fluid flow, heat transfer, concentration diffusion and crystallization fouling. The second-order mass deposition rate is solved and transformed to the surface-reaction boundary condition in lattice Boltzmann (LB) scheme, and the volume of pixel (VOP) method is employed to simulate the dynamic crystal growth. The scheme and the sub-models are verified systematically by the analytical solution of a linear diffusion-reaction problem, the semi-theoretical fouling models, and the experimental data. The results indicate that the present model can effectively predict the crystallization fouling controlled by either surface integration or mass transfer, and show its capability to simulate the non-uniform fouling growth process in heat transfer channels, providing insight towards full understanding and mitigation design of crystallization fouling. • A mesoscopic model of fouling formation under convective heat transfer is built. • Dynamic crystal growth under the diffusion-convection-reaction process is modeled. • Model predictions show good correlation with semi-theoretical model and test data. • The evolving fouling structure with the coupled multi-physics field are analyzed. • A 355-h long term fouling test in narrow rectangle channel is conducted. [ABSTRACT FROM AUTHOR]

Grate boilers are widely applied in biomass combustion for heat and energy generation. However, grate-firing systems often suffer from low efficiency and high emission. Computational fluid dynamic (CFD) becomes increasingly popular as a flexible method to obtain the detailed combustion behaviors in the furnace, and to optimize the performance of existing grate boilers. This paper presents efforts toward a reliable baseline CFD model for an industrial biomass-fired grate boiler, where the structure of the fuel-bed was sufficiently considered. The combustion performances in the furnace were investigated experimentally and numerically by coupling the fuel bed and freeboard, to clarify the impact of bed structure on the simulation accuracy. Results show that when the bed structure has been taken into account, the predictions are in better agreement with the various measurements, as the deviations between them are all within 10 %. Moreover, the flame center drops, the total heat transferred to the water-cooled walls increases, and the residence time of flue gas is greatly prolonged from 2.76 s to 3.90 s, resulting in a distinct difference of the temperature and species patterns in the freeboard. The simulations will provide valuable theoretical guidance for the accurate modeling of grate-fired boiler. [Display omitted] • A baseline model is proposed for accurate modeling of biomass-fired grate boiler. • Effect of fuel-bed structure on the simulation of grate boiler is clarified in detail. • Bed structure greatly affects the predicted temperature and species patterns. • Flue gas residence time and heat transfer are also highly impacted by bed structure. [ABSTRACT FROM AUTHOR]

Microalgae is one of the most promising feedstocks for biofuel production because it yields the high content of sugar and oil. In order to help to develop this nascent industry, this paper proposes a mixed integer linear programming (MILP) model for planning and designing a microalgae-based biobutanol supply chain network. The goal of this study is minimizing the fixed cost of constructing required facilities, transportation costs, and operational costs (harvesting, pretreatment, treatment, and energy conversion). This paper considers supply, production, distribution, and addresses a multi-period model. Since the volume of harvested and dried algae cannot be determined accurately, a fuzzy programming approach is employed to address uncertainties. Additionally, a data envelopment analysis (DEA) method is used to reduce the complexity of solving the proposed model. The applicability of the model is evaluated through a real case study of Iran. • An MILP model is proposed for planning and designing a microalgae-based biobutanol supply chain network. • The model minimizes fixed costs of constructing required facilities, transportation costs, and operational costs. • A fuzzy programming approach is employed to address with uncertainties. • A DEA method is used to reduce the complexity of solving the proposed model. [ABSTRACT FROM AUTHOR]

Abstract The paper presents selected results of simulations of a rapid increase in the supercritical power boiler thermal load. The simulations concerned the possibility of obtaining the required increase in the live steam mass flow rate at the boiler outlet in a set period. This condition must be met to achieve the required increase in the power unit load, of the order of a few dozen MW in a few dozen seconds. For this purpose, it is necessary to decrease the boiler pressure and increase the fired fuel mass flow rate at the same time. The pressure reduction is carried out by opening, at a constant rate, the control valves installed on the pipeline at the turbine inlet. Assuming that the rate is known, the unknown parameters are the values of the target pressure reduction and the time of the pressure decrease process duration. The values vary depending on the power unit initial load. After the pressure decrease process is stopped, the required increase in the power unit load (the increase in the live steam mass flow rate) should be maintained only by firing more fuel. The required values of the target reduction in pressure within a specific range of the power unit load can only be determined by developing a precise mathematical model of the entire boiler and performing simulation computations. The obtained results are of fundamental practical importance because they are used by the boiler manufacturer to generate the power unit modified sliding curves. The results presented in the paper relate to a supercritical power unit now being constructed in one of the Polish power plants. An in-house mathematical model was developed for the power unit boiler. The model comprises all heating surfaces of the boiler and enables simulation of the boiler operation in conditions of rapid changes in loads. Highlights • The effects of turbine valve opening and increasing the fuel mass flow rate are simulated. • A new algorithm for the steam mass flow rate rapid increase at the boiler outlet is proposed. • The correct values of boiler pressure reduction can only be determined by computations. • A required increase in the supercritical power unit load is possibly in a set period. [ABSTRACT FROM AUTHOR]

The paper presents a new mathematical model of the processes of charging and discharging a thermochemical energy storage (TChES) reactor with a high potential for effective application in a residential building. The model is an intermediate approach between lumped-element models and 2D/3D spatially resolved models. The paper also contains the results of the numerical implementation of the developed model. The efficiency of the storage process is one of the key parameters describing the operation of the system, and the study of the impact of individual factors on its value is one of the main goals of the work carried out. A system for heat accumulation using solar collectors and a fixed bed thermochemical reactor was proposed for the analysis. The K 2 CO 3 hydration/dehydration reaction was selected for analysis purposes, but the model is also valid for other reversible reactions. The following parameters describe the considered reactor operations: specific humidity and temperature of the moist air in the reactor, degree of transformation of K 2 CO 3 ·1.5H 2 O into K 2 CO 3 and bed temperature across the reactor. Their temporal and spatial variations in the reactor enable finding the amount of energy accumulated in the reactor during the charging process (or the amount of heat rejected to the moist air in the reactor during the discharging process). Therefore, the efficiency of the storage process (or the efficiency of the discharging process) can be determined. The simulation results provide insight into the multi-physical phenomena occurring during heat accumulation and release processes. Therefore, they help identify the factors with the most significant impact on the proposed reactor's operation. It was found that the species conversion process and amount of heat stored are affected by the bed geometry (ratio of the inner and outer radius of the reactor, bed and particles porosity, and diameter of the bed particles) as well as reactor's diffusive properties. The developed model and presented results might facilitate the creation of valuable experimental setups and save the time and resources spent on unsuccessful experimental attempts. • A thermochemical heat storage system single-family building was analysed. • The K 2 CO 3 hydration/dehydration reaction was selected for analysis. • A mathematical model of charging/discharging process was developed. • The influence of most important factors on reactor's operation was investigated. • The inlet parameters of heat transfer fluid and bed geometry showed the greatest impact. [ABSTRACT FROM AUTHOR]

Abstract Within the domain of sustainable manufacturing, most of the ongoing research efforts, regarding reduction in energy consumption, are focused on manufacturing processes while a little effort is being made to make other production related efforts energy-efficient. This paper presents an analytical effort for saving energy in a machine shop environment by optimizing assignment of manufacturing processes to various machines and grouping machines in various cells for minimizing parts transportation distance. A nonlinear mathematical model is developed that seeks minimization of total energy consumed in machining various quantities of multiple parts and their transportation within the machine shop. An algorithm based on simulated annealing metaheuristic is developed for solution of the mathematical model. The model is then applied for energy based revamping of a machine shop, which deals in manufacturing of various quantities of multiple jobs. It is found from its application that significant levels of production and transportation energies can be saved by assigning the manufacturing operations to the most appropriate machines and optimally grouping the machines into machine cells, respectively. The paper contributes towards energy conservation by optimizing facility layout and production planning of a manufacturing setup. Highlights • Production energy can be saved by optimizing allocation of processes to machines. • Transportation energy can be saved by properly grouping machines in manufacturing cells. • Optimally formed cellular manufacturing system is energy-efficient replacement of job-shop. • 26% of energy is saved in cellular manufacturing system without affecting workload balance. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a bi-objective mathematical model is presented for energy hub scheduling with consideration of preventive maintenance policy. In the model, the hub equipment is assumed to be at risk of random failure, and a periodic preventive maintenance action is planned considering the energy hub utilization plan to take the system into an operational state as good as new. The aim of the proposed model is to determine the preventive maintenance cycles and the best strategy to allocate hub energy capacity under different demand scenarios, while the goals are to minimize costs and to maximize the reliability of the system. The novelty of this paper is the integration of preventive maintenance scheduling and energy hub scheduling. Considering the uncertainty of the demand, a scenario-based two-stage stochastic programming approach is used. CPLEX solver of GAMS is used to solve the model based on the Epsilon-constraint method. The sensitivity analysis is provided to define the effect of parameters such as demand and capacity on the model. The performance of the proposed integrated model is compared with the solutions offered by two well-known techniques from the subject literature. The results show that the integrated model possesses outstanding performance. Highlights • An integrated energy hub scheduling and preventive maintenance scheduling model is studied. • The risk of random failure for hub equipment is considered. • The scenario-based two-stage stochastic programming for energy hub scheduling is developed. [ABSTRACT FROM AUTHOR]

The heliostat field of solar power tower (SPT) system occupies a large proportion of both the total investment and total energy losses of a plant. However, the optimization design of a heliostat field is a challenging work, because there are too many parameters to be optimized. In this paper, a new high-dimensional genetic algorithm toolbox (HDGA) is developed in Visual Studio Community 2015 for the heliostat field design, in which a new crossover strategy is employed for the high-dimensional optimization. The algorithm is verified by both mathematical models and engineering cases, the results show that HDGA is more effective for the high-dimensional problem, and its convergence speed is much faster than that of the genetic algorithm toolbox developed by the University of Sheffield (Sheffield GA). The new algorithm is explained in detail and the optimal field layout is presented. With the new algorithm, a heliostat field referencing to the Gemasolar plant is optimized in this paper. The results show that the optical performance of the heliostat field is improved significantly than that of the un-optimized case, and the optical efficiency of 63.7% is reachable at the design point. At the same time, the annual insolation weighted efficiency is 56.9%. [ABSTRACT FROM AUTHOR]

As environmental awareness grows, sustainable scheduling is attracting increasing attention. The purposes of this paper are obtain the lower bound of energy-efficient flexible job shops with machine selection, job sequencing, and machine on-off decision making via a new mathematical model and to discover more energy-efficient rules with easy implementation in real practice via an efficient Gene Expression Programming (eGEP) algorithm. This paper first formulates a novel mixed-integer linear mathematical model to achieve effective machine selection, job sequencing, and machine off-on decision making. Then for the purpose of avoiding the empirical combination, five attributes exerting direct influence on the total energy consumption are extracted and consequently involved in the evolutionary process of eGEP. Furthermore, diversified rule mining operations with multi-gene representation and self-study are designed to enhance the search space and solutions quality. And, unsupervised learning is utilized in which global best and current worst are set to guide evolution direction since the learning progress has no prior knowledge. Experimental results show that machine off-on decisions efficiently reduce the total energy consumption; and, the discovered rules reach the lower bound calculated by GAMS/CPLEX in small problems and have significant superiority over other dispatching rules in energy saving. [ABSTRACT FROM AUTHOR]

Numerous metrics and indices have been proposed for the assessment of thermal perception and comfort. Commonly used indices based on the estimate of the heat flow between the human and its environment includes the well-known Fanger's method, also known as the PMV-PPD thermal comfort model. Recently this thermodynamic approach has been expanded with the application of the second law of thermodynamics. In this paper, an exergy-based analysis of the relation between the human and its environment is presented. Heat and mass flow rate due to convection, radiation, evaporation and respiration are calculated and expressed in terms of exergy loss. This value is used in the modified Fanger's thermal comfort model, where the heat balance equation is replaced by the exergy loss. The paper builds upon prior studies on determination of internal and external exergy losses by revised and newly defined formulas taking into account clothing and indoor conditions. The results quantitatively show that thermal energy load in the original Fanger's PMV model could be substituted by exergy loss and it corresponds to a certain level of subjective assessed thermal comfort level. [ABSTRACT FROM AUTHOR]

It is a challenging task to solve a large-scale Inter-Plant Heat Integration (IPHI) problem, especially for simultaneous optimization for intra- and inter-plant heat integration. In the companion paper (Part I), a novel screening algorithm named Nearest and Largest Q r e c -based Screening Algorithm (NLQSA) was proposed. It can be used to divide a large-scale IPHI problem into several small ones, each of which includes two or three plants, while keeping the theoretical maximum inter-plant heat recovery potential Q r e c max almost unchanged. NLQSA provides a prior solution before determination of inter-plant Heat Exchanger Network (HEN) configuration for each achieved small IPHI scheme. In this paper, a modified MINLP model with an objective of minimum Total Annual Cost (TAC) is proposed to determine the final inter-plant HEN configurations of achieved segregated IPHI schemes. With the addition of stream data extraction method and NLQSA which were proposed in Part I of this paper series, a complete three-step strategy is established in order to solve the large-scale IPHI problem. Theoretically, a large-scale IPHI problem can be solved no matter how many plants involved. A case study with seven plants is introduced to illustrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The paper is devoted to the main results of the development and application of a multilevel approach to mathematical and computer modeling of large-scale pipeline systems. The approach is intended to overcome the problems of dimension of such systems, as well as fragmentation of information and methodological support of modeling tasks that are dealt with at different departmental, regional, organizational and temporal levels of decision-making on the control of pipeline system expansion and operation. The principles and experience of the implementation of a computer platform for the automation of customization and use of multilevel information and computational models of pipeline systems of various purposes are characterized. Heating systems are used as an example to set forth the mechanisms for implementing the multilevel approach to calculate and analyze operating conditions in the design, operation and dispatch control. The formalization of the hydraulic planning task is presented as a discrete-continuous optimization problem of large dimension with multiple criteria. A new procedure for hierarchical optimization of hydraulic conditions and new methods to solve the problems of optimization of different hierarchical levels and coordination of solutions are presented. This approach could be useful in calculation of energy systems (heat, gas, water, electricity, etc.). [ABSTRACT FROM AUTHOR]

This paper deals with the Bayesian estimation of flow parameters in a porous material based on the measurements of local temperature at selected points inside the packed-bed. The unknown probability distribution function of estimated parameters was sampled using a Markov Chain Monte Carlo (MCMC) method. The MCMC method is efficient in sampling unknown distributions, but it is extremely time-consuming. The Proper Orthogonal Decomposition was used to construct off-line, low order approximation of the porous media flow problem. This model was further incorporated into the Metropolis-Hastings algorithm to retrieve the posterior distribution of the unknown parameters. This approach allowed us to decrease the computational time necessary to generate an ergodic Markov Chain. The efficiency of the proposed approach was tested on the simulated data generated with commercial CFD tools, and finally, it was applied to the real data acquired on the dedicated experimental stand. • Research highlight are summarized as follows: • Development of the mathematical model of biomass drying process. • Development of the coupled POD-MCMC inverse methodology estimate unknown parameters of the model. • Analysis of the accuracy of the developed approach. • Application of the inverse method to estimate model parameters for a real measurement data. [ABSTRACT FROM AUTHOR]

The challenge in developing an electric tractor control strategy lies in operating efficiently and smoothly in most conditions. This paper put forward a co-optimization energy management strategy (EMS) for dual-motor electric tractors to achieve working efficiency and smoothness simultaneously in typical conditions including ploughing, rotary tillage and transportation. Firstly, the mathematical models for components of the drive system are established, such as the power transfer model and gear shifting model. Secondly, the novel EMS combining demand torque calculation method (DTCM) and driving torque distribution strategy (DTDS) is proposed, which is based on nonlinear PID control and modified snake optimizer (SO) algorithm respectively. Then, the hardware in the loop (HIL) platform is manufactured, and load data for the HIL test collecting by a tractor operating in the field. Finally, the performances of the electric tractor with the novel EMS in three typical conditions are validated. It shows that EMS can identify the demand torque accurately. Compared to the rule-based algorithm with reasonable parameters, the novel EMS improves efficiency and stability significantly, especially in ploughing increasing efficiency by 14.44% and decreasing jerk fluctuates by 73.33%. The research results can provide theoretical references for developing the EMS of the electric tractor. • An energy management strategy is designed for a dual-motor driven electric tractor. • This strategy consists of nonlinear PID control and modified SO algorithm. • The nonlinear PID control is applied to calculate the demand torque of the tractor. • The modified SO algorithm is used to distribute the driving torque of the two motors. • HIL platform with three typical conditions is performed to verify the strategy. [ABSTRACT FROM AUTHOR]

Building thermal mass control has great potentials in saving energy consumption and cost. Optimal control schemes are able to utilize passive thermal mass storage to shift the cooling load from peak hours to off-peak hours to reduce energy costs. As such, this paper explores the idea of model predictive control for building thermal mass control. Specifically, this paper presents a study of developing and evaluating a multi-objective optimization based model predictive control framework for demand response oriented building thermal mass control. This multi-objective optimization framework takes both energy cost and thermal comfort into consideration simultaneously. In this study, the developed model predictive control framework has been applied in six commercial buildings at Boston, Chicago, and Miami, under typical summer weather conditions. Time-of-use electricity prices from these three locations are used to calculate the cooling and reheating energy costs. Pareto curves for optimal temperature setpoints under different thermal comfort requirements are calculated to show the trade-off between the cost saving and thermal comfort maintaining. Comparing with a typical “night setback” operation scheme, this model predictive control schemes are able to save energy costs from 20% to 60% at these three locations under different weather and energy pricing conditions. In addition, the Pareto curves also show that the energy cost saving potentials are highly dependent on the thermal comfort requirements, weather conditions, utility rate structures, and the building constructions. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to investigate the challenges in modelling the energy losses of heating networks and to analyse the factors that influence them. The verification of the simulation was conducted on a test stand in-situ and based on the measurements of the testing station, a database for the final version of the numerical model was developed and a series of simulations were performed. Examples of the calculated results are shown in the graphs. The paper presents an innovative method of identify the energy losses of underground heating network pipelines and quantify the temperature distribution around them, in transient working conditions. The presented method makes use of numerical models and measured data of actual objects. The dimensions of the pipelines used were 6 m wide, 8 m high and 1 m in depth, while they were simulated under conditions of zero heat flow in the ground, in the perpendicular to the sides direction of the calculated area and considering the effects of ground's thermal conductivity. The mesh was developed using advanced functions, which resulted its high quality with the average orthogonal quality of 0.99 (close to 1.00) and Skewness of 0.05 (between 0.00 and 0.25). To achieve better accuracy of the simulation model, the initial conditions were determined based on the numerical results of a three-dimensional analysis of heat losses, in steady state conditions in a single moment. The validation process confirmed the high quality of the model, as the differences between the ground temperatures were approximately 0.1 °C. [ABSTRACT FROM AUTHOR]

Abstract The subject of this paper is the steam boiler nonlinear mathematical model. The furnace chamber heat transfer is modelled assuming that the flue gas temperature across the entire furnace chamber is constant. Only radiation heat transfer to the boiler waterwalls is modelled. Distributed parameter mathematical models are developed of the steam superheater individual stages: the superheater first stage, the platen superheater, the second and third stage of the superheater. In the same way, the boiler two-stage economizer is modelled. The flue gas and air temperatures downstream the air heater individual stages are determined using the ε-NTU method (effectiveness ε - the number of transfer units NTU). Due to such arrangement of the boiler heating surfaces and the heat transfer nonlinear character, iterative calculations of the steam, flue gas, and air temperatures are necessary. The developed mathematical model makes it also possible to determine temperatures of the tube outer and inner surfaces and external fouling for all heating surfaces of the boiler. The developed non-linear mathematical model of the entire boiler has high practical importance. The proposed mathematical model can be used to simulate the boiler operation in various conditions, allowing to determine and correct selection the parameters of boiler operation. A non-linear mathematical model of the boiler can also be used to design the individual stages of the superheater properly so as to achieve the desired temperature behind the individual stages. Determination of the local temperature of the tube wall allows selecting an appropriate grade of steel for the individual stages of the superheater. Also, the developed non-linear mathematical model can be used for boiler operation monitoring in on-line mode. Highlights • A nonlinear mathematical model of the entire steam boiler was presented. • Mathematical models of individual heating surfaces in the boiler were presented. • Results of the boiler operation simulations were presented. • Results of the boiler economizer operation were presented. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a new online-ready mathematical model of a supercritical power boiler, which enables comprehensive analysis of the boiler dynamics. The model allows generating modified sliding curves for a power unit that is currently under construction in one of a Polish power plant. The modified sliding curves illustrate the transients of the steam at the turbine inlet, which varies depending on the power unit load. The developed model allows analysing the boiler operation during start-up from cold, warm, and hot states. Moreover, the model allows simulating the boiler operation when the power unit output increases by 7.5% and 5% in a specified period. To satisfy the requirement of increasing the power unit load by 5% in a set period, the live steam mass flow rate must be increased at the boiler outlet. For this purpose, the live steam pressure at the turbine inlet is reduced, and the fuel mass flow rate is increased simultaneously. This results in an increase in the live steam mass flow rate at the boiler outlet. The total increase in the live steam mass flow rate can be determined using the developed model. After the pressure decrease process is stopped, the required level in the steam mass flow rate at the boiler outlet should be achieved only by firing more fuel. The only approach to obtain the appropriate values of the target decrease in the pressure at a set load, in the range of the power unit loads from 40% to 80%, is to develop a mathematical model of the entire boiler and perform the simulations. All the simulations are performed using an in-house developed computer program. Highlights • A new mathematical model for comprehensive analysis of power boiler dynamics. • Analysis of a once-through supercritical steam boiler start-up from the cold state. • New algorithm for the rise in the power unit power output in a set period of time. • Selective Catalytic Reduction reactor and Rotary Air Heaters mathematical models. [ABSTRACT FROM AUTHOR]

Abstract The uncertainty of market demand and dynamic behaviour of the pipeline system are usually ignored in previous gas supply reliability assessments. With the intent of overcoming these deficiencies, a novel methodology to assess the gas supply reliability of natural gas transmission pipeline systems is proposed in this paper. Considering both gas supply capacity and market demand uncertainties, calculations of these two items are integrated into a single Monte Carlo simulation. On each Monte Carlo trial, the hydraulic analysis of unsteady flow is combined with the state transition process simulation to calculate the gas supply capacity. In terms of market demand, the load duration curve technology is employed to predict the amount of demand. Then, the indicator proposed to quantify gas supply reliability is calculated on each trial. Finally, the average gas supply reliability is obtained based on N Monte Carlo trials. Applications of this methodology are demonstrated through a real transmission pipeline system. Thereafter, the method is compared with previous approaches and differences are discussed. Furthermore, the impacts of supply capacity and market demand uncertainties on the gas supply reliability are investigated and suggestions to improve the gas supply reliability are proposed. Highlights • A methodology to assess gas supply reliability of pipeline systems is proposed. • Demand uncertainty and system's dynamic behaviour are considered. • A real pipeline system is adopted to demonstrate the feasibility of methodology. • The impacts of supply capacity and market demand uncertainties are investigated. [ABSTRACT FROM AUTHOR]

Abstract In this paper, a novel thermoelectric assisted indirect evaporative cooling system is proposed. Specifically, thermoelectric cooling (TEC) modules are sandwiched between channels of a flat plate cross flow indirect evaporative cooler. A mathematical model of the novel system is developed, and influences of main operating and geometrical parameters on the system's performance are analyzed in detail. Analytical results show that with the assistance of the thermoelectric cooling, the proposed system is able to cool primary air to a temperature much lower than inlet air wet bulb temperature, even dew-point temperature, meanwhile keep a relatively high coefficient of performance (COP), by selecting appropriate number and electric current of TEC modules. The dew point effectiveness and COP of the proposed system change monotonously with inlet mass flow rate, temperature and humidity ratio of primary air, respectively. The dew point effectiveness also varies monotonously with the mass flow rate ratio of secondary air to primary air. However, there exists an optimal mass flow rate ratio resulting in a maximum COP. Moreover, under variable number and electric current of TEC modules, there always exist optimal widths of primary air channel and secondary air channel, leading to a maximum COP. Highlights • A novel thermoelectric assisted indirect evaporative cooling system is proposed. • A mathematical model of the novel system is developed. • Effects of main operating and geometrical parameters are studied. • The system's cooling effectiveness increases with the assistance of TEC modules. [ABSTRACT FROM AUTHOR]

Abstract A new method using liquid desiccant in compressed air drying was put forward in our previous work. However, only the test bench of the pressurized dehumidifier was established and analyzed. And the regenerator was not established, so the proposed system was not complete. Thus, the system performance of the complete system is unknown. In this paper, the experimental bench and steady-state mathematical model of the complete system are established to investigate the system performance. The dew point of compressed air is −2.4 °C (0.8 MPa) in experiments, indicating dryness could meet needs of various industries which use cooling dehumidification. Besides, the average regeneration temperature is 72.9 °C in experiments, indicating using waste heat from the air compressor to drive solution regeneration is feasible. Moreover, effect of different key parameters, including solution flow rate, solution temperature and ambient conditions on system performance is analyzed by mathematical model. It can be concluded that relative higher solution flow rate, lower inlet solution temperature of dehumidifier and higher inlet solution temperature of regenerator can get a lower humidity ratio. The selected regeneration temperatures in different ambient conditions are 70 °C (summer), 39 °C (winter), 60 °C (transitional season) respectively, which can be used as a reference for the actual operation. Highlights • A steady-state mathematical model of the novel compressed air drying system is established. • Using waste heat from air compressor for desiccant regeneration is verified by experiments. • The novel system can get the compressed air with dew point temperature of −2.4 °C (0.8 MPa). [ABSTRACT FROM AUTHOR]

In order to meet the requirement of frequent start-stop of the units, it is significant to optimize the operation scheme of the unit. A novel optimized mathematical model of a steam turbine was proposed at a previous paper of this study’s authors. In this study the supported vector machine (SVM) stress model of a 320 MW steam turbine was established based on 13 groups of start-up schemes. According to the novel optimized mathematical model and SVM stress model of the turbine, Genetic algorithm-particle swarm optimization was employed to search for the best values of the steam temperature rise rate. The optimization schedule can shorten the start-up time of 170 min in the premise of meeting the stress requirement. It is necessary to testify the feasibility of the optimized schedule, the fatigue, creep, and creep-fatigue life of the steam turbine rotor were analyzed by continuous damage mechanics (CDM) model. The results shown that the life assessment of the rotor from the nonlinear CDM is accordance with the bilinear failure criterion of ASME Section III, and the critical creep-fatigue damage of the rotor is 0.2083, and the life loss of the rotor after working 30 years under the optimized start-up schedule is 19.25%. [ABSTRACT FROM AUTHOR]

The lack of access to electricity in developing countries necessitates spatial electricity planning for guiding sustainable electrification projects that evaluate the costs of centralized systems vis-a-vis decentralized systems. Heuristic approaches have been widely used in such electrification problems to find feasible, cost effective solutions; however, most of the time global optimality of these solutions is not guaranteed. Our paper through its modeling approach provides a new methodology to find the least cost solution to this electrification problem. We model the spatial network planning problem as Prize Collecting Steiner Tree problem, which would be a base for a decision support tool for rural electrification. This new method is systematically assessed using both randomly generated data and real data from rural regions across Sub-Saharan Africa. Comparative results for the proposed approach and a widely used heuristic method are presented based on computational experiments. [ABSTRACT FROM AUTHOR]

The exploitation of oceans is currently recognized as an abundant, geographically diverse and renewable source of energy which still remains largely untapped. Marine currents are, together with waves, one of the most promising sources of ocean energy thanks to their enormous potential for electricity production and their high predictability. Owing to the fact that the marine current harnessing industry has only just begun to demonstrate full-scale devices and device arrays, most of the research papers related to marine current harnessing technologies have been focused on improving their technical aspects. However, there is limited information as regards other aspects, such as those of an economic nature, that should be studied in detail in order not to compromise the future of these technologies. The objective of this research is to address this gap by providing an economic-financial methodology that will help quantify the profitability and feasibility of these renewable energy projects. The methodology developed considers the following aspects: (i) a definition of the fundamental variables of the economic model. (ii) a definition of its financing structure on the basis of the industry's common stockholder equity that partners must provide and the estimation of bank financing needs; (iii) a definition of the main components required to obtain the forecast balance, the forecast income statement and the forecast sources and application of funds for the entire service life of the project; (iv) a determination of the cost-benefit analysis, carried out using the information provided in the cash-flows of the project and the forecast sources and application of funds; (v) an analysis of the most important economic-financial ratios of the model and; (vi) the realization of a sensitivity analysis, with the aim of detecting business risks when fundamental variables of the model, such as investment, the annual energy production, the price of energy or the percentage of loan requested, among others, oscillate. The proposed model has been applied to a case study, after which it was found to provide a good profitability for the project and the stakeholders. The results also indicate that the variables that most affect the profitability of the project are the interest rate, the price of energy and the annual energy produced. [ABSTRACT FROM AUTHOR]

The global drive for integration of RESs (renewable energy sources) means that TEP (transmission expansion planning) has to be carried out over geographically wide and large-scale networks under high levels of uncertainty. This leads to complex combinatorial TEP optimization problems, requiring a huge amount of OPF (optimal power flow) computations. The algorithm employed to calculate the OPF must be reasonably accurate but computationally very efficient, because it has to be run for a lot of operational conditions. Overly simplified OPF formulations are not adequate, since they neglect aspects which play a relevant role in TEP. Specifically, network losses significantly influence TEP solutions, but they are often disregarded due to their computational burden. Given their potential impact on the optimal TEP solution, the main focus of this paper is to find an appropriate losses model in the context of medium to long-term TEP for large-scale power systems. Keeping the balance between accuracy and computation time is essential in such problems. The paper presents two alternative linear losses models, as well as two variants of existing ones. These models are compared and tested using case studies, including small, medium and large-scale networks. Practical conclusions and recommendations are drawn from numerical results. [ABSTRACT FROM AUTHOR]

The paper presents an innovative and advanced MCC (mixture controlled combustion). The MCC model is coupled to the innovative mechanistically based 0D spray model presented in a companion paper [1] that provides inputs on fuel mass distribution. Advanced MCC model is embedded into a 2-zone combustion modeling framework. Advanced MCC predicts ROHR (Rate-Of-Heat-Release) as the combination of the premixed and two diffusion parts, which correspond to rich and lean spray region. It also calculates the amount of fuel available for premixed combustion based on the duration of the ignition delay period. In addition, it reduces the reaction rate based on the oxygen availability using mechanistic basis, based on evaporation rate and based on mechanistically determined fuel amount that has reached the walls. High level of model predictability was confirmed by good agreement between the simulated and the measured ROHR traces over very broad operating range of the engine by using fixed parameters of the advanced MCC model and the spray model. Moreover, the applied modeling framework with embedded innovative spray and advanced MCC model features HiL (Hardware-in-the-Loop) compatible computational times. [ABSTRACT FROM AUTHOR]

Under the trend of global energy prices continuously going up, this paper considers the concept of maximized energy reduction to model the energy productivity index by decomposing it into energy technical change and energy efficiency change. The paper takes the eight SADC (Southern Africa Development Community ) members as an example to estimate their energy efficiency, energy productivity change, energy technical change, energy efficiency change, and rebound effect on energy use, as well as to test the Jevons Paradox. The time period of the data spans 2005 to 2009. The empirical result shows large energy performance differences among the eight SADC members. Not one country among the eight members is an energy technology innovator. After calculating the rebound effect and testing the Jevons Paradox, the result shows that there seems to be no obvious Jevons Paradox in this economic region. [ABSTRACT FROM AUTHOR]

Wind energy shows considerable promise for the future. Doubly fed induction generators (DFIGs) are attracting much attention in wind energy systems due to their unique advantages, including a reduced size power converter, as well as versatility in the independent control of active and reactive power. It is important to determine the precise output energy from the DFIG, particularly when the output voltage is unbalanced, in order to be able to undertake an accurate assessment of the entire output energy from the wind farm. This paper presents a new model for the doubly fed induction generator operating under unbalanced conditions. This model is deduced using the space vector and the angle of unbalanced current for the stator and the rotor currents. This model is used for the precise assessment of the output energy from the doubly fed induction generator, whether it generates either a balanced or unbalanced supply of voltage. Also the paper introduces a power circle diagram which translates the use of the proposed mathematical model by a simple way to stand one of the degrees of the unbalance during the unbalanced operation. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear mathematical model of modern regenerative MGT (micro gas turbine) with superior accuracy is developed. The regenerator can improve efficiency and slow dynamic response of MGT. In view of its significant influence on MGT performance, the average static and dynamic model of the regenerator is included. In order to get more accurate mathematical description for off-design condition performance characteristic of compressor and turbine, nonlinear analytical expressions of compressor and turbine are employed instead of polynomial approximate expressions. The specific expressions of nonlinear state space equations are deduced in this paper. Static simulation results prove the correctness and validity of the model. In this paper, the new model is adopted to analyze dynamic characteristic of MGT having regenerator. The new nonlinear model can be used to thoroughly study performance characteristic of MGT and design superior nonlinear controller. [ABSTRACT FROM AUTHOR]

The paper presents numerical analysis of heat recovery exchanger, which operates as an indirect evaporative air cooler in summer conditions and as a typical heat recovery unit during winter season. The numerical simulation is performed with the original mathematical model which is able to simulate the operation during summer and winter season. The model was validated against existing experimental data (operation as indirect evaporative air cooler) and against experimental data collected by authors at Wroclaw University of Technology (operation as heat recovery exchanger). Obtained results allowed for analysis of heat and mass transfer process occurring in considered exchanger during round-year operation. The characteristic heat and mass transfer zones for evaporative air cooler and heat recovery exchanger were established. Results also allowed for analysis of most important problems connected with achieving highest efficiency of the exchanger and achieving safe operating conditions during winter season (preventing the exchanger from freezing). Safe operating conditions (parameters of the ambient air in winter which would guarantee that no frost would be formed on the plates) were established. The analysis of the effectiveness of the novel exchanger with selected factors (i.e. obtained cooling capacity, thermal efficiency and relative effectiveness) was also presented in the paper. [ABSTRACT FROM AUTHOR]

In this paper, a reverse-bootstrap turboexpander-compressor (TEC) scheme is proposed for the direct recovery of expansion work into the cooling capacity of small air-separation plants. A mathematical model is established for the codesign and off-design analysis of TEC. The off-design performance is predicted based on the mean streamline method and is validated by the experimental data. The isentropic coefficient is proposed to evaluate the overall performance improvement of the reverse-bootstrap TEC. The results indicate that the use of a reverse-bootstrap compressor in the original turboexpander can increase the isentropic coefficient by 12% compared with that of the traditional braking turboexpander under design condition. The codesign of the turboexpander and the coaxial compressor can improve the coupling characteristics and further increase the isentropic coefficient by 7.1% under design condition, which shows cooling power improvement by 8.1% and reduction of required heating power by 1.7%. The results and analysis demonstrate that the proposed reverse-bootstrap TEC with the codesign method is an effective way for the energy recovery in small refrigeration systems. [Display omitted] • A reverse-bootstrap TEC is proposed for air-separation plants. • Codesign approach and off-design model are developed for TEC. • Interdependency of TEC operating parameters are quantitatively described. • Codesign of TEC leads improvement of TEC cooling power by 8.1%. [ABSTRACT FROM AUTHOR]

The 1995 survey on DA (decision analysis) in energy and environmental modeling by Huang et al. [1] listed 95 publications; later Zhou et al. [2] updated the survey with 252 publications by classifying the studies according to source of publications, DA method, application area, and several new attributes. As multiple criteria decision-making is a specific perspective to deal with decision problems in energy-related environmental studies with the rapid changes and the increasing complexity of the energy issues, DA techniques have been extended to further methodological developments. This paper aims at illustrating the evolution of DA techniques involved in energy and environmental decision situations. Earlier surveys are extended and refined by classifying and comparing the DA techniques used in 115 energy and environmental studies. It was found that there is increasing importance placed on DA methods, and energy and environmental studies had increased substantially in last ten years. The paper also defines the integrated decision analysis and describes its new developments used in energy and environmental modeling. [ABSTRACT FROM AUTHOR]

In this paper, based on the mathematical models of microalgae growth, the performance of microalgae growth in nitrogen-limited and light-limited continuous culture is investigated and the effect of important factors on the growth is examined. The dilution rate and the influent inorganic nitrogen concentration have been shown to have a significant influence on the growth of microalgae in continuous culture. In order to obtain a maximum productivity of microalgae, lower dilution rate is better for a lower influent inorganic nitrogen concentration and an optimal dilution rate can be obtained for a higher influent inorganic nitrogen concentration. There is an optimal influent inorganic nitrogen concentration corresponding to maximum microalgae productivity, and the optimal value for lower dilution rate is far higher than that for higher dilution rate. This paper will lay a foundation for the design of the operational parameters of continuous culture PBR (photobioreactor). [ABSTRACT FROM AUTHOR]

This paper describes the comprehensive mathematical modeling, simulation and finally validation the developed dynamic equations of a pressurizable liquid piston Stirling engine. The proposed system comprises of the main following components: solar fresnel lens, hot, cold and tuning liquid columns, regenerator, solid pressure intensifier, liquid power piston and output water column. The mathematical modeling of the proposed system is divided into distinct parts, including dynamic of working gas pressure, hot, cold and tuning liquid columns and dynamic of the output part of the system. The obtained dynamic differential equations are rewritten to nine first order differential equations and solved employing 4th order Runge-Kutta numerical method. The pumping head of 1.5 m, the hot and cold side temperature of 100 °C and 20 °C, respectively and zero dead volumes are considered. It is obtained that the working gas pressure has the oscillatory behavior between two upper and lower points, frequently. According to the oscillatory dynamic of working gas pressure, when the working gas pressure is high enough, it can push the liquid power piston to overcome the static pressure of the output column of the pump and finally the water pumping occurs. [ABSTRACT FROM AUTHOR]

This paper presents the development of a comprehensive open-source numerical model to study the dynamic response and load analysis of floating offshore wind turbines. The model accounts for the wind inflow, rotor aerodynamics, multibody structural model of the system, wave and current kinematics, hydrodynamics, and mooring-line dynamics. This coupled simulation tool can be used for analysis, optimization and preliminary design to determine the technical and economic feasibility. Several verification and validation cases are performed to show the correctness of the numerical simulations. The results show that the proposed approach provides an accurate estimate of the wind turbine dynamics and loads. The simulation tool is then applied in the analysis of a 5 MW wind turbine aimed to characterize the dynamic response and to identify potential loads and instabilities resulting from the dynamic couplings between the turbine and the external conditions. This open-source fully coupled aero-hydro-elastic model provides a modular framework to enable investigating a variety of wind turbine configurations, support systems, and mooring lines. Therefore, it is expected that researchers and design engineers worldwide use the model to study, investigate and analyze different aspects of floating offshore wind turbine design, which results is the promotion and advancement of science and technology for floating offshore wind turbines. [ABSTRACT FROM AUTHOR]

This paper compares different operation models of the air-to-water heat pump (HP). Detail focus of this study aims at a potential to increase seasonal coefficient of performance (SCOP) by utilising the predictive control. The considered predictive control uses an outdoor air temperature forecast for the upcoming 48 h. The predictive control operates the heat pump so that it runs, preferably, during the periods of the day with the highest air temperature. For a detailed assessment, a model of the heat supply system with a heat pump supplemented by a heat accumulator has been developed. The mathematical model involves detailed algorithm for time-dependent quantification of the heat demand for the considered model building. Dataset of real operation tests of the HP helps correctly evaluate the coefficient of performance (COP). An original algorithm of predictive control has been developed and tested for different operating parameters and different capacities of the heat accumulator. A long-term record of air temperatures from the last ten years is employed to evaluate the model. The mathematical model allows for a complex parametrical study to evaluate the relations of SCOP - accumulator capacity, SCOP - method of heat pump control. [ABSTRACT FROM AUTHOR]

This paper presents a 2D multiphase non-isothermal mass transfer model for a single-cell direct methanol fuel cell (DMFC). The model includes the reaction of methanol and oxygen at the anode and cathode, respectively. In addition, it also considers the diffusion of every component involved in DMFC—i.e., methanol, water and oxygen at the diffusion layer and the methanol crossover phenomena. It also includes the relation between the temperature and concentration towards the power output. Later, the model was optimised and the result shows this model can generate up to 48 mWcm −2 of power density reflected to 190 mAcm −2 and 0.26 V of current density and voltage, respectively. It shows this study generate a good model compare to previous study, at a methanol concentration of 4 M and operating temperature of 60 °C. [ABSTRACT FROM AUTHOR]

Global problems of effective coal and oil processing waste recovery can be solved by making use of these wastes as the main fuel components for coal water slurries containing petrochemicals (CWSP). Until now, no predictive models have been developed that would simulate the sustainable ignition of CWSPs based on components with highly different properties, such as ash, moisture, and volatile content, heat of combustion, etc. This is exactly the type of model we are presenting in this paper. In order to gain a greater insight in the process under study, the experimental research has been conducted. We have created an experimental database with the main characteristics of CWSP ignition, namely the duration of stages, gas-phase and heterogeneous ignition delay times, maximum combustion temperatures, and minimum sufficient oxidizer temperatures. A mathematical model has been developed predicting the conditions and characteristics of CWSP droplet ignition. The signature feature of the model is that it accounts for all the main heat and mass transfer processes and chemical reactions in the solid fuel – liquid fuel – water system under study. This mathematical model can serve as the basis for estimating and comparing the ignition characteristics of different CWSPs. [ABSTRACT FROM AUTHOR]

Impedance and open circuit voltage (OCV) parameter identification is the key technology for state of health (SOH) diagnosis of lithium ion battery (LIB) in an equivalent circuit model (ECM). The current identification methods of impedance and OCV parameter are time consuming, destructive, non-real-time and costly. It is usually difficult to identify each component from the overall impedance parameter using aforesaid impedance identification methods, which severely affects the identification precision of impedance parameter. Furthermore, fast OCV identification is another difficult issue to be resolved. In this paper, a new real-time and nondestructive method is developed to identify dynamic impedance parameter for SOH diagnosis ECM (SDEM) of LIB. This method can identify ohmic impedance and charge transfer impedance from internal impedance and realize the transformation of Warburg diffusion impedance from frequency domain to time domain. Fast determination method of OCV is proposed based on the short-time and low current pulse to realize real-time measurement and identification of the OCV. Dynamic update of the all parameters is conducted based on least squares method (LSM). SDEM with new developed impedance and OCV parameter identification method is validated with high accuracy. [ABSTRACT FROM AUTHOR]

This paper proposes and discusses a soft-linking procedure between a Computable General Equilibrium (CGE) model and an energy system model with the aim to improve national energy policy decision-making. Significant positive and negative experiences are communicated. Specifically, the process of soft-linking the EMEC and TIMES-Sweden models is presented, and unlike previous work we rely on the use of multiple direction-specific connection points. Moreover, the proposed soft-linking methodology is applied in the context of a climate policy scenario for Sweden. The results display a partly new description of the Swedish economy, which when soft-linking, generates lower CO 2 -emissions in the reference scenario due to a decline in industrial energy demand. These findings point at the importance of linking bottom-up and top-down models when assessing national energy and climate policies. [ABSTRACT FROM AUTHOR]

The project reported in this paper used CFD as a tool to investigate the effect of multi-pass on the shell side heat transfer of a heat exchanger system. The heat exchanger system is equipped with six vertical thermosyphons transferring thermal energy from a heat source (air) to a heat sink (water). The CFD model has been experimentally validated. The two-phase change processes inside the thermosyphons were not modelled during the simulation. Instead, the thermosyphons were treated as solid rods with a constant thermal conductivity, which was calculated theoretically by applying the thermal resistance analogy with the aid of convection, boiling and condensation correlations found in the literature. The heat source consists of multiple air passes on the evaporator section of the thermosyphons and two water passes on the condenser section. Three different arrangements on the evaporator section were investigated with one, two or three shell passes and the thermal performance compared for the three configurations. The investigation was performed at various inlet conditions: a range of air inlet temperatures (100, 150, 200 and 250 °C) and mass flow rates (0.05, 0.08, 0.11 and 0.14 kg/s). The water inlet conditions were kept constant (a temperature of 15 °C and a mass flow rate of 0.08 kg/s). The overall rate of heat transfer was obtained by both CFD and a theoretical model, and the results lay within 15% of the experimental data. The numerical predictions demonstrated that the k − ε Realizable turbulence model is a reliable tool for predicting heat transfer and fluid flow in such heat exchangers. [ABSTRACT FROM AUTHOR]

The wind power time series always exhibits nonlinear and non-stationary features, which make it very difficult to predict accurately. In this paper, a new chaotic time series prediction model of wind power based on ensemble empirical mode decomposition-sample entropy (EEMD-SE) and full-parameters continued fraction is proposed. In this proposed method, EEMD-SE technique is used to decompose original wind power series into a number of subsequences with obvious complexity differences. The forecasting model of each subsequence is created by full-parameters continued fraction. On the basis of the inverse difference quotient continued fraction, the full-parameters continued fraction model is proposed. The parameters of model are optimized by the primal dual state transition algorithm (PDSTA). The effectiveness of the proposed approach is demonstrated with practical hourly data of wind power generation in Xinjiang. A comprehensive error analysis is carried out to compare the performance with other approaches. The forecasting results show that forecast improvement is observed based on EEMD-SE and full-parameters continued fraction model. [ABSTRACT FROM AUTHOR]

Thermoacoustic phenomena can be modeled by means of analytical closed-forms and numerical models. The analytical solution can be obtained with a minimum computational cost, whereas the numerical approach is computationally expensive. The former, however, provides an average solution along the engine, while within the numerical simulations non-stationary phenomena can be observed. This paper includes results related to the modeling of the operation of a thermoacoustic engine both by means of the analytical approach and numerical models. Some computational details and assumptions adopted in both models are discussed. The main focus is placed on the numerical approach, where the model size (number of pores analyzed) is taken into account. The results show differences between a single-pore symmetrical model and multiple-pore ones. The object of the comparisons is to determine the reliability of the modeling of the operation of a thermoacoustic engine and to evaluate sources of discrepancy between models, both numerical ones, as well as the numerical and analytical approaches. [ABSTRACT FROM AUTHOR]

Fuel cell technology is one of the most promising, emissions free, energy conversion technology under renewable energy systems because of its wide ability in most of the commercial applications like electrical vehicles, building cogeneration and standby power supply. Mathematical models are trusted as important tools for designing and performance analysis of fuel cell based systems. Many mathematical models based on thermal, electrochemical and electrical steady states as well as dynamic have been reported in literature to evaluate performance of Proton Exchange Membrane (PEM) fuel cell, but all these models are complex and needs huge amount of data for modeling and performance testing. The present paper proposes simple, but more realistic MATLAB SIMULINK model for PEM fuel cell to evaluate its performance under different operating conditions. The performance of the proposed model is compared with single practical, 25 cm 2 active area, PEM fuel cell for model validation. The presented model is also valid for a stack having any number of cells. [ABSTRACT FROM AUTHOR]

Kalina cycle is a promising power cycle to utilize or recover the heat of low-grade heat sources. Most of previous works focused on the thermodynamic and thermoeconomic analysis or optimization for the cycle. In this paper, an off-design mathematical model for Kalina cycle is established to examine the off-design performance of the cycle with the variation of heat source mass flow rate, heat source temperature and cooling water temperature. A modified sliding pressure regulation method, which regulates the turbine inlet pressure to keep the temperature difference between heat source temperature and turbine inlet temperature constant, is applied to control the cycle when off-design conditions occur. The results show that the modified sliding pressure regulation method keeps Kalina cycle with a good off-design performance. With the increase of heat source mass flow rate or heat source temperate, both of the net power output and thermal efficiency increase. With the increase of cooling water temperature, both of the net power output and thermal efficiency decrease. In addition, the turbine efficiency almost keeps the designed value under the off-design conditions. [ABSTRACT FROM AUTHOR]