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• A novel application of SFO algorithm to extract PV model parameters is presented. • Three-diode PV model is used in this paper. • Parameters of SFO-TDPV model are compared with other optimization based models. • The SFO-TDPV model is verified by comparing its results with measured data. • The error among these results records a value less than 0.5%. This article proposes an accurate and straightforward method for modeling and simulation of photovoltaic (PV) modules. The main target is to find the nine-parameter of a three-diode (TD) model based on the datasheet parameters, which are given by all commercial PV modules. The objective function is formulated based on short circuit, open circuit, power derivative, and maximum power equations. Two parameters (parallel resistance and photo-generated current) are calculated analytically and rest parameters are optimally designed using the sunflower optimization (SFO) algorithm. The presented method is applied to model three types of commercial PV modules (multicrystal KC200GT, poly-crystalline MSX-60, and mono-crystalline CS6K-280M). The optimal nine-parameters obtained in this paper are paralleled with that attained by other approaches. In order to assess the efficiency of the offered approach, I-V and P-V characteristics are validated with measured data under various temperatures and solar irradiations. The error among these results records a value less than 0.5%. Therefore, the simulation results indicate an excellent agreement with the measured data. This proposed approach can be utilized to model any marketable PV module based on given datasheet parameters only. [ABSTRACT FROM AUTHOR]

Highlights • Set-up of a physics-based model to predict the performance curves of pumps as turbines. • The model is calibrated on experimental data from four centrifugal pumps taken from literature. • The predicted performance curves are physically consistent over the entire range of operation. • Model prediction error is acceptable, compared to other methods available in literature. • The physics-based model is powerful and reliable to estimate PAT complete performance curves. Abstract This paper presents the development of a physics-based simulation model, aimed at predicting the performance curves of pumps as turbines (PATs) based on the performance curves of the respective pump. The simulation model implements the equations to be used for the estimation of head, power and efficiency for both direct and reverse operation. Model tuning on a given machine is performed by using loss coefficients and specific parameters identified by means of an optimization procedure, which is first applied to the considered pumps and subsequently to the same machine running in PAT mode. The simulation model is calibrated on data taken from literature, reporting both pump and PAT performance curves for head, power and efficiency over the entire range of operation. The performance data were acquired experimentally from four different centrifugal pumps, running in both pump and PAT mode and characterized by specific speed values in the range of 1.53–5.82. The accuracy of the predictions of the physics-based simulation model is quantitatively assessed against both pump and PAT experimental performance curves. Prediction consistency from a physical point of view is also evaluated. The results presented in this paper highlight that all the performance curves predicted by the simulation model are physically consistent over the entire range of operation. In general, the prediction error on the head of PATs is acceptable, while the accuracy of the prediction of PAT power, and thus of PAT efficiency, is more case-sensitive and usually higher. The relative deviation of model prediction with respect to the field data regarding head and power at the PAT best efficiency point always seems acceptable compared to the uncertainty of the original experimental data and to typical deviations of other methods available in literature. As a conclusion, the physics-based simulation model developed in this paper represents a powerful and reliable tool for estimating PAT performance curves over the entire range of operation based on pump characteristics. [ABSTRACT FROM AUTHOR]

Past studies of hybrid power cycles using multiple heat sources of different temperatures focused mainly on case studies and almost no general theory about this type of systems was developed. This paper is a first comprehensive study of their general thermodynamic performance, with their comparison to their corresponding single temperature heat source reference system, focusing on three types of power cycles: simple Rankine cycle, Rankine cycle with reheat and Rankine cycle with heat regeneration. The generalized expressions for the energy and exergy efficiency differences between the hybrid and the corresponding single heat source system were developed. A number of simulation case studies were performed to help the understanding and confirm the thermodynamic generalization of the results. The results show that the energy and exergy efficiencies of the hybrid systems are higher than those of their corresponding single heat source reference systems if and only if the energy andexergy conversion efficiency (defined in the paper) of the additional heat source (AHS) is larger than that of the original heat source. The conditions that defined the effects of the AHS temperature and heat addition rate on the energy and exergy efficiencies of the hybrid systems as convex or concave curves were described. Comparisons across the first two types of hybrid power cycles were made, showing that the energy and exergy efficiencies of the reheat Rankine cycle is generally higher than that of the simple Rankine cycle as AHS is changed. Recommendations were made for obtaining the maximal energy and exergy efficiency as a function of the AHS temperature, of the heat addition rate by the AHS, and of the AHS position in the power cycle flow sheet. For the hybrid power generation systems with heat regeneration it was found that when using an AHS to raise the net system power by a given amount, using it to replace the higher-pressure extracted steam will result in a higher system energy efficiency than when using it to replace lower-pressure extracted steam. Hybrid cycles can have significantly lower emissions, cost, and fuel depletion. [ABSTRACT FROM AUTHOR]

The "shoeboxing" algorithm is a simplification approach capable of converting a building of any shape into a representative shoebox, with the aim of speeding-up Urban Building Energy Modeling simulations. The procedure works towards accurately predicting both annual energy needs and hourly thermal loads, going beyond the preliminary assessment of buildings' thermal performance at city-scale. Furthermore, the simplification has been particularly developed to work with buildings of complex geometry considering adjacencies and obstructions. After a first validation performed for stand-alone buildings, in this paper, the capabilities of the algorithm are evaluated at district-level on fictional parametrically generated layouts and in different climatic conditions. As a whole, the shoeboxing algorithm properly predicted both heating and cooling needs at building-level in all the considered climatic conditions, yielding annual differences within ±10% and ± 20%, respectively for cooling and heating. Moreover, both annual and hourly deviations showed to be similar in the different climates considered, suggesting that the simplification can be reliably employed worldwide. Finally, the thermal simulation time has been reduced up to 36 times. • District-scale validation of an algorithm for Urban Building Energy Modeling • Buildings are converted in shoeboxes including adjacencies and urban context • The simplification is validated on 64 districts of 324 buildings in three climates • Heating and cooling needs are predicted with differences within ±20% and ± 10% • The algorithm reduced the thermal simulation time up to 36 times [ABSTRACT FROM AUTHOR]

This paper studies the effects of learning and risk aversion on generation company (GenCo) bidding behavior in an oligopolistic electricity market. To this end, a flexible agent-based simulation model is developed in which GenCo agents bid prices in each period. Taking transmission grid constraints into account, the ISO solves a DC-OPF problem to determine locational prices and dispatch quantities. Our simulations show how, due to competition and learning, the change in the risk aversion level of even one GenCo can have a significant impact on all GenCo bids and profits. In particular, some level of risk aversion is observed to be beneficial to GenCos, whereas excessive risk aversion degrades profits by causing intense price competition. Our comprehensive study on the effects of Q -learning parameters finds the level of exploration to have a large impact on the outcome. The results of this paper can help GenCos develop bidding strategies that consider their rivals’ as well as their own learning behavior and risk aversion levels. Likewise, the results can help regulators in designing market rules that take realistic GenCo behavior into account. [ABSTRACT FROM AUTHOR]

Power split configurations exhibit potential on decreasing fuel consumption. However, how to select the best power split configuration among all the possible configurations still need to be explored. In this paper, a one-dimensional searching ECMS (Equivalent Consumption Minimization Strategy) is developed to evaluate fuel consumption for input power split configuration. Additionally, a battery degradation model based on experimental data is applied to evaluate the battery degradation for input power split configuration. According to one-dimensional searching ECMS and battery degradation model, the impact of different input power split configurations on fuel consumption and battery degradation is investigated. Simulations show that configuration T1 has fuel consumption and battery degradation advantages for PHEV city bus application in China. These advantages are observed because the system efficiency operation points of configuration T1 are closer to the high efficiency area than the system efficiency operation points of other input power split configurations. Furthermore, according to the lever model and one-dimensional searching ECMS method, a power split configuration selection method is provided in this paper. The simulation results based on configuration selection method still indicate that configuration T1 appears to have the best fuel economy for PHEV city bus application. Moreover, configuration T5, with a lever length close to 0, exhibits the worst fuel consumption and battery degradation. [ABSTRACT FROM AUTHOR]

• Two innovative small-scale CCHP solar ORC systems are modelled in TRNSYS/MATLAB. • The two systems are powered by two different CSP technologies: CPC and LFR. • The performance is analysed varying location and composition of global irradiance. • The DNI/GHI ratio has an influence on the system performance. • Useful hints for the selection of the best CSP technology with DNI are provided. In this paper, two innovative small-scale solar Organic Rankine Cycle (ORC) trigeneration plants are investigated and compared using a simulation analysis. In particular, the first plant (Plant 1) consists of a 146 m2 Compound Parabolic Collectors (CPC) solar field, a 3 m3 diathermic oil storage tank, a 3.5 kWe ORC plant and a 17 kWc absorption chiller, while the second plant (Plant 2) consists of a Linear Fresnel Reflectors (LFR) solar field of equal reflecting area, a phase change material storage tank equipped with reversible heat pipes, a 3.2 kWe ORC unit and the same 17 kWc absorption chiller as the former. The dynamic performance of the considered plants has been assessed for two Italian locations representative of the European Mediterranean area, Napoli and Messina, having a similar global radiation but a significantly different ratio of direct normal irradiance to diffuse irradiance. The comparison between the two different solar ORC trigeneration systems has revealed the great influence of the solar radiation on the effectiveness of such systems even for locations at similar latitudes. The energy production has been analysed both on a monthly and daily basis. Results have shown that while the performance of Plant 1 is not so sensitive to location and radiation conditions, Plant 2 is greatly affected by these parameters. Moreover, the higher condensing temperatures necessary in summer to supply the absorption chiller significantly limit the electrical efficiency of the solar CPC ORC. On the contrary, the LFR technology allows the achievement of higher temperatures and conversion efficiencies in summer, thus resulting especially suitable for solar cooling applications. In conclusion, this study has highlighted the importance of adequate technology selection with different radiation conditions in order to better exploit the potential of trigenerative solar ORC systems. [ABSTRACT FROM AUTHOR]

Highlights • Improved simulation of activity sequences is achieved through variable memory length models. • Characteristic behavioural patterns are identified and exploited for the simulation of realistic activity schedules. • Average quality improvement over the simulated output of a 1st-order Markov chain model is about 28%. • A new error metric to further assess the quality of the simulation of activity sequences is introduced. Abstract Residential activity modelling has attracted considerable attention over the last years. This is particularly due to the fact that residential energy demand loads are highly dependent on the activity patterns of the household. Therefore, activity models are being increasingly used to underpin high-resolution energy demand models. This paper details the implementation of a new methodology for the analysis of empirical activity data that allows for the identification of characteristic behavioural patterns within them. The identified patterns are then used as the basis for the construction of a high-resolution residential user activity model. The model attempts to capture the statistical characteristics of the empirical data in the form of a stochastic process with memory of variable length. The proposed model is compared to a model based on the predominant first-order Markov chain approach. In addition to the modelling approach, a new metric for assessing the quality of activity sequences simulations is proposed. Given the amount of empirical data contained in any of the individual time-use datasets currently available, it would appear that the performance improvement over the predominant first-order Markov chain approach is modest. However, the validation results show that the proposed approach has the potential for broadening our understanding of the scheduling of activities in people's day-to-day lives and how this relates to the observed variability in both activity and energy consumption patterns. [ABSTRACT FROM AUTHOR]

Highlights • Battery state of charge profiles are affected by the suppressed demand effect. • In small rural systems the suppressed demand effect impacts directly to reliability. • Considering the suppressed effect demand lead to more sustainable systems design. Abstract Rural electrification programs usually do not consider the impact that the increment of demand has on the reliability of off-grid photovoltaic (PV)/battery systems. Based on meteorological data and electricity consumption profiles from the highlands of Bolivian Altiplano , this paper presents a modelling and simulation framework for analysing the performance and reliability of such systems. Reliability, as loss of power supply probability (LPSP), and cost were calculated using simulated PV power output and battery state of charge profiles. The effect of increasing the suppressed demand (SD) by 20% and 50% was studied to determine how reliable and resilient the system designs are. Simulations were performed for three rural application scenarios: a household, a school, and a health centre. Results for the household and school scenarios indicate that, to overcome the SD effect, it is more cost-effective to increase the PV power rather than to increase the battery capacity. However, with an increased PV-size, the battery ageing rate would be higher since the cycles are performed at high state of charge (SOC). For the health centre application, on the other hand, an increase in battery capacity prevents the risk of electricity blackouts while increasing the energy reliability of the system. These results provide important insights for the application design of off-grid PV-battery systems in rural electrification projects, enabling a more efficient and reliable source of electricity. [ABSTRACT FROM AUTHOR]

Highlights • A novel daylight quality evaluation metric named " N-Daylit area" was developed. • The daylighting simulation model in Daysim was experimentally validated. • The daylight and energy performance of STPV facades was investigated. • An optimal design of STPV facades was offered in view of daylight and energy saving. Abstract Building-integrated semi-transparent photovoltaics (STPV) technology has attracted more and more attentions for its obvious advantage in renewable energy utilization. However, the STPV facades have potential conflicts of interest between daylighting and energy efficient. Thus, this paper reported an investigation of the daylighting and overall energy performance of STPV facades in cold climatic regions of China, with the aim of resolving the conflicts. Firstly, the reliability of daylighting model in Daysim was experimentally verified. In addition, a novel dynamic daylighting evaluation metric named " N-Daylit area" was developed, considering the glare phenomenon and setting reasonable indoor illumination thresholds. On basis of this, the effect of several key design parameters, including transmittance、orientation and window-wall ratio (WWR), on the performance of STPV facades installed in a generic reference office was studied, by using a comprehensive simulation method. According to the simulation result, the transmittance and WWR of the STPV façade were recommended to be in the ranges of 50–60% and 40–50%, respectively, for the purpose to improve the energy efficiency of STPV facades with the premise of ensuring a satisfied daylight quality of the tested room. Furthermore, the results also revealed that south facing was the preferred orientation of STPV facades, to obtain the best daylighting quality and the lowest annual net electricity use of the space. [ABSTRACT FROM AUTHOR]

Highlights • A novel Concentrating PV/DC system is proposed for building application. • The concept of combining daylighting and PV system is presented. • Indoor experiment is conducted to validate the optical model. • The actual performance analysis of the CPV/DC system under real weather conditions is presented. • The CPV/DC system can be optimized for different building rooftop designs. Abstract A wide range of developed and commercially available daylighting systems have been reported, however, they have just a single function, so they require an extra complex component to adjust daylighting intensity to create a better visual-comfort interior environment seasonally. Thus, in this paper, a novel concentrating photovoltaic/daylighting control system based on the lens-walled compound parabolic concentrator which is made by the transparent material is proposed. It combines both PV and daylighting control for green building design. At noon, when the incidence angle is small and the solar radiation is strong, the majority of the solar radiation can be collected by the PV cell for electricity generation and the remaining solar radiation will act as the daylighting source. In the morning or evening, when the incidence angle is large and the solar radiation is weak, the majority of the solar radiation will pass into the building for daylighting while the remaining solar radiation will be collected by the PV cell for electricity generation. An optical model was built for the ray-tracing simulation by using the commercial software Lighttools®. The prototype of the lens-walled compound parabolic concentrator was manufactured and assembled for the indoor experiment to validate the optical model. To prove the feasibility of the system, the optical and electrical performance of the proposed concentrating photovoltaic/daylighting control system are derived from the simulation and experimental results, and the actual all-day daylighting performance of it is investigated through the software simulation. The simulation and experimental results indicate good electrical and daylighting performance of the concentrating photovoltaic/daylighting control system, and the proposed concentrating photovoltaic/daylighting control system suits all kinds building rooftop designs with different inclination angles, which proves it a wide scope of application. [ABSTRACT FROM AUTHOR]

With the increasing number of electric vehicles (EVs), the EV fast charging load will significantly affect the voltage quality of electricity distribution networks. On the other hand, EVs have potentials to change the choices of charging locations due to the incentives from the variations of charging prices, which can be considered as a flexible response resource for electricity distribution networks. In this paper, a charging pricing strategy of EV fast charging stations (FCSs) was developed to determine the pricing scheme for the voltage control of electricity distribution networks, which consisted of a simulation model of EV mobility and a double-layer optimization model. Considering the travel characteristics of users, the simulation model of EV mobility was developed to accurately determine the fast charging demand. Taking the total income of FCSs and the users’ response to the pricing scheme into account, the double-layer optimization model was developed to optimize the charging pricing scheme and minimize the total voltage magnitude deviation of distribution networks. A test case was used to verify the proposed strategy. The results show that the spatial distribution of EV fast charging loads was reallocated by the proposed charging pricing scheme. It can also be seen that the proposed strategy can make full use of the response capacity from EVs to improve the voltage profiles without decreasing the income of the FCSs. [ABSTRACT FROM AUTHOR]

Considering uncertain power outputs of distributed generations (DGs) and load fluctuations, energy storage system (ESS) represents a valuable asset to provide support for the smooth operation of active distribution networks. This paper proposes an affine arithmetic-based multi-objective optimization method for the optimal operation of ESSs in active distribution networks with uncertainties. Affine arithmetic is applied to the optimization model for handling uncertainties of DGs and loads. Two objectives are formulated with affine parameters including the minimization of total active power losses and the minimization of system voltage deviations. The affine arithmetic-based forward-backward sweep power flow is first improved by the proposed pruning strategy of noisy symbols. Then, the affine arithmetic-based non-dominated sorting genetic algorithm II (AA-NSGAII) is used to solve the multi-objective optimization problem for ESSs operation under uncertain environment. Furthermore, three types of indices with respect to convergence, diversity, and uncertainty are defined for performance analysis. Numerical studies on a modified IEEE 33-bus system with embedded DGs and ESSs show the effectiveness and superiority of the proposed method. The optimization results demonstrate that the obtained Pareto front has better convergence and lower conservativeness in comparison to the interval arithmetic-based NSGA-II. A multi-period case considering seasonality of DGs and loads is further simulated to show the applicability in real applications. [ABSTRACT FROM AUTHOR]

Thermal energy storage has been shown to improve the efficiency of solar absorption cooling systems by capturing excess insolation during peak to meet cooling demand in low insolation periods. While water is the most commonly used thermal storage medium in solar cooling applications, the small operating temperature range of solar cooling systems limits its energy density. In contrast, Phase Change Materials maintain a high energy density under limited temperature ranges, and are ideally suited for such applications. Methods to select and size appropriate thermal storage technologies in solar cooling applications vary between studies with no standard methodology being utilized across the literature. Moreover, there is limited quantification of the influence of thermal storage on system performance to motivate the additional capital investment in these systems. This study provides an analytical framework to quantify the benefit of the thermal energy storage. Predictions from the analytical model are compared to the results from a validated transient system simulation. The paper gives an engineering approach for predicting the expected benefit from both water and phase change materials based thermal storage for applications with limited temperature ranges. [ABSTRACT FROM AUTHOR]

Smart Grids consist of multiple actors and physical phenomena, which are often difficult to capture in one single simulation framework. Therefore, researchers increasingly couple distinct simulators to form novel “co-simulations”. In this paper we present a literature survey of 26 smart grid co-simulation frameworks. First of all, we present our understanding of a co-simulation. We then classify the 26 frameworks on multiple characteristics, such as simulation tools, synchronization methods and research topics. Finally, we present correlations between different key characteristics, analyze possible research gaps and discuss possible trends and future development areas in the field of smart grid co-simulations. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the impact of different Electric Vehicle (EV) penetration on quasi real-time Volt–VAR Optimization (VVO) of smart distribution networks. Recent VVO solutions enable capturing data from Advanced Metering Infrastructure (AMI) in quasi real-time to minimize distribution networks loss costs and perform Conservation Voltage Reduction (CVR) to save energy. The emergence of EVs throughout distribution feeder increases grid complexity and uncertainty levels that could affect AMI-based VVO objectives. Hence, this paper primarily introduces an AMI-based VVO engine, able to minimize grid loss and Volt–VAR control assets operating costs while maximizing CVR benefit. It then presents a real-time co-simulation platform comprised of the VVO engine, grid model in a real-time simulator and monitoring platform, communicating with each other through DNP.3 protocol, to test the precision and performance of AMI-based VVO in presence of different EV penetration levels. Accordingly, 33-node distribution feeder is studied through different EV penetration scenarios. The results show significant changes in AMI-based VVO performance especially in CVR sub-part of VVO according to EV model and type. Thus, this study could lead near future VVO solutions to gain higher levels of accuracy and efficiency considering smart microgrid components such as EV in their models. [ABSTRACT FROM AUTHOR]

China will enact a national emissions trading system in 2017. The rules for the initial allocation of emission allowances have not been settled yet. This paper assesses the effect of auctioning as an initial emission allowance allocation methods of the China electricity power generation sector. This study employs a combined model with modified Trans-log production function, dynamic simulation model and multi-objective linear programming to provide more realistic results. After estimating the optimal electric power sources structure and technological structure under different auctioning rates, this paper calculates the abatement cost of the China’s electric power generation sector. When the allowance is free, the carbon shadow price will be 206.12 Yuan/ton. When 5% allowance is auctioned, the price will be 216.91 Yuan/ton. When the auctioning rate increases, the carbon emission abatement cost increases accordingly, as does the growth rate. The results also show that when the allowance auction rate is 5%, the marginal abatement costs for coal-fired power generation and clean power generation are 0.123 Yuan/kW h and 0.121 Yuan/kW h respectively, and thus, the total additional cost of the electric power generation sector will increase by 0.244 Yuan/kW h, which would be a heavy burden to China’s electric power generation sector and the forward progress of auctioning in the near future may be hindered. [ABSTRACT FROM AUTHOR]

At the present time, trains in heavy haul operations are typically hauled by several diesel-electric locomotives coupled in a multiple unit. This paper studies the case of a typical consist of three Co–Co diesel-electric locomotives, and considers replacing one unit with an alternative version, with the same design parameters, except that the diesel-electric plant is replaced with flywheel energy storage equipment. The intelligent traction and energy control system installed in this unit is integrated into the multiple-unit control to allow redistribution of the power between all units. In order to verify the proposed design, a three-stage investigation has been performed as described in this paper. The initial stage studies a possible configuration of the flywheel energy storage system by detailed modelling of the proposed intelligent traction and energy control system. The second stage includes the investigation and estimation of possible energy flows using a longitudinal train dynamics simulation. The final stage compares the conventional and the proposed locomotive configurations considering two parameters: fuel efficiency and emissions reduction. [ABSTRACT FROM AUTHOR]

Energy simulation, the virtual representation and reproduction of energy processes for an entire building or a specific space, could assist building professionals with identifying relatively optimal energy conservation measures (ECMs). A review of current work revealed that methods for achieving simultaneous high accuracies in different levels of simulations, such as building level and zone level, have not been systematically explored, especially when there are several zones and multiple HVAC units in a building. Therefore, the objective of this paper is to introduce and validate a novel framework that can calibrate a model with high accuracies at multiple levels. In order to evaluate the performance of the calibration framework, we simulated HVAC-related energy consumption at the building level, at the ECM level and at the zone level. The simulation results were compared with the measured HVAC-related energy consumption. Our findings showed that MBE and CV (RMSE) were below 8.5% and 13.5%, respectively, for all three levels of energy simulation, demonstrating that the proposed framework could accurately simulate the building energy process at multiple levels. In addition, in order to estimate the potential energy efficiency improvements when different ECMs are implemented, the model has to be robust to the changes resulting from the building being operated under different control strategies. Mixed energy ground truths from two ECMs were used to calibrate the energy model. The results demonstrated that the model performed consistently well for both ECMs. Specific contributions of the study presented in this paper are the introduction of a novel calibration framework for multi-level simulation calibration, and improvements to the robustness of the calibrated model for different ECMs. [ABSTRACT FROM AUTHOR]

This paper presents a generic bulk energy storage dispatch model for production costing simulation, and assesses the performance and economics of storage under various system scenarios. The storage model presented captures the dynamic relationship between the reservoir energy status and the storage commitments in energy and ancillary co-optimization market, thereby enabling the dispatch of storage for both energy and cross-market arbitrage opportunities. The paper also presents a methodology to quantify the cycling costs incurred by conventional generating units due to frequent start–shut cycles and ancillary services. The bulk storage technology modeled is compressed air energy storage (CAES), and it is represented within the IEEE 24 bus reliability test system. Simulations are performed to quantify the impacts of bulk energy storage in terms of reduction in market prices, system production and cycling costs, and also to investigate the economic viability of storage projects in terms of payback periods under increasing wind penetration levels. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to contribute to the discussion on the role of Net Zero Energy Buildings (Net ZEBs) on future energy systems by the interplay between on-site generation and the building loads, often called load matching, and the resulting import/export interaction with the surrounding electricity grid, commonly named grid interaction. This investigation analyzes five case studies with high resolution data, three of which are based on real monitored buildings. The research aims at selecting and suggesting a limited set of quantitative indicators that: (a) can provide practical information for building as well as grid designers and operators, and (b) are understandable for a wider audience and do not require complex simulation tools or additional resources. This paper also presents novel graphical representations describing the yearly or daily variation of the indexes in an understandable manner. It has been found that the hourly values of the cover factors (namely, the load cover factor and the supply cover factor) provide quite a good picture of the correlation between on-site demand and supply of energy. These factors illustrate both the daily and seasonal effect, the production pattern of different renewable energy technologies, and applied operation/control strategies. The loss-of load probability factor shows how often the on-site supply does not cover the on-site demand but it provides limited information. Several grid interaction indicators are presented in a normalized form based on the connection capacity between the building and the grid. The generation multiple is an index that compares peak values of exported/imported energy; it may also be used with generation/load values. The dimensioning rate and the connection capacity credit relate the building with the electrical grid. These indexes can be used to analyze individual buildings and extend their use in the case of cluster of buildings. Although some general trends have been identified in the results and the usefulness of these indicators is demonstrated, it should be noted that further studies are needed in order to define reference values for particular building topologies, clusters of buildings and climates, which could be used as a rule-of-thumb for grid/building designers. [ABSTRACT FROM AUTHOR]

This paper describes a novel type of solar concentrator – a rotationally asymmetrical compound parabolic concentrator (RACPC). The RACPC aims at addressing the following objectives: (i) to increase the electrical output of a concentrating photovoltaic (CPV) system by providing sufficient concentration gain; (ii) to minimise the usage of the PV material with the corresponding reduction of CPV system cost, and (iii) to eliminate the requirement of mechanical tracking by providing a wide field-of-view. This paper first provides a short review on variations of compound parabolic concentrator designs available to date. Next, the process of designing the RACPC is presented and the geometrical concentration gain of the concentrator is discussed. In addition, the optical concentration gain is also presented for various angles of incidence. Through simulations, it is demonstrated that the RACPC can provide significant optical concentration gains within its designed acceptance angle. An RACPC based system is an attractive alternative to conventional solar photovoltaic systems. [ABSTRACT FROM AUTHOR]

In a previous paper, we have introduced a simulation and optimization framework for the integration of renewable generators into an electrical distribution network. The framework searches for the optimal size and location of the distributed renewable generation units (DG). Uncertainties in renewable resources availability, components failure and repair events, loads and grid power supply are incorporated. A Monte Carlo simulation–optimal power flow (MCS–OPF) computational model is used to generate scenarios of the uncertain variables and evaluate the network electric performance with respect to the expected value of the global cost ( ECG ). The framework is quite general and complete, but at the expenses of large computational times for the analysis of real systems. In this respect, the work of the present paper addresses the issue and introduces a purposely tailored, original technique for reducing the computational efforts of the analysis. The originality of the proposed approach lies in the development of a new search engine for performing the minimization of the ECG , which embeds hierarchical clustering analysis (HCA) within a differential evolution (DE) search scheme to identify groups of similar individuals in the DE population and, then, ECG is calculated for selected representative individuals of the groups only, thus reducing the number of objective function evaluations. For exemplification, the framework is applied to a distribution network derived from the IEEE 13 nodes test feeder. The results show that the newly proposed hierarchical clustering differential evolution (HCDE) MCS–OPF framework is effective in finding optimal DG-integrated network configurations with reduced computational efforts. [ABSTRACT FROM AUTHOR]

The market for solar energy in the US has grown exponentially due to increased consumer demand resulting from price reduction via economies of scale, technological progress, and a variety of incentives from federal and state governments as well as utility companies. The installation of solar power in Tennessee has more than doubled each year from 2009 to 2011. In this paper, we focus on the behavior of the Tennessee Solar Value Chain (TNSVC) to study the factors that influence growth of solar industry in the state. The impact of existing incentives on the TNSVC is analyzed. The TNSVC is simulated based on inputs from on-site survey to estimate economic impact in terms of the number of jobs added and the tax revenue generated in the state. In addition, a sensitivity analysis for the impact on the TNSVC under different policies those may be adopted by the state of Tennessee in the future is conducted. This paper employs a holistic model which can predict PV installation demand, understand solar value chain capacity, and estimate the revenue generation. It should be noted that the method employed in this study is not unique to the solar energy industry in Tennessee. The data utilized in this study is a combination of public domain information and surveys of suppliers, manufacturers, distributors, and installers. This makes the model in this paper flexible enough to be applied to assess the solar value chain in other state or country. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic three-dimensional volume element model of a parabolic trough solar collector coupled to an existing semi-finite optical model for simulation and optimization. The spatial domain in the volume element model is discretized with lumped control volumes (i.e., volume elements) in cylindrical coordinates according to the predefined collector geometry. The spatial dependency of the model is therefore taken into account without the need to solve partial differential equations. The proposed model combines the laws of thermodynamics and heat transfer as well as empirical correlations to simplify the modeling and expedite the computations, and the resulting system of ordinary differential equations is integrated in time for temperature. The model was validated with the experimental data provided in the literature, and was employed to evaluate the sensitivity of the collector performance described by the first and second law efficiencies to receiver length, annulus gap spacing, concentration ratio, incidence angle, inlet fluid temperature and flow rate. This work also examined the effects of inlet fluid temperature and temperature differential on dynamic collector performance in the transient case study. Results showed that the first law efficiency was most sensitive to the inlet fluid temperature with the maximum variation of 30%, whereas the incidence angle and concentration ratio affected the second law efficiency the most with the maximum variations of 375% and 300%, respectively. The remaining parameters featured trivial effects in all cases. In the transient analysis, higher temperature differential and lower inlet fluid temperature yielded higher total heat gain while the total exergy gain was insensitive to both parameters. The first law efficiency should therefore be of greater importance than the second law efficiency in the control of dynamic collector performance based on these two parameters. [ABSTRACT FROM AUTHOR]

Control of superheater steam temperature (SST) is critical for the safety and efficiency of the coal-fired power plant. However, the conventional cascaded PI controller is faced with great challenges in regulating the SST within a satisfactory range in the environment of extensive load changes, which is inevitably becoming even worse due to the growing integration of the intermittent renewables. To this end, this paper introduces advanced control and multi-objective optimization (MOO) to improve the SST control performance and thus to enable the load being quickly adjusted in a wider range. The inner-loop PI controller parameters are optimized based on the tracking and regulation performance objectives subject to a robustness constraint. The improvement of the outer-loop controller involves two steps, (i) the outer-loop PI controller is upgraded to active disturbance rejection controller (ADRC) in order to eliminate the sluggish response to the external load disturbances; (ii) a mathematical algorithm is developed to depict the stable region for the ADRC parameters, serving as the MOO search space. Comparative simulations show the advantage of the proposed strategy, which is confirmed by a field test in an in-service 300 MW power plant. It shows that the proposed strategy leads to a much smaller temperature deviation in both constant-load and load-varying conditions than the conventional control, making it less sensitive to the external disturbances. Furthermore, the load demand can be shifted more flexibly in a wide range (from 10 MW to 15 MW) while the SST is strictly confined within the allowable range, indicating a promising prospect of the proposed strategy in a power grid with high renewables penetration. [ABSTRACT FROM AUTHOR]

Occupant behavior is regarded as one of the major factors contributing to the discrepancy between simulation prediction and real energy use. Over the past several decades, occupants have been represented as fixed profiles of occupant presence in building energy simulation tools. Recently, stochastic models have been introduced to account for dynamic occupant presence. This stochastic approach is based on the premise that occupant presence can be described by empirical and probabilistic transition rules, e.g. Markov Chain. This paper presents evidence that occupant presence in some rooms and buildings follows a “random walk” pattern. In other words, occupant presence in certain types of buildings cannot be predicted stochastically. In this study, occupants’ presence in two laboratories and three reading rooms at two universities was monitored. The hypothesis of the random walk pattern was tested using the Normalized Cumulative Periodogram (NCP) method. Based on a series of six experiments, it is shown that each occupant’s presence in the five locations follows a random walk pattern. Three different occupant models (fixed ASHRAE model, Markov Chain model, and Random Walk model) were applied in EnergyPlus simulation runs. The adjusted R 2 for three experiments between the fixed AHSRAE model and the random walk model, and between the Markov chain model and the random walk model are 0.54, 0.02, 0.01 and 0.86, 0.19, 0.41, respectively. This does not negate the need for the fixed ASHRAE model or the MC model. Rather, this signifies that, for a certain type of building, another occupant presence model should be introduced, e.g. the RW Model. [ABSTRACT FROM AUTHOR]

This paper presents a computational modeling approach to characterize the internal temperature distribution within a Li-Ion battery pack. In the mathematical formulation both entropy-based and irreversible-based heat generation have been considered; combined with CFD software in order to simulate the temperature distribution and evolution in a battery pack. A prismatic Li-ion phosphate battery is tested under constant current discharge/charge rates of 1C, 2C, 5C and 8C. Model parameters (in particular, the entropic heat coefficient and the internal resistance) needed for the calibration of the model are determined using experimentation. The model is then used to simulate two different strategies for the thermal control of a battery pack in case of car application: an air-cooling and a liquid-cooling strategy. The simulation has highlighted the pros and cons of the two strategies, allowing a good understanding of the needs during the process of battery pack design and production. [ABSTRACT FROM AUTHOR]

In the evaluation of thermal response tests and in the dynamic simulation of ground-coupled heat pumps, the mean temperature T m of the working fluid in a borehole heat exchanger is usually approximated by the arithmetic mean of inlet and outlet temperature. In thermal response tests, this approximation causes an overestimation of the thermal resistance of the heat exchanger. In the dynamic simulation of ground-coupled heat pumps, this approximation introduces an error in the evaluation of the outlet temperature from the ground heat exchangers. In this paper, by means of 3D finite element simulations, we provide tables of a dimensionless coefficient that allows an immediate evaluation of T m in any working condition, with reference to double U-tube borehole heat exchangers with a typical geometry. These tables allow a more accurate estimation of the borehole thermal resistance by thermal response tests and a more accurate evaluation of the outlet temperature in dynamic simulations of ground-coupled heat pump systems. Criteria for the extension of the results to other geometries are also provided. [ABSTRACT FROM AUTHOR]

CHP based combined district heating (DH) systems with gas-fired boilers for peak load shaving have higher energy and environmental efficiencies compared to DH systems supplied heat by heat only boilers. However, proper multicriteria decision making method is lacking for them. This paper is dedicated to develop a decision support framework from economy, energy, technology and environment viewpoints, in order to facilitate the planning/retrofitting of the combined DH systems. Firstly, the installation strategy of gas-fired boilers is introduced, and then combined heating alternatives to be addressed are constructed by choosing different base load ratios of CHP. Secondly, a criterion aggregation system is developed, based on which weights can be elicited using complementary judgment matrix (CJM) plus feasible weight space (FWS) methods. Thirdly, an application-oriented, multicriteria decision support framework is demonstrated in a real-life DH system in Daqing, China. Stochastic multicriteria acceptability analysis (SMAA) is implemented to synthetically handle the decision problem, which is characterized by incommensurable measurements, conflicting preferences, uncertainties and imprecise information. The results indicate that the developed framework works well in the multicriteria decision making for the combined district heating systems. The optimal base load ratio in the demonstration case is between 0.66 and 0.77 with high confidence. [ABSTRACT FROM AUTHOR]

This paper proposes a novel CO 2 capture technology from the integration of partial oxy-combustion and the Calcium-Looping capture process based on the multicycle carbonation/calcination of limestone derived CaO. The concentration of CO 2 in the carbonator reactor is increased by means of partial oxy-combustion, which enhances the multicycle CaO conversion according to thermogravimetric analysis results carried out in our work, thus improving the CO 2 capture efficiency. On the other hand, energy consumption for partial oxy-combustion is substantially reduced as compared to total oxy-combustion. All in all, process simulations indicate that the integration of both processes has potential advantages mainly regarding power plant flexibility whereas the overall energy penalty is not increased. Thus, the resulting energy consumption per kilogram of CO 2 avoided is kept smaller than 4 MJ/kg CO 2 , which remains below the typical values reported for total oxy-combustion and amine based CO 2 capture systems whereas CO 2 capture efficiency is enhanced in comparison with the Calcium-Looping process. [ABSTRACT FROM AUTHOR]

In this paper we consider control-oriented modeling of a sensible thermal energy storage (TES) tank with a helical immersed heat exchanger (IHX) coil. A key focus of the modeling approach is to minimize the number of dynamic states required to adequately describe the system dynamics. The resulting model is well-suited for model-based control design, real-time simulation, and hardware-in-the-loop testing aimed at intelligent operation of TES systems. We use a discretized approach to model the temperature dynamics of the water within the storage tank. We use a quasi-steady approach to model the IHX coil dynamics, thereby limiting computational complexity. In simulation, the model runs up to 1200× faster than real-time. A simulated case study of model-based feedback control demonstrates the utility of the modeling approach. The model contains four tuning parameters that are empirically determined using experimental data collected from a commercially available domestic hot water storage tank. The model is then validated, both temporally and spatially, against data collected during the simultaneous charge/discharge mode. Finally, we quantify the trade-off between model fidelity and increased control volume discretization, showing that a 60 node model yields a RMSE value under 4.5%. [ABSTRACT FROM AUTHOR]

This paper proposes a hierarchical coordination mechanism for coordinating the economic dispatch of transmission system operator (TSO) and distribution system operator (DSO). The challenge of dispatching large-scale distributed energy resources (DERs) is addressed. The coordination problem of dispatching energy and reserve is formulated. Benders decomposition is the underlying mathematical foundation of the proposed hierarchical coordination mechanism. We define the generalized bid function to approximate the dispatch cost of distribution network by a series of affine functions. The generalized bid function is communicated from DSO to TSO. By using convex AC optimal power flow model, the convergence of hierarchical coordination is guaranteed. A grid computing structure in General Algebraic Modeling System (GAMS) to accelerate the computation is proposed. The generalized bid function is simulated for various test cases. We also demonstrate the effect of DERs on the voltage magnitude and phase angle. The numerical results show that the hierarchical coordination using the generalized bid function converges to very close results compared with the results of centralized dispatch. Hierarchical coordination is capable of managing various network congestion scenarios and power loads. The generalized bid function provides a unified format of communication between TSO and DSO. [ABSTRACT FROM AUTHOR]

Energy simulation tools have a major role in the assessment of building energy retrofit (BER) measures. Exergoeconomic analysis and optimisation is a common practice in sectors such as the power generation and chemical processes, aiding engineers to obtain more energy-efficient and cost-effective energy systems designs. ExRET-Opt, a retrofit-oriented modular-based dynamic simulation framework has been developed by embedding a comprehensive exergy/exergoeconomic calculation method into a typical open-source building energy simulation tool (EnergyPlus). The aim of this paper is to show the decomposition of ExRET-Opt by presenting modules, submodules and subroutines used for the framework’s development as well as verify the outputs with existing research data. In addition, the possibility to perform multi-objective optimisation analysis based on genetic-algorithms combined with multi-criteria decision making methods was included within the simulation framework. This addition could potentiate BER design teams to perform quick exergy/exergoeconomic optimisation, in order to find opportunities for thermodynamic improvements along the building’s active and passive energy systems. The enhanced simulation framework is tested using a primary school building as a case study. Results demonstrate that the proposed simulation framework provide users with thermodynamic efficient and cost-effective designs, even under tight thermodynamic and economic constraints, suggesting its use in everyday BER practice. [ABSTRACT FROM AUTHOR]

The electric engine cooling system, where the coolant pump and the radiator fan are driven by electric motors, admits advanced control methods to decrease auxiliary energy consumption. Recent publications show the fuel saving potential of optimal control strategies for the electric cooling system through offline simulations. These strategies often assume full knowledge of the drive cycle and compute the optimal control sequence by expensive global optimization methods. In reality, the full drive cycle is unknown during driving and global optimization not directly applicable on resource-constrained truck electronic control units. This paper reports state-of-the-art engineering achievements of exploiting vehicular onboard prediction for a limited time horizon and minimizing the auxiliary energy consumption of the electric cooling system through real-time optimization. The prediction and optimization are integrated into a model predictive controller (MPC), which is implemented on a dSPACE MicroAutoBox and tested on a truck on a public road. Systematic simulations show that the new method reduces fuel consumption of a 40-tonne truck by 0.36% and a 60-tonne truck by 0.69% in a real drive cycle compared to a base-line controller. The reductions on auxiliary fuel consumption for the 40-tonne and 60-tonne trucks are about 26% and 38%, respectively. Truck experiments validate the consistency between simulations and experiments and confirm the real-time feasibility of the MPC controller. [ABSTRACT FROM AUTHOR]

Energy management strategy is crucial in improving the fuel economy of hybrid electric vehicles (HEVs). This paper targets at evaluating the role of velocity forecast in the adaptive equivalent consumption minimization strategies (ECMS) for HEVs. A neural network based velocity predictor is constructed to forecast the short-term future driving behaviors by learning from history data. Then the velocity predictor is combined with adaptive-ECMS to provide temporary driving information for real-time equivalence factor (EF) adaptation. Compared with traditional adaptive-ECMS, which uses historical driving profile for EF estimation, the proposed strategy is able to foresee the change of the driving behaviors and adjust the EF more reasonably. Simulation results show that, compared with traditional adaptive-ECMS, the proposed improvement with velocity forecast incorporated is able to achieve better fuel economy and more stable battery state of charge (SOC) trajectory, with a fuel consumption reduction by over 3%. [ABSTRACT FROM AUTHOR]

In this paper, a multi-objective optimization model for the investment planning and operation management of distributed heat and electricity supply systems is presented. Different energy efficiency measures and supply options are taken into account, including various distributed heat and power generation units, storage systems and energy-saving renovation measures. Furthermore, district heating networks are considered as an alternative to conventional, individual heat supply for each building. The optimization problem is decomposed into three subproblems to reduce the computational complexity. This enables a high level of detail in the optimization and simultaneously the comprehensive investigation of districts with more than 100 buildings. These capabilities distinguish the model from previous approaches in this field of research. The developed model is applied to a district in a medium-sized town in Germany in order to analyze the effects of different efficiency measures regarding total costs and emissions of CO 2 equivalents. Based on the Pareto efficient solutions, technologies and efficiency measures that can contribute most efficiently to reduce greenhouse gas emissions are identified. [ABSTRACT FROM AUTHOR]

This paper describes a novel design approach of the free piston Stirling engines (FPSEs) based on multiple-scale perturbation method. First, a comprehensive mathematical model for an FPSE possessing nonlinear springs is presented. Then, the method of multiple scales is used to obtain the steady-state response of the engine system. Thus, some useful analytical relationships to predict frequency, strokes of pistons, and phase angle, as well as output power and efficiency of the nonlinear FPSE, are presented. Furthermore, a systematic mathematical approach for estimating the gas temperatures within expansion and compression spaces of the FPSE is proposed based on the perturbation technique. Next, a simulation study is carried out to investigate how much the engine frequency, strokes of pistons, and phase angle of the FPSE are sensitive to the variation of gas temperature. Besides, the effect of changes in the engine design parameters such as mass and stiffness of the pistons on the output power of the FPSE is studied using simulation. Finally, a test engine is developed and experimented to verify the proposed design technique. It is found that the experimental results are in a good agreement with the simulation outcomes of the analytical model through which validity of the proposed design scheme is clearly demonstrated. [ABSTRACT FROM AUTHOR]

Direct carbon solid oxide fuel cell (DC-SOFC) is a promising energy conversion device for power generation using solid carbon fuel. In this paper, a 2D model is developed for a tubular DC-SOFC for CO and electricity co-generation. Parametric simulations are conducted to understand the physical/chemical processes in the DC-SOFC. Good performance of DC-SOFC is observed even at a large distance between the carbon bed and the porous anode, indicating the feasibility of large-scale DC-SOFC applications. The DC-SOFC performance is found to decrease with decreasing temperature due to the decreased Boudouard reaction kinetics. It’s also found that the molar fraction of CO at the anode can be well controlled by adjusting the operating conditions, enabling DC-SOFC for electricity and CO cogeneration. Another finding is that the current density in the DC-SOFC increases slightly along the cell length, which is different from the H 2 -fueled SOFC. In addition, the anode-supported configuration is found to be beneficial in improving the electrical output of the DC-SOFC but is unfavorable for CO generation. A small D ce and a high potential are recommended to improve CO generation from the DC-SOFC. The model can be used for design optimization of DC-SOFC at a system level. [ABSTRACT FROM AUTHOR]

A computer simulation model of an integrated solar-hydrogen combined heat and power system with solar-thermal collectors (SH CHP-ST) is developed in TRNSYS to supply both power and heat (i.e. hot water demand) for a standalone application. The model is applied to a case study of a remote household in southeast Australia with conservative loads. Two possible configurations of the integrated system are studied and the optimal one is selected. The simulation results show that the system (i.e. designed to meet the full power demand) with the adopted configuration can supply 95% of the annual hot water demand, with more than 90% of this demand met in winter compared to 54% met from the collectors of the solar-thermal (ST) only. The fuel cell heat that is transferred for utilisation is evaluated in this integration along with that of the solar collectors. An important aspect about the heat matching capability of the fuel cell with the un-supplied demand from the ST throughout the year is concluded. This presents an advantageous characteristic of this integration and permits the system to be effectively used to supply full power and almost the entire hot water demand in the standalone remote domestic case (i.e. in southeast Australia) studied in this paper. [ABSTRACT FROM AUTHOR]

This paper presents a parameter extraction technique for the five-parameter solar-cell model. It only requires the priori knowledge of three load points: the open circuit, the short circuit, and the maximum power points. An intrinsic property of solar cells helps to construct an extra equation. A cost function is formulated with another intrinsic property. A search algorithm for minimizing the cost function is proposed. The best set of parameters is revealed at the end of searching. Two load scanning experiments are performed on two different solar panels. The simulated I – V curves, produced with the obtained parameters, match the empirical measured results nicely. When compared to other existing techniques, our proposed method usually yields less mean absolute error. [ABSTRACT FROM AUTHOR]

Researchers have begun developing simulation models as a cost-effective and expeditious means to explore and enhance our understanding of energy use behavior interventions. These models have provided unique insights into potential energy savings as a result of improved occupant behavior, but have not yet reached the capability to be used for predictive modeling purposes. Therefore, this paper attempts to build on previous modeling efforts and develops an empirically and conceptually grounded occupant behavior model for simulating normative feedback interventions based on literature from the social science and field data. This model is then used to conduct “what if” analyses testing three novel normative feedback intervention strategies and the effect of social network structure on intervention outcomes. The most successful and immediately applicable strategy consists of sending normative feedback only to individuals who use more energy than the group norm. This strategy resulted in a mean energy use reduction of 1.4 kW h per week per occupant, 2.2%, relative to traditional individual and normative feedback strategies used today. Lastly, it was found that the social network structure in which the interventions took place affected the absolute outcomes (i.e., net change) of the simulations but not the relative outcomes (i.e., strategy ranking). [ABSTRACT FROM AUTHOR]

• Compact shifted-frequency analysis models transferred readily from the time-domain models. • Flexible simulation model switching method that accelerates the multi-timescale simulations. • Flexible discontinuity treatment that exploits inherent phase information of the shifted-frequency analysis provides high accuracy during the discontinuities. The growing proportion of distributed generators in active distribution networks highlights the importance of multi-timescale system dynamics. The electromagnetic transient simulators with detailed modeling have been widely used for high-fidelity simulations, which leads to a contradiction between the efficiency and accuracy in the studies of the multi-timescale property of the ADNs. The shifted-frequency analysis method integrated with state-space based exponential integration is introduced in this paper, which possesses both high accuracy of exponential integration and the advantage of system-level modeling. It accurately simulates the networks considering the nonlinearities with the advantage that allows large time-steps in the simulations wherein the signals have a small bandwidth around the fundamental frequency. A model-switching method based on the integral transformation of the shifted-frequency models is designed to address the inefficiency of multi-timescale simulations. In addition, a flexible discontinuity treatment in the shifted-frequency domain is introduced for the reduction of the errors brought by the detections and interpolations of discontinuities in the time-domain. Numerical studies are conducted considering the distributed generations, the shifted-frequency models are generated integrally from the original time-domain models. The results of the multi-timescale simulations with model-switching in different domains show the high efficiency of the proposed method, and the discontinuity treatment presents higher accuracy compared with the time-domain solution. Those combined advantages compose the flexible shifted-frequency analysis for the multi-timescale simulations of active distribution networks. [ABSTRACT FROM AUTHOR]

In this paper an empirical capacity fade model for Li-ion batteries has been developed, calibrated and validated for a NCA/C and a LFP/C Li-ion cell. Based on extensive experimental work, this original, generic model is well suited for system simulation approaches, and is able to describe both cycle and calendar effects on aging. The stress factors taken into account for each aging mode are the state of charge and the temperature for calendar aging, and the temperature and the current for cycle aging. A simple approach has been adopted in order to instantaneously apply either cycle aging or calendar aging according to operating conditions and thus accurately model aging effects due to dynamic operating conditions. This model has then been coupled to an electrothermal model and integrated in a system simulation software application in order to assess the effect of charging rates, charging strategies and V2G on battery lifetime. When compared, the two battery chemistries exhibited different behaviors when submitted to V2G scenarios. Light V2G scenarios caused relatively low aging for the LFP/C based battery but tended to slightly increase the aging of the NCA/C based battery according to simulations. [ABSTRACT FROM AUTHOR]

Various process utilities are used in the petrochemical industry as auxiliary variables to facilitate the addition/removal of energy to/from the process, power process equipment and inhibit unwanted reaction. Optimisation activities usually focus on the process itself or on the utility consumption though the generation and distribution of these utilities are often overlooked in this regard. Many utilities are prepared or generated far from the process plant and have to be transported or transmitted, giving rise to more losses and potential inefficiencies. To illustrate the potential benefit of utility optimisation, this paper explores the control of a dual circuit cooling water system with focus on energy reduction subject process constraints. This is accomplished through the development of an advanced regulatory control (ARC) and switching strategy which does not require the development of a system model, only rudimentary knowledge of the behaviour of the process and system constraints. The novelty of this manuscript lies in the fact that it demonstrates that significant energy savings can be obtained by applying ARC to a process utility containing both discrete and continuous dynamics. Furthermore, the proposed ARC strategy does not require a plant model, uses only existing plant equipment, and can be implemented on control system hardware commonly used in industry. The simulation results indicate energy saving potential in the region of 30% on the system under investigation. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient methodology for the simulation-based multi-objective optimization problems, which addresses important limitations for the optimization of the building energy performance. In this work, a mono- and multi-objective particle swarm optimization (MOPSO) algorithm is coupled with EnergyPlus building energy simulation software to find a set of non-dominated solutions to enhance the building energy performance. To evaluate the capability and effectiveness of the approach, the developed method is applied to a single room model, and the effect of building architectural parameters including, the building orientation, the shading overhang specifications, the window size, and the glazing and the wall material properties on the building energy consumption are studied in four major climatic regions of Iran. In the optimization section, mono-criterion and multi-criteria optimization analyses of the annual cooling, heating, and lighting electricity consumption are examined to understand interactions between the objective functions and to minimize the annual total building energy demand. The achieved optimum solutions from the multi-objective optimization process are also reported as Pareto optimal fronts. Finally, the result of multi-criteria minimization is compared with the mono-criterion ones. The results of the triple-objective optimization problem point out that for our typical model, the annual cooling electricity decreases about 19.8–33.3%; while the annual heating and lighting ones increase 1.7–4.8% and 0.5–2.6%, respectively, in comparison to the baseline model for four diverse climatic regions of Iran. In addition, the optimum design leads to 1.6–11.3% diminution of the total annual building electricity demand. The proposed optimization method shows a powerful and useful tool that can save time while searching for the optimal solutions with conflicting objective functions; therefore facilitate decision making in early phases of a building design in order to enhance its energy efficiency. [ABSTRACT FROM AUTHOR]

This paper presents an efficient decomposition-based optimization method to optimize the hourly combined heat and power (CHP) production and power transmission between multiple areas. The combined production and power transmission problem is decomposed into local CHP production models and into a power transmission model. The CHP production models are formulated as linear programming (LP) models and solved using a parametric analysis technique to determine the local production cost as a function of power transmitted into or out from each area. To obtain the overall optimum, the power transmission problem is then formulated in terms of the parametric curves as a network flow problem, and solved using a special network Simplex algorithm. The decomposition method has been tested with different sized artificial problems. The method can be used in situations where it is necessary to solve a large number of hourly production and transmission problems efficiently. As an example, the method can be used as part of long-term planning and simulation of CHP systems in different cities or countries connected by a common power market. [ABSTRACT FROM AUTHOR]

Buildings today represent 40% of world primary energy consumption and 24% of greenhouse gas emissions. In our society there is growing interest in knowing precisely when and how energy consumption occurs. This means that consumption measurement and verification plans are well-advanced. International agencies such as Efficiency Valuation Organization (EVO) and International Performance Measurement and Verification Protocol (IPMVP) have developed methodologies to quantify savings. This paper presents a methodology to accurately perform automated envelope calibration under option D (calibrated simulation) of IPMVP – vol. 1. This is frequently ignored because of its complexity, despite being more flexible and accurate in assessing the energy performance of a building. A detailed baseline energy model is used, and by means of a metaheuristic technique achieves a highly reliable and accurate Building Energy Simulation (BES) model suitable for detailed analysis of saving strategies. In order to find this BES model a Genetic Algorithm (NSGA-II) is used, together with a highly efficient engine to stimulate the objective, thus permitting rapid achievement of the goal. The result is a BES model that broadly captures the heat dynamic behaviour of the building. The model amply fulfils the parameters demanded by ASHRAE and EVO under option D. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) is a promising, environmental friendly technique for its potential to reduce the using of fossil fuels. Massive EVs pose both opportunities and challenges for power systems, especially with the growing amount of wind-power integration. This paper investigates the problem of collaborative optimization scheduling of generators, EVs and wind power. A novel bi-layer optimization of transmission and distribution system is proposed to solve the scheduling problem of EVs charging and discharging load from respective time and space domain in the presence of wind-power. The upper layer optimization in transmission grid coordinates EVs with thermal generators, base load, with the consideration of wind power, to optimize load periods of EVs in the time domain. The lower layer optimization in distribution grid then spatially schedules the location of EVs load. Based on a power system benchmark with a 10-unit transmission grid and an IEEE 33-bus distribution grid, the performance of the proposed bi-layer optimization strategy is evaluated. The impacts of electricity price profile, EVs penetration and EVs load location are analyzed. Simulation results show that the proposed bi-layer optimization strategy can accommodate wind power and improve both the economics of grid operation and benefits of EV users by scheduling EVs charging and discharging temporally and spatially. Also, the results have shown that the location of EVs charging and discharging load is critical for the distribution network planning. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hydrogen production process by Methane Cracking thermally coupled with Chemical Looping Combustion (MC–CLC) which provides an advantage of inherent capture of CO 2 . The energy utilisation performance of the MC–CLC process is compared with that of conventional Methane Cracking with combusting CH 4 (MC-CH 4 ) and Methane Cracking with combusting H 2 (MC-H 2 ) using exergy analysis, with focus on exergy flows, destruction and efficiency. The three MC processes are simulated using Aspen Plus software with detailed heat integration. In these processes, the majority of the exergy destruction occurs in the combustors or CLC mostly due to the high irreversibility of combustion. The CO 2 capture unit has the lowest exergy efficiency in the MC-CH 4 process, leading to a lower overall exergy efficiency of the process. The combustor in the MC-H 2 process has a much higher energy efficiency than that in the MC-CH 4 process or the CLC in the MC–CLC process. Although the use of H 2 as fuel decreases the H 2 production rate, the MC-H 2 process provides the advantage of an absence of CO 2 generation, and stores more chemical exergy in the solid carbon which can be utilised appropriately. The MC–CLC process obtains the highest exergy efficiency among the three models and this is primarily due to the absence of a CO 2 capture penalty and the CLC’s higher fuel utilization efficiency than the conventional combustion process. [ABSTRACT FROM AUTHOR]