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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]

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]

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]

Abstract: The paper analyses the issues for consideration listed in the stock taking document “New Energy Strategy for Europe 2011–2020” and explores the impact of their implementation on the use of renewable energy sources. The main objective of the paper is to introduce and provide a summary of the theoretical and methodological achievements required for an analysis of the implications of such an EU level strategy. It also provides a summary of the results of the analysis of the impacts of the Strategy on a specific field; namely, on the use of renewable energy sources. Contradictions inherent in the Strategy are discussed as well, and a proposal is put forward to aid the resolution of these contradictions. The paper also points out that the further development of the theoretical and methodological achievements may result in the creation of a simulation model, the application of which could effectively aid the process of strategic planning and the testing of strategies prior to approval. Finally, the paper discusses how an EU level and/or a global network of energy security centres could promote the development and implementation of an energy policy ensuring the appropriate utilization of renewable energy sources. [Copyright &y& Elsevier]

Abstract: This paper proposes a novel and fast sizing method under the constant daily load profile for sizing a stand-alone PV system. The term “efficient sizing” means that the approach did not use simulation but could get the result as good as those employing simulation. So, the sizing method is more efficient than the others. Traditionally, a typical day or a typical year’s solar irradiation profile is employed for the sizing task. However, facing the global warming crisis as well as the fact that no 2years would have the same weather condition for a single site, this approach statistically models the trend of climate change year by year and put it into the sizing formula, so that the results are optimal for the current weather condition and for the future as well. Hence, the suitable size for the PV array and the number of batteries are obtained by purely computation. This is different from the traditional sizing curve method. Although the traditional sizing curve method were satisfactory in the normal cases, they might fail in the extreme climate condition. This paper concludes the behavior of the extreme climate for at least 20years. So, the derived system may have statistical confidence for at least 20years of operation. A new reliability index (Loss of Power Probability) in terms of Extreme Value Theory is introduced. LPP provides upper bound reliability for application and rich information for many extreme events. A technological and economical comparison among the traditional daily energy balance method, sizing curve method and this approach is conducted and shows the usefulness of this approach. [Copyright &y& Elsevier]

Abstract: This paper investigates the technical and economic potential of energy-intensive industries to provide demand-side management (DSM) in electricity and balancing markets through 2030. Increasing shares of renewables will lead to a rising demand for ancillary services at the same time that less conventional plants will be available to provide these services. This paper makes projections on the extent to which DSM from industrial processes can provide economic benefits in electricity markets with renewables by providing tertiary reserve capacity. Different industrial processes and their specific technical and economic properties are investigated and compared with other storage devices and electricity generation technologies. Based on an extension of an existing European electricity market model, simulations are used here to make long-term forecasts for market prices, dispatch and investments in the electricity markets through linear optimization. [ABSTRACT FROM AUTHOR]

This work describes and evaluates a new simulation model for direct steam generation in parabolic-trough solar collectors. In direct steam generation, water is heated and evaporated through a solar field to feed a steam Rankine cycle or an industrial process. However, the behaviour of the involved multiphase fluid poses some challenges to simulation models. The model explained in this work is based on a steady-state approach but deals with transient conditions such as start-up, shutdown and clouds in a reasonable computing time. A new simulation tool is implemented in the TRNSYS software environment by means of new components that are suitable to be integrated into a whole solar plant model in order to carry out long-term energy production analyses with low computational resources. The main advantages of the new quasi-dynamic approach include fast computation with satisfactory accuracy; consideration of thermal inertia when addressing transient conditions; and flexibility to use different types of collector or solar field configurations. The performance of the model is validated with real experimental data obtained from the DISS solar test loop in Plataforma Solar de Almería, Spain. This paper describes the modelling approach and summarizes the comparison of simulation results with measurements taken at the DISS facility. [ABSTRACT FROM AUTHOR]

Efforts to meet climate change mitigation and energy security targets spur investments in variable renewable energy sources. Their implications for the operation of power plants are frequently investigated drawing on unit commitment and dispatch models. However, the temporal granularity and operational detail these models consider is commonly omitted in the broader family of long-term energy system models. To compensate this short-coming, these two types of tools have sometimes been ‘soft-linked’ and harmonised for limited simulation years. This paper assesses an alternative approach. We examine an extended version of an open source energy system model (OSeMOSYS), which is able to capture operating reserve and related investment requirements within a single tool. The implications of these model extensions are quantified through comparison with an Irish case study. That case study examined the effects of linking a long-term energy system model (TIMES) with a unit commitment and dispatch model (PLEXOS). It analysed the year 2020 in detail, applying a yearly temporal resolution that is over 700 times higher than in OSeMOSYS. Without increasing temporal resolution (and computational burden) we show that results of the enhanced OSeMOSYS model converge to results of TIMES and PLEXOS: Investment mismatches decrease from 21.4% to 5.0%. The OSeMOSYS analysis was then extended to 2050 to assess the implications of short-term variability on future capacity investment decisions. When variability was ignored, power system investments in 2050 were found to be 14.3% lower. This might imply that energy policies derived from such long-term models – of which there are many – may underestimate the costs of introducing variable renewables and thus meeting climate change or energy security targets. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes a method to characterize the fluctuating electricity generation of renewable energy sources (RESs) in a power system and compares the different parameters for California and Germany. Based on this method describing the fluctuation and residual load, the potential contribution of grid-connected vehicles to balancing generation from renewable energy sources is analyzed for a 2030 scenario using the agent-based simulation model PowerACE. The analysis reveals that integrating fluctuating RES is possible with less effort in California because of a higher correlation between RES generation and the load curve here. In addition, RES capacity factors are higher for California and therefore the ratio of installed capacity to peak load is lower. Germany, on the other hand, faces extreme residual load changes between periods with and without supply from RES. In both power system scenarios, grid-connected vehicles play an important role in reducing residual load fluctuation if smart charging is used. Uncontrolled charging or static time-of-use tariffs do not significantly improve the grid integration of RES. [Copyright &y& Elsevier]

Abstract: Increasing levels of intermittent renewables, especially wind power, in energy systems require accurate temporal characterisation of the resources’ availability at seasonal, daily and hourly scales. This is crucial for isolated energy systems, where increasing wind power penetration is limited due to costly backup power generation requirements. In the case studies presented in this paper, the energy systems of two islands are simulated using a new methodology for synthetic wind speed scenarios including daily wind patterns. A trade-off analysis was conducted in terms of surplus wind power and renewables penetration rate, with the objective of supplying decision support on wind turbine placement. Results show that there may be a significant advantage in locating future wind parks on sites where wind speed patterns better match electricity demand patters, rather than just choosing a site with the highest mean wind speed, but only if the annual mean wind speed is still sufficiently high to make the investment economically feasible. [Copyright &y& Elsevier]

Abstract: Two of the most significant challenges in the 21st century will be to improve energy security and reduce the greenhouse gas emissions associated with energy consumption. A co-beneficial solution to these challenges is seen as increasing the use of renewable energy for the production of electricity. Some renewable sources, such as wind are often presented as a way to reduce greenhouse gas emissions; however, since wind’s variability increases uncertainty and risk in expected generation, it can be detrimental to energy security. One of the ways in which wind’s contribution to a jurisdiction’s energy security and greenhouse gas reduction strategies can be improved is to employ a forecasting method that can help reduce risks. This paper proposes a method that applies risk and reliability analysis techniques to obtain the most-likely RL (Resistance–Load) scenario using a set of historical data for wind-supply or generation and load. RL estimates the reliability of a wind-energy system by simulating an anticipated resistance (the electrical generation) attempting to meet a load (the electricity demand) for a future year. The method is demonstrated through a case study and its results are compared with real-time data from a 12MW wind farm to prove its efficacy. [Copyright &y& Elsevier]

Abstract: Organic Rankine Cycles (ORCs) are particularly suitable for recovering energy from low-grade heat sources. This paper describes the behavior of a small-scale ORC used to recover energy from a variable flow rate and temperature waste heat source. A traditional static model is unable to predict transient behavior in a cycle with a varying thermal source, whereas this capability is essential for simulating an appropriate cycle control strategy during part-load operation and start and stop procedures. A dynamic model of the ORC is therefore proposed focusing specifically on the time-varying performance of the heat exchangers, the dynamics of the other components being of minor importance. Three different control strategies are proposed and compared. The simulation results show that a model predictive control strategy based on the steady-state optimization of the cycle under various conditions is the one showing the best results. [Copyright &y& Elsevier]

Abstract: This paper presents the analysis and comparison of the main active techniques for islanding detection used in grid-connected microinverters for power processing of renewable energy sources. These techniques can be classified into two classes: techniques introducing positive feedback in the control of the inverter and techniques based on harmonics injection. Accurate PSIMTM simulations have been carried out in order to perform a comparative analysis of the techniques under study and to establish their advantages and disadvantages according to IEEE standards. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, modeling, analysis, design, simulation and control of a single ended primary inductor converter (SEPIC) are discussed for renewable energy applications. Because the traditional control methods such as proportional–integral–derivative (PID) and classical half-cycle Posicast controllers based on feedforward are sensitive to noise and variations in natural frequency, a Posicast control with feedback structure is proposed and designed to reduce or rejection undesirable sensitivity greatly, to suppress measurement noise and to eliminate the overshoot in the output response. The SEPIC converter is modeled using average value modeling analysis. Dynamic modeling and simulation are accomplished using MATLAB Simulink™ 7.2. [Copyright &y& Elsevier]

Abstract: Over eight million hectares of olive trees are cultivated worldwide, especially in Mediterranean countries, where more than 97% of the world’s olive oil is produced. The three major olive oil producers worldwide are Spain, Italy, and Greece. Olive tree pruning residues are an autochthonous and important renewable source that, in most of cases, farmers burn through an uncontrolled manner. Besides, industrial uses have not yet been developed. The aim of this paper consists of a new calculation tool based on particles swarm (Binary Honey Bee Foraging, BHBF). Effectively, this approach will make possible to determine the optimal location, biomass supply area and power plant size that offer the best profitability for investor. Moreover, it prevents the accurate method (not feasible from computational viewpoint). In this work, Profitability Index (PI) is set as the fitness function for the BHBF approach. Results are compared with other evolutionary optimization algorithms such as Binary Particle Swarm Optimization (BPSO), and Genetic Algorithms (GA). All the experiments have shown that the optimal plant size is 2MW, PI =3.3122, the best location corresponds to coordinate: X =49, Y =97 and biomass supply area is 161.33km2. The simulation times have been reduced to the ninth of time than the greedy (accurate) solution. Matlab® is used to run all simulations. [Copyright &y& Elsevier]