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Abstract This paper investigates the hydrodynamics of a seabed-mounted, bottom-hinged, flap-type wave energy converter in shallow water. A conceptual model of the hydrodynamics of the device has been formulated and shows that, as the motion of the flap is highly constrained, the magnitude of the wave force on the flap is the key determinant of power capture. The results from a physical modelling program have been used in conjunction with numerical data from WAMIT to validate the conceptual model. The work finds that designing the device to increase the wave force is more profitable than designing it to be tuned to the incident wave climate. As wave force is the primary driver of device performance it is shown that the flap should fill the water column and pierce the water surface to reduce decoupling due to wave overtopping. It is concluded that, in order to maximize capture factor at a typical North Atlantic site, the flap should be approximately 20–30 m wide, with large diameter rounded side edges, having its pivot close to the seabed and its top edge piercing the water surface.

Abstract In this paper, a strategy is proposed in order to introduce in a realistic way wind generation into a transmission power system non sequential Monte Carlo adequacy study with economic dispatch. Thanks to the implemented solution, wind generation is consequently confronted to operational constraints related to high powered thermal units, nuclear parks or thermal machines with technical minimum value. Moreover, during each simulated system state, a DC load flow is also calculated in order to evaluate reinforcements optimizing the large scale integration of wind power production. The simulation tool modified during the present work is called Scanner© and is the property of Tractebel Engineering (Gaz de France – Suez) company. It has been here applied to an academic test system: the Roy Billinton Test System (RBTS).

Although considered a current highlight, the concept of intelligent buildings (IB) has not been adopted as quickly and widely as expected. One of the reasons for this is the lack of information and knowledge support to all professionals involved at the design stage of a project. This paper provides a brief overview on the new advances of IB technologies and discusses ways of supplementing the decision making process by adopting two methods for economical and technical aspects of IB applications. It goes on to introduce an on-going research which aims to utilise knowledge based systems to provide comprehensive evaluations to alternatives and decision support to retrofit building projects, when they are being conceptualised.

Abstract An indirect forced convection and desiccant integrated solar dryer is designed and fabricated to investigate its performance under the hot and humid climatic conditions of Chennai, India. The system consists of a flat plate solar air collector, drying chamber and a desiccant unit. The desiccant unit is designed to hold 75 kg of CaCl2-based solid desiccant consisting of 60% bentonite, 10% calcium chloride, 20% vermiculite and 10% cement. Drying experiments have been performed for green peas at different air flow rate. The equilibrium moisture content Me is reached in 14 h at an air flow rate of 0.03 kg/m2 s. The system pickup efficiency, specific moisture extraction rate, dimensionless mass loss, mass shrinkage ratio and drying rate are discussed in this paper.

Abstract Reliability analysis of IESs (Integrated Energy System) is complicated because of the complexity of system topology and dynamics and different kinds of uncertainties. Reliability is often calculated based on statistic methods, which always focus on historical performances and neglect the importance of their dynamics and structure. To overcome this problem, in this paper, a systematic framework for dynamically analysing the real-time reliability of IESs is proposed by integrating different machine learning methods and statistics. Firstly, the bootstrap-based Extreme Learning Machine is developed to forecast the conditional probability distributions of the productions of renewable energies and the energy consumptions. Then, the dynamic behaviour of IESs is simulated based on a stacked auto-encoder model, instead of using traditional mechanism-based simulation models, for improving computational efficiency. Besides, the variables representing the transient properties of natural gas pipeline networks, such as delivery pressures and flow rates, are taken as the indicators for quantifying the energy supply security in natural gas pipeline networks. The time-dependent relationships among these indicators and their statistic correlations are modelled for improving the effectiveness of the analysis results. Finally, the reliability assessment is performed by estimating the probability distribution of each functional state of the target IES. A case study of a realistic bi-directional IES is carried out to demonstrate the effectiveness of the proposed method. The results show that the method is able to effectively evaluate the reliability of IESs, which can provide useful information for system operation and management.

Abstract This paper focuses on the formulation, fabrication and characterization of a novel composite for high-temperature heat energy storage. The proposed composite is a shape-stable phase change material consisting of the eutectic chloride (MgCl2–NaCl–KCl) as phase change material, expanded graphite (EG) for heat conduction enhancement and shape stability, and SiO2 nanoparticles for the further improvement of specific heat and thermal conductivity. The composite was prepared following a three-step procedure: mechanical dispersion, tableting and sintering. Concerning the material characterization, a suite of techniques were used, including simultaneous thermal analysis (STA) and laser flash analysis (LFA). The consequences demonstrate that using EG and SiO2 nanoparticles ensure the stability and preventing the leakage of the eutectic chloride. A thorough comparison with the pure ternary chloride shows that the composite specific heat increased up to 1.36 times in solid-state and 1.63 times in liquid-state, and the thermal conductivity increased by 23.2 and 9.2 times in the solid and liquid state, respectively. Upon inspection with scanning electron microscopy, a high-density nanostructure was observed and distributed evenly in the pores of EG, which appear to be the reason for the enhancement of specific heat and thermal conductivity of the material. Finally, the nano-SiO2/MgCl2–NaCl–KCl/EG composite has the advantages of wide working temperature range, shape stability, high specific heat and thermal conductivity, which has a promising application in a high-temperature thermal storage system.

Access to a reliable source of electricity is a basic need for any community as it can improve the living standards characterized via the improvement of healthcare, education, and the local economy at large. There are two key factors to consider when assessing the appropriateness of a micro-grid system, the cost-effectiveness of the system and the quality of service. The tradeoff between cost and reliability of the system is a major compromise in designing hybrid systems. In this way, optimization of a Hybrid Micro-Grid System (HMGS) is investigated. A hybrid wind/PV system with battery storage and diesel generator is used for this purpose. The power management algorithm is applied to the load, and the Multi-Objective Particle Swarm Optimization (MOPSO) method is used to find the best configuration of the system and for sizing the components. A set of recent hourly wind speed data from three meteorological stations in Iran, namely: Nahavand, Rafsanjan, and Khash, are selected and tested for the optimization of HMGS. Despite design complexity of the aforementioned systems, the results show that the MOPSO optimization model produces appropriate sizing of the components for each location. It is also suggested that the use of HMGS can be considered as a good alternative to promote electrification projects and enhance energy access within remote Iranian areas or other developing countries enjoying the same or similar climatic conditions.

We compare two models to determine the size of grid units and dispatch in a wind-diesel power system with hydrogen storage. Both take as data 1-year time series of hourly wind speed and electricity demand, and their objective is to minimise cost. Our first model, based on linear programming, generates as output a combination of capacities and a year time series for the dispatch variables. Our second model runs a fixed dispatch rule over several capacity combinations and selects the cheapest option. The dispatch rule can then be improved through comparison with the linear programming solution. At present costs, the hydrogen storage-conversion system is excluded from the solutions, so the interesting operation rules associated with the option of harvesting do not arise. However, the costs of hydrogen storage technologies are decreasing with investment. By running our model with prospective costs for year 2010, we see storage emerge in the optimum, and thus a sample of the operation patterns that will occur in a renewable dominated grid.

Abstract Justifying continued development and large-scale deployment of Wave Energy Converters (WECs) requires quantification of the potential resource. Currently, estimates are available for individual countries or, at low accuracy, for global resource. Additionally, existing estimates do not provide insight into potential future markets, i.e. the location of the resource. Here, NOAA WaveWatch III data are analysed for a 6-year period to calculate wave energy potential. The global market is then quantified by calculating the energy flux across a line 30 nautical miles offshore. Results are presented by country, continent, hemisphere and for the globe. Confidence values are also presented in the form of 95% confidence intervals. These limits provide insight into the uncertainty associated with the length of dataset used and the variability of the resource. This enables direct comparison with other resource assessment studies, whether using numerical model or measured data. An extensive survey of previous global and regional resource estimates is also conducted, in order to compare both results and methods. Supplementing this, extractable resource is estimated by considering the deployment of an illustrative WEC (Pelamis P2). The global wave power resource is 2.11 ± 0.05 TW, of which 4.6% is extractable with the chosen WEC configuration.