• Energy Research
• Restricted close
• Open Source close
• Embargo close
• NL close
• US close
• DE close
• CH close

The presented article will describe an 'effect-cause' model for the purpose of simulating the energy consumption of DC fed light rail vehicles. The model will assess the advantages of hybrid vehicles in terms of energy consumption, network power and voltage variations, line current and losses; and will help sizing and designing a supercapacitor based energy storage system (ESS) for both on-board, and stationary applications. The proposed modeling needs to allow the ESS sizing according to the objective that needs to be achieved, being braking energy recovery, voltage drop compensation and peak power shaving the most common goals of ESS use in hybrid vehicles. The needed power and energy levels will vary in function of the vehicle features and the driving cycle followed. This all can be determined by the quasi-static simulation tool to ease the design process. Another objective of the modeling tool is to evaluate the behaviour of the vehicle power flow controller, which manages the power from/to the ESS in function of the state of several variables.

Thermoacoustic technology emerges as a sustainable and low-carbon method for energy conversion, leveraging environmentally friendly working mediums and independence from electricity. This study presents the development of a multimode heat-driven thermoacoustic system designed to utilize medium/low-grade heat sources for room-temperature cooling and heating. We constructed both a simulation model and an experimental prototype for a single-unit direct-coupled thermoacoustic system, exploring its performance in heating-only, cooling-only, and hybrid heating and cooling modes. Internal characteristic analysis including an examination of internal exergy loss and a distribution analysis of key parameters was first conducted in the hybrid cooling and heating mode. The results indicated a positive-focused traveling-wave-dominant acoustic field within the thermoacoustic core unit, enhancing energy conversion efficiency. The output system performance was subsequently tested under different working conditions in the heating-only and cooling-only modes. A maximum output heating power of 2.3 kW and a maximum COPh of 1.41 were observed in the heating-only mode. Meanwhile, a cooling power of 748 W and a COPc of 0.4 were obtained in the typical cooling condition at 7 °C when operating in cooling-only mode. These findings underscore the promising potential of thermoacoustic systems for efficiently utilizing medium/low-grade heat sources for cooling and/or heating applications in the future.

It is well known that the efficiency of PV modules decreases with increasing module temperatures. Many studies have paid attention to the development and validation of heuristic models to calculate the PV module temperature in higher latitudes, however only a few focus on the thermal behaviour of PV modules in tropical regions of the world, where constantly high temperatures prevail. Also, little is known about the effect of including wind speed in these thermal models. This study evaluates three of such models - one that excludes wind, and two others including the wind influence - using hourly data for two tropical locations. Results show that the average hourly wind speeds in Singapore and Jayapura (Indonesia) are low and therefore the influence of the wind on the PV module temperature is minor. The three evaluated models produce about the same results with RMSE between 1.5-3.8 °C during daytime, which corresponds to a deviation in power output in the range of 0.3-1.6 %, depending on the PV module technology.

AbstractThe potential impacts of future climate scenarios on water balance and flow regime are presented and discussed for a temporary river system in southern Italy. Different climate projections for the future (2030–2059) and the recent conditions (1980–2009) were investigated. A hydrological model (Soil and Water Assessment Tool) was used to simulate water balance at the basin scale and streamflow in a number of river sections under various climate change scenarios, based on different combinations of global and regional models (global circulation models and regional climate models). The impact on water balance components was quantified at the basin and subbasin levels as deviation from the baseline (1980–2009), and the flow regime alteration under changing climate was estimated using a number of hydrological indicators. An increase in mean temperature for all months between 0.5–2.4 °C and a reduction in precipitation (by 4–7%) was predicted for the future. As a consequence, a decline of blue water (7–18%) and total water yield (11–28%) was estimated. Although the river type classification remains unvaried, the flow regime distinctly moves towards drier conditions and the divergence from the current status increases in future scenarios, especially for those reaches classified as I‐D (ie, intermittent‐dry) and E (ephemeral). Hydrological indicators showed a decrease in both high flow and low flow magnitudes for various time durations, an extension of the dry season and an exacerbation of extreme low flow conditions. A reduction of snowfall in the mountainous part of the basin and an increase in potential evapotranspiration was also estimated (4–4.4%). Finally, the paper analyses the implications of the climate change for river ecosystems and for River Basin Management Planning. The defined quantitative estimates of water balance alteration could support the identification of priorities that should be addressed in upcoming years to set water‐saving actions.

In this paper, we address the problem of determining the optimal day-ahead generation profile for a wind power producer by exploiting wind speed forecasts provided by a meteorological service. In the considered framework, the wind power producer is called to take part in the responsibility of system operation by providing day-ahead generation profiles and undergoing penalties in case of deviations from the schedule. Penalties are applied only if the delivered hourly energy deviates from the schedule more than a given relative tolerance. The optimal solution is obtained analytically by formulating and solving a stochastic optimization problem aiming at maximizing the expected profit. The proposed approach consists in exploiting wind speed forecasts to classify the next day into one of several predetermined classes, and then selecting the optimal solution derived for each class. The performance of the bidding strategy is demonstrated using real data from an Italian wind plant and weather forecasts provided by a commercial meteorological service.

North Sea fisheries are managed by the European Union (EU) through a system of annual quota. Due to uncertainty about future fish stocks, yearly revisions of these policies lead to fluctuation in quota, which in turn affects harvest and investment decisions of fishermen. Determination of quota requires high management costs in terms of obtaining information and negotiations between experts and policy makers. To reduce both quota fluctuation and management costs, the EU has proposed a system of multiannual quota. In this paper we study the effect of multiannual quota on quota volatility and resource rents, while accounting for management costs. We develop a bi-level stochastic dynamic programming model, where at level one, the EU determines the quota that maximizes resource rents. At level two, fishermen decide myopically on their harvest and investment levels, subject to the quota. Results show that policy makers can reduce quota volatility and improve resource rents from the fishery with multiannual quota. Important trade-offs are involved in the accomplishment of these objectives: fish stock and investments become more volatile, which leads to more overcapacity.

Saving energy in greenhouses is an important issue for growers. Here, we present a method to minimize the total energy that is required to heat and cool a greenhouse. Using this method, the grower can define bounds for temperature, humidity, CO2 concentration, and the maximum amount of CO2 available. Given these settings, optimal control techniques can be used to minimize energy input. To do this, an existing greenhouse climate model for temperature and humidity was expanded to include a CO2 balance. Heating, cooling, the amount of natural ventilation, and the injection of industrial CO2 were used as control variables.Standard optimization settings were defined in order to compare the grower's strategy with the optimal solution. This optimization resulted in a theoretical 47% reduction in heating, 15% reduction in cooling, and 10% reduction in CO2 injection for the year 2012. The optimal control does not need to maintain a minimum pipe temperature, in contrast to current practice. When the minimum pipe temperature strategy of the grower was implemented, heating and CO2 were reduced by 28% and 10% respectively.We also analyzed the effect of different bounds on optimal energy input. We found that as more freedom is given to the climate variables, the higher the potential energy savings. However, in practice the grower is in charge of defining the bounds. Thus, the potential energy savings critically depend on the choice of these bounds. This effect was analyzed by varying the bounds. However, because the effect can be demonstrated to the grower, the outcome has value to the grower with respect to decision making, an option that is not currently available in practice today.