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(Abstract) This paper proposes a new power line communication (PLC) architecture for monitoring and remote control of Distributed Generators (DG) and Energy Storage Systems (ESS) connected to low voltage distribution networks. The final aim is to improve the performance of the PLC link in terms of robustness and efficiency in devices addressing. The proposed solution is based on a concentrator, to be installed in secondary substation, and a new PLC bridge, to be linked both to inverters and interface protection systems of DGs or ESSs. In this way, a communication link is obtained between distribution system operator (DSO) and DG or ESS owners. The proposed system is able to provide advanced functions for the remote control of DGs and ESSs inverters, not only in terms of remote disconnection but also in terms of adjusting the inverter operating modes.

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.

AbstractClimate change effects along with anthropogenic activities present the main factors that threaten the existence of heritage sites across the north Nile Delta of Egypt close to the coastline of the Mediterranean Sea. Observing the changes in the landscape close to the archaeological sites is an important issue for decision‐makers in terms of reducing the negative impact of natural events and human activities. The coastal heritage sites are becoming strongly threatened by the rising sea level phenomena that will happen due to global warming. Focusing on the distribution of the archaeological sites, this study aims to detect the areas at risk of shoreline erosion or accretion in the northern shoreline of the Nile Delta. In this study, the changes in the northern shoreline of the Nile Delta were observed and calculated during the last hundred years based on the integration between the old topographic maps from surveys in 1900, 1925 and 1945, optical satellite images captured by Landsat in 1972, 1986 and 2000; Sentinel2 2021; and the Radar SRTM data. The results of this study showed that the changes were enormous with a great shoreline erosion process over the last 121 years recorded along the shoreline in the periods between 1900–1925, 1925–1945, 1945–1972, 1972–1986, 1986–2000 and 2000–2021. The areas eroded were about 5.3, 4.7, 5.6, 8.9, 2.5 and 5.4 km2, respectively. Such negative movements caused the loss of two heritage sites, and the expected changes will lead to the loss of additional heritage sites in the next 500 years. Furthermore, a model was suggested for protecting the coastal heritage sites threatened by the risk of submergence. This study can help the decision‐makers to detect the coastal archaeological sites at risk and create innovative solutions for protecting these irreplaceable heritage sites.

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.

Abstract In this paper, a medium-term load forecasting model is proposed, intended to be used for the extrapolation of loads containing a small proportion of air conditioners. The main feature of the proposed model is the decomposition of weekly load observations into two independent components: trend line and seasonal variations. The trend line is described by the combination of the polynomial regression and the first-order autoregressive model. The parameters of this model are estimated with the aid of the generalized least-squares method. The seasonal component is modeled via a discrete model, where the weather sensitive cycle is separated from the weather insensitive one. A linear regression model is further proposed in order to associate weather sensitive variations with the exogenous weather variable (temperature). This procedure enabled a simple and efficient convolution of all load components into a single forecasting model. The whole methodology is verified on a real-life example of the peak-load consumption within the power system of former Yugoslavia.

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.

The development of heat transfer fluids (HTF) and heat storage materials (HSM) is crucial to design concentrating solar plant (CSP). Binary alkaline nitrate mixtures are currently used as sensible thermal energy storage materials. However, multi-component nitrate/nitrite systems were proposed as possible better candidates. In particular, ternaries mixtures containing sodium, potassium, and calcium are extremely promising as thermal fluids, given their reduced toxicity and greater cost-effectiveness. Nevertheless, very few data are present in the scientific literature regarding the correspondent phase diagram, and only the properties of specific compositions are reported. For this reason, a regular solution model was developed and employed in this work, and validated by comparing the simulation results with experimentally obtained phase change values. In particular, given that the common calorimetric techniques are impracticable for detecting the transition temperatures of calcium containing nitrate mixtur...

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.