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With the share of intermittent renewable energies within the electricity system rising, balancing services from dispatchable power plants are of increasing importance. Highlighting the importance of the need to keeping fuel costs for flexible power generation to a minimum, the study aims to identify favourable biogas plant configurations, supplying biogas on demand. A cost analysis of five configurations based on biogas storing and flexible biogas production concepts has been carried out. Results show that additional flexibility costs for a biogas supply of 8h per day range between 2€ and 11€MWh(-1) and for a 72h period without biogas demand from 9€ to 19€MWh(-1). While biogas storage concepts were identified as favourable short term supply configurations, flexible biogas production concepts profit from reduced storage requirements at plants with large biogas production capacities or for periods of several hours without biogas demand.

AbstractCurrent climate change impact studies on coffee have not considered impact on coffee typicities that depend on local microclimatic, topographic and soil characteristics. Thus, this study aims to provide a quantitative risk assessment of the impact of climate change on suitability of five premium specialty coffees in Ethiopia. We implement an ensemble model of three machine learning algorithms to predict current and future (2030s, 2050s, 2070s, and 2090s) suitability for each specialty coffee under four Shared Socio-economic Pathways (SSPs). Results show that the importance of variables determining coffee suitability in the combined model is different from those for specialty coffees despite the climatic factors remaining more important in determining suitability than topographic and soil variables. Our model predicts that 27% of the country is generally suitable for coffee, and of this area, only up to 30% is suitable for specialty coffees. The impact modelling showed that the combined model projects a net gain in coffee production suitability under climate change in general but losses in five out of the six modelled specialty coffee growing areas. We conclude that depending on drivers of suitability and projected impacts, climate change will significantly affect the Ethiopian speciality coffee sector and area-specific adaptation measures are required to build resilience.

AbstractThe main aim of this work is to explore the injector performance in terms of fuel mass flow rate and discharge coefficient when ethanol is in use with gasoline injectors at elevated temperatures. The operating fuel injection was at the pressures between 0.2 and 0.4MPa and the temperatures in a range of 40–80°C. A fuel injector test cell with electronic control for injection pulse, timing and pressure was set to 120Hz and 60min injection duration to drive three single-hole 0.34mm nozzle diameter injectors. The fuels were injected into a known volume flask at quiescence atmospheric pressure and weighed to attain the fuel mass flow rates. By this manner, the discharge coefficient can be calculated by the assumptions of quasi steady, incompressible and one dimensional flow through each injector. When operating at 40°C injection temperature, ethanol delivered greater fuel amounts than gasoline resulting in higher discharge coefficients. The temperatures of the injected fuels are shown to affect the fuel flow rates and the discharge coefficients.

This paper presents a new method to solve the constrained unit commitment problem by applying ant colony optimization (ACO) based on the diversity control approach. The pheromone updating rule is modified to control the diversification by adopting a simple mechanism for random selection in ACO. The proposed method is tested on the 10-unit test system with a scheduling time horizon of 24 hours. The numerical results show an economical saving in the total operating cost when compared to the previous literature results. Moreover, two types of the proposed diversity control technique have the features of easy implementation and a better convergence rate superior to a standard ACO.

One of the most critical risks for modern societies is a largescale power system blackout. Critical infrastructure has emergency power supplies (e.g., nuclear power plants, hospitals, or communication infrastructure) to confront power outage situations. However, after about 8 h of a blackout, fuel supplies and battery capacities normally run out. Thus, it is of utmost importance to restore the power system as robustly and quickly as possible. This responsibility lies with the transmission system operators (TS Os), and it is in their best interest to rapidly accomplish it.

Abstract Almost all available power and temperature models of photo voltaic (PV) panels can only predict the power output and the cell temperature under clean conditions. The objective of this research is to study the effect of dust accumulation on the solar cells temperature as well as to model the solar cells temperature and the power output from PV panels under dusty conditions. An experimental setup has been developed in this study, which consists of a PV panel that contains two thermocouples embedded inside the panel, in order to measure the cells' temperatures. The cells temperatures, solar irradiance received by the panel, and the power output from the panel have been measured for five consecutive weeks in Cairo, Egypt. The actual solar irradiance received by the cells, i.e., Gcell, was calculated using the power model of PV panels. Afterward, the cell temperature was calculated based on the cells temperature model and the actual solar irradiance received by the cells. It has been found that the difference between the measured and the calculated cell temperature was not more than 3.71% during the time of experiments. Therefore, it can be concluded that the influence of dust on the power output as well as the cell temperature can be calculated using the power model and the cell temperature model under clean conditions, but the solar irradiance in these models should be replaced by the actual solar irradiance received by the cells, i.e., Gcell.