The Impact of HVAC on the Development of Autonomous and Electric Vehicle Concepts

Automation and electrification are changing vehicles and mobility. Whereas electrification is mainly changing the powertrain, automation enables the rethinking of the vehicle and its applications. The actual driving range is an important requirement for the design of automated and electric vehicles, especially if they are part of a fleet. To size the battery accordingly, not only the consumption of the powertrain has to be estimated, but also that of the auxiliary users. Heating Ventilation and Air Conditioning (HVAC) is one of the biggest auxiliary consumers. Thus, a variable HVAC model for vehicles with electric powertrain was developed to estimate the consumption depending on vehicle size and weather scenario. After integrating the model into a tool for autonomous and electric vehicle concept development, various vehicle concepts were simulated in different weather scenarios and driving cycles with the HVAC consumption considered for battery sizing. The results indicate that the battery must be resized significantly depending on the weather scenario to achieve the same driving ranges. Furthermore, the percentage of HVAC consumption is in some cases higher than that of the powertrain for urban driving cycles, due to lower average speeds. Thus, the HVAC and its energy demand should especially be considered in the development of autonomous and electric vehicles that are primarily used in cities.

Towards supporting prescribed fire management decisions in the Cabreira Mountain, Portugal

<p>The importance of implementing preventive fuel reduction strategies to build wildfire resilient landscapes has been increasingly present in the Portuguese politicians’ agenda. Science-based information is crucial to guide decision-makers, to better allocate resources, to decrease the projected increasing impacts of large wildfires following climate change, and to ensure the sustainability of environmental resources. Currently, fuel management is implemented without prior evaluation of wildfire exposure or optimization of strategic location of landscape treatments units, impairing a greater reduction in wildfire hazard and losses.</p><p>Prescribed burning can be used to create spatial fuel discontinuities in the landscape thus, to mitigate wildfire impacts. This study proposes to evaluate wildfire exposure in a large and diverse fire-prone area (~193 000ha) containing the Cabreira Mountain, located in Northwestern Portugal.  The main goal is to locate vegetation patches where fuel management can decrease landscape connectivity, fire spread (ROS) and fireline intensity (FLI), simultaneously reducing wildfire burn probability (BP). To address this, we run simulations using the FlamMap MTT fire spread model and quantify landscape connectivity using indexes from the graph theory, under different weather scenarios. Input data on fuels and topography were assembled in a binary landscape file at 100m spatial resolution.</p><p>Fire regime analysis was done for burned areas larger than 100 ha, from 2001 to 2019. Using the national fire ignition database and satellite data, the dates of active fire progression and fire durations are calculated. Daily weather variables (temperature, relative humidity, wind speed and direction) corresponding to those dates are compiled. To calibrate the fire model, we compare the observed and the estimated distributions of fire sizes, and the observed fire frequency with the estimated BP. A hierarchical clustering analysis identified three historical weather scenarios. Besides these a 95<sup>th</sup> percentile extreme weather scenario is also defined.</p><p>Results show a strong relationship between wind speed and landscape connectivity. The contribution of old, burned Pine stands and shrubland areas, mainly located at the east part of the Cabreira Mountain, is high for the overall landscape connectivity. For the extreme weather scenario, assessment of the impact of different fuel treatment extents (Treatment Optimization Model), from 5 to 30%, on the landscape connectivity and on the decrease of the FLI values showed that with a 20% of fuel treatment area (~39 000ha): 1) landscape connectivity decreases 85%; 2) the proportion of the two most extreme FLI classes decreases to ~10% within the study area.</p><p>Based on the results, we discuss the best strategies to reduce wildfire hazard for multi criteria based on the studied fire regime and under different weather scenarios, providing information to support a fire management plan. This study explores the potential of fire spread models and graph theory to assess wildfire landscape connectivity and to identify the landcover patches that mostly contribute to that, to determine optimal landscape treatment proportion and to evaluate the impact of treatment locations on the decrease of wildfire properties, ultimately leading to a more comprehensive and effective wildfire management strategy.</p>

Studi Kapasitas Daya Pembangkit Listrik Tenaga Hibrida Angin dan Surya Berkapasitas 6 kW berdasarkan Skenario Cuaca

ABSTRAKPembangkit listrik tenaga hibrida angin dan surya adalah suatu pembangkit listrik yang menggunakan gabungan antara tenaga angin dan tenaga sinar matahari. Penelitian dilakukan dengan metode probabilitas distribusi normal terhadap kecepatan angin dan radiasi matahari yaitu terjadinya kecepatan angin lebih dari 3,73 m/s adalah berpeluang sebesar 78,81% dan terjadinya radiasi matahari lebih dari 0,397 kW/m2 berpeluang sebesar 92,79%. Kemudian dirancang dua desain pembangkit listrik tenaga angin dan surya berdasarkan nilai investasi dan keandalan, yaitu desain pertama terdiri dari satu unit turbin angin horizontal berkapasitas 3 kW dengan panel surya berkapasitas 3 kW sedangkan desain kedua terdiri dari satu unit turbin angin horizontal berkapasitas 4 kW dengan panel surya berkapasitas 2 kW, selanjutnya dilakukan beberapa skenario cuaca antara lain saat radiasi matahari 0,439 kW/m2 dengan probabilitas 78,23% dan saat panel surya tidak dapat menghasilkan daya dikarenakan tidak adanya sinar matahari. Desain pembangkit kedua memiliki keandalan dan nilai investasi lebih kecil yaitu Rp 119.591.000 dibandingkan desain pertama.Kata kunci: hibrida, metode probabilitas, investasi, keandalan, skenario cuacaABSTRACTA wind and solar hybrid power plant is a power plant that uses a combination of wind power and solar. The research was done by probability method of normal distribution to wind speed and solar radiation that was wind velocity more than 3.73 m/s as a probability equal to 78.81% and the occurrence of solar radiation more than 0.397 kW/m2 had a chance equal to 92.79%. Further more, design of the two wind and solar power plant based on the investment and reliability, the first design consisted of 3 kW horizontal axis wind turbine unit with 3 kW solar panel while the second design consisted of 4 kW horizontal axis wind turbine unit with the solar panel 2 kW capacity. Further more, it was conducted some weather scenarios when the occurrence of solar radiation more than 0.439 kW/m2 had a chance equal to 78.23% and the solar panel could not produced power because of the absence of sun ray. The second design had reliability and lower investation value that is Rp 119.591.000 compared to the first design.Keywords: hybrid, probability method, investation, reliability, weather scenario

Modelling energy supply options for electricity generations in Tanzania

The current study applies an energy-system model to explore energy supply options in meeting Tanzania’s electricity demands projection from 2010 to 2040. Three economic scenarios namely; business as usual (BAU), low economic consumption scenario (LEC) and high economic growth scenario (HEC) were developed for modelling purposes. Moreover, the study develops a dry weather scenario to explore how the country’s electricity system would behave under dry weather conditions. The model results suggests: If projected final electricity demand increases as anticipated in BAU, LEC and HEC scenarios, the total installed capacity will expand at 9.05%, 8.46% and 9.8% respectively from the base value of 804.2MW. Correspondingly, the model results depict dominance of hydro, coal, natural gas and geothermal as least-cost energy supply options for electricity generation in all scenarios. The alternative dry weather scenario formulated to study electricity system behaviour under uncertain weather conditions suggested a shift of energy supply option to coal and natural gas (NG) dominance replacing hydro energy. The least cost optimization results further depict an insignificant contribution of renewable energy technologies in terms of solar thermal, wind and solar PV into the total generation shares. With that regard, the renewable energy penetration policy option (REPP), as an alternative scenario suggests the importance of policy options that favour renewable energy technologies inclusion in electricity generation. Sensitivity analysis on the discount rate to approximate the influence of discount rate on the future pattern of electricity generation capacity demonstrated that lower values favour wind and coal fired power plants, while higher values favour the NG technologies. Finally, the modelling results conclude the self-sufficiency of the country in generating future electricity using its own energy resources.