The hazardous effects of pollutants from conventional fuel vehicles have caused the scientific world to move towards environmentally friendly energy sources. Though we have various renewable energy sources, the perfect one to use as an energy source for vehicles is hydrogen. Like electricity, hydrogen is an energy carrier that has the ability to deliver incredible amounts of energy. Onboard hydrogen storage in vehicles is an important factor that should be considered when designing fuel cell vehicles. In this study, a recent development in hydrogen fuel cell engines is reviewed to scrutinize the feasibility of using hydrogen as a major fuel in transportation systems. A fuel cell is an electrochemical device that can produce electricity by allowing chemical gases and oxidants as reactants. With anodes and electrolytes, the fuel cell splits the cation and the anion in the reactant to produce electricity. Fuel cells use reactants, which are not harmful to the environment and produce water as a product of the chemical reaction. As hydrogen is one of the most efficient energy carriers, the fuel cell can produce direct current (DC) power to run the electric car. By integrating a hydrogen fuel cell with batteries and the control system with strategies, one can produce a sustainable hybrid car.
Energy conservation is a concern in many commercial industries, and consequently facility operators are turning to various efficiency and alternative measures to reduce electricity costs. Growing use of intermittent resources, energy storage systems (ESSs) and demand side management (DSM) options are also gaining interest to maximize potential energy savings. Here we study the potential of ESSs versus DSM for water utilities through a case study of the National Energy Laboratory of the Hawaii Authority (NELHA). NELHA is a multizone water utility, where most electricity is dedicated to pumping water. In this study the optimization of the NELHA's overall electricity charges, using both ESSs or DSM via pump load shifting and optimization of pump house output is investigated. Optimization is performed to determine the optimal size of the batteries considering the water demand and energy costs in each zone. An extended approach of considering the characteristics of individual pumps on each pump house in the optimization model is applied to provide insight to the proper optimization framework for selecting individual pumps depending on the current zonal load, given pump efficiencies and maximum flow rates from each pump. The outcome from mathematical models using general quadratic pump efficiency functions and a simplified linear version of pump efficiency is compared to determine the significance of this difference in modeling methodology. Additionally, the effect of increasing solar power on electricity purchased is analyzed. This work will help to establish the role of ESS and DSM in energy savings for water utility industry.
There is a growing interest in utilizing energy storage for behind-the-meter customers. Energy storage systems have many functions for behind-the-meter use such as energy time shifting, peak demand shaving, and backup power. However, demand side management of energy consuming systems can also provide similar energy shifting functionality often with a significantly lower upfront cost. Though energy storage systems and demand side management can both be applied, each option has strengths and weaknesses that can make the optimal selection of measures difficult in many cases. In this study, the tradeoff between energy storage and demand side management is investigated at the Hawaii Ocean Science and Technology (HOST) park of the Natural Energy Laboratory of Hawaii Authority (NELHA). The major energy consumption at the HOST park is for pumping the seawater that serves many functions at the park, including supplying temperature-controlled water for various agriculture applications and even building air conditioning measure. NELHA’s facilities are broken into two major load centers that are connected by the piping network, though they are electrically isolated and subject to different electricity price tariffs. This scenario is modeled to optimize the dispatch of the pump stations and potential battery systems to minimize the cost of electricity for both load centers. This scenario is a good example of the interplay between demand side management and energy-storage-based cost reduction measures.
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