Electrochemical Hydrogen Production Powered by PV/CSP Hybrid Power Plants: A Modelling Approach for Cost Optimal System Design

Global trade of green hydrogen will probably become a vital factor in reaching climate neutrality. The sunbelt of the Earth has a great potential for large-scale hydrogen production. One promising pathway to solar hydrogen is to use economically priced electricity from photovoltaics (PV) for electrochemical water splitting. However, storing electricity with batteries is still expensive and without storage only a small operating capacity of electrolyser systems can be reached. Combining PV with concentrated solar power (CSP) and thermal energy storage (TES) seems a good pathway to reach more electrolyser full load hours and thereby lower levelized costs of hydrogen (LCOH). This work introduces an energy system model for finding cost-optimal designs of such PV/CSP hybrid hydrogen production plants based on a global optimization algorithm. The model includes an operational strategy which improves the interplay between PV and CSP part, allowing also to store PV surplus electricity as heat. An exemplary study for stand-alone hydrogen production with an alkaline electrolyser (AEL) system is carried out. Three different locations with different solar resources are considered, regarding the total installed costs (TIC) to obtain realistic LCOH values. The study shows that a combination of PV and CSP is an auspicious concept for large-scale solar hydrogen production, leading to lower costs than using one of the technologies on its own. For today’s PV and CSP costs, minimum levelized costs of hydrogen of 4.04 USD/kg were determined for a plant located in Ouarzazate (Morocco). Considering the foreseen decrease in PV and CSP costs until 2030, cuts the LCOH to 3.09 USD/kg while still a combination of PV and CSP is the most economic system.

The Literature Review of De Novo Programming

De novo programming (DNP) is a system design approach which links system flexibility efficient and optimal system design. It shows that within single or multi-objective decision making framework. DNP allows the decision maker to achieve an ideal or meta-optimal system performance, or improve the performance of compromise solutions through the modification of the feasible region of decision alternatives. This paper considers a brief review of DNP, which provides a brief insight DNP and its applications.

The Literature Review of De Novo Programming

De novo programming (DNP) is a system design approach which links system flexibility efficient and optimal system design. It shows that within single or multi-objective decision making framework. DNP allows the decision maker to achieve an ideal or meta-optimal system performance, or improve the performance of compromise solutions through the modification of the feasible region of decision alternatives. This paper considers a brief review of DNP, which provides a brief insight DNP and its applications.

COORDINATOR SIMULATION COMPUTER MODEL WORKING AS APART OF BIOMETRIC RECOGNITION SYSTEM

Simulation computer model of an optoelectronic coordinate measurer for point objects is considered that is a part of the subject recognition system based on biometric features. The presented model allows you to virtually explore and analyze the processes of functioning of the coordinator, which ensures optimal coordination of parameters and characteristics of various parts of the device, as well as to choose the most effective algorithm for processing the resulting digital image by minimizing the error of measuring the coordinates of a single point object. The simulation is based on the Monte Carlo method of multiple statistical tests, which provides most accurate representation of noise processes that occur when receiving and converting optical information in the optical-electronic path of a coordinate device, since these processes, under solid equal conditions, make a decisive contribution to the final measurement error. The principles of the model are described and the results obtained are discussed, as well as the future development of the model and its application for solving problems of optimal system design of biometric recognition systems.

If You Provide, Will They Ride? Motivators and Deterrents to Shared Micro-Mobility

Bike share, e-bike share, and e-scooter systems (shared micro-mobility) are gaining popularity throughout the United States and internationally, but the optimal system design has not been determined. This study investigated motivators and deterrents to the use of such systems in the Pacific Northwest with secondary data, participant observations, depth interviews, and an on-line survey to users and non-users. The survey was administered in all cities in Washington, Oregon, and Idaho that have shared micro-mobility systems. The strongest motivators reported were exercise and enjoyment. The strongest deterrents were weather, danger from automobile traffic, and insufficient bike lanes and paths. The latter two deterrents might be alleviated through continued improvements to infrastructure; however, the weather cannot be changed, and neither can hills. Data were fitted to the Theory of Reasoned Action and the resulting recommendation is to promote popular motivators of exercise and enjoyment and emphasize personal benefits more than social appearances.

Optimal Design of a Stand-Alone Residential Hybrid Microgrid System for Enhancing Renewable Energy Deployment in Japan

This paper aims at the optimal designing of a stand-alone microgrid (PV/wind/battery/diesel) system, which can be utilized to meet the demand load requirements of a small residential area in Kasuga City, Fukuoka. The simulation part is developed to estimate the electrical power generated by each component, taking into account the variation of the weather parameters, such as wind, solar irradiation, and ambient temperature. The optimal system design is then based on the Particle Swarm Optimization (PSO) method to find the optimal configuration of the proposed system, using the least-cost perspective approach.