Future City Hydrogen: Reality or Utopia?

Future City Hydrogen: Reality or Utopia?: A techno-economical feasibility study of an optimal stand-alone Solar-Electrolyzer-Battery-FuelCell system for residential utilization

Tamarzians, Michel (TU Delft Electrical Engineering, Mathematics and Computer Science)

Smets, A.H.M. (mentor)
Isabella, O. (graduation committee)
Rueda, José L. (graduation committee)

Delft University of Technology

Electrical Engineering | Sustainable Energy Technology

2019-05-10

The population worldwide is growing rapidly which leads to an increase of the energy demand. Simultaneously, the established energy resources are being depleted and contribute negatively to the climate. The necessity for a sustainable and inexhaustible energy source, to deal with the increasing energy demand in an ecological friendly approach, will play a key role in the 21st century. One of the most predictable and inexhaustible renewable energy sources is the Sun. Nevertheless, changing weather conditions, like rain and clouds, winter and summer, result in daily and seasonal fluctuations. A reliable stand-alone solar system requires a profound storage method to tackle the daily and seasonal fluctuations that can potentially result in deficit or dumped energy.
Generally, a battery bank is adopted in stand-alone solar systems, but the low energy density makes a battery bank not suitable as a seasonal storage method. A seasonal storage method can be implemented by the production and consumption of the chemical product hydrogen. Hydrogen has a high energy density compared to batteries (142 MJ/kg vs 0.95 MJ/kg), but the low round-trip efficiency prevents implementing hydrogen as a daily storage method. For a highly reliable and optimal sized stand-alone energy system, a combination of both a battery bank and the chemical product hydrogen are used as a profound storage method. The combined storage method can be used in times
of excess and deficit energy. This results in a so called stand-alone hybrid PV-Electrolyzer-Battery-FC energy system. In this final thesis project a stand-alone hybrid PV-Electolyzer-Battery-FC energy system is modelled and optimized to determine the current and future feasibility, both technologically and economically, for residential utilization. A simulation model of the hybrid energy system is designed in TRNSYS. The model is optimized by minimizing the loss of load probability (LLP) and levelized cost of energy (LCOE) for the stand-alone hybrid PV-Electolyzer-Batter-FC energy system at residential level in TRNOPT. Several cases are optimized based on the electrical, heat and mobility demand. The used optimization method is a combination of particle swarm optimization (PSO) and Hooke-Jeeves optimization algorithms implemented by GenOpt.
It is established that the proposed stand-alone hybrid PV-Electrolyzer-Battery-FC is technically feasible for the fulfillment of the annual electrical demand of a typical Dutch household. The feasible system size consists of 19 PV modules, battery capacity of 25.5 kWh and a tank volume of 1.24 cubic meters for a LCOE of 1.04 /kWh. If the future prices of the main components can be reduced to 0.01 €/Wp for PV, 0.01 €/Wh for battery and 0.01 €/W for electrolyzer and fuel cell the hybrid system can potentially reach a LCOE of 0.28 €/kWh. Reduction of the prices can be realized by large scale production, large scale implementation and technology maturity. In the end, a LCOE of 0.17 €/kWh can be realized by renewable energy systems if these future prices are realized and the following conditions are met: (1) fully covered roof area by PV modules and (1) the production, consumption and storage of hydrogen should be centralized to scatter the infrastructure costs over all the consumers. This can induce a so called hydrogen economy in the future, whereby the hydrogen gas can be the sustainable link between the increasing energy demand and the depleting fossil fuels.

Solar-Battery-Hydrogen System
Alkaline Electrolyzer
PEM fuel cell
Autonomous
Hybrid
optimization
Hooke-Jeeves
Particle Swarm Optimization
Residential
Netherlands

http://resolver.tudelft.nl/uuid:6eb18a63-3cc5-43d5-a38c-a8992b9cddd1

Student theses

master thesis

© 2019 Michel Tamarzians