Design and Comparison of Scheduling Schemes for Grid-Connected Hybrid PV-Hydrogen-Battery Microgrid

The hybrid PV-Hydrogen-Battery microgrid is a promising solution to the global energy crisis. A novel scheduling strategy for this microgrid is designed in this paper. It divides one day into four periods, namely Morning, Daytime, Evening, and Night, based on the Time-of-Use prices and the electricity demand-supply matching degree. Diverse energy resources are adopted during each period to save the electricity bill. Then, three scheduling schemes with different PV power utilizing strategies are devised for Daytime period, and their economic performances with the change of feed-in tariffs are compared. Moreover, the battery capacities of three schemes are optimized from both technical and economic perspectives. Finally, the developing trends of three schemes are analyzed to assist customers in selecting the most applicable one according to their demands.

[1]  Roberto Carapellucci,et al.  Modeling and optimization of an energy generation island based on renewable technologies and hydrogen storage systems , 2012 .

[2]  Jiyong Kim,et al.  Design and operation of renewable energy sources based hydrogen supply system: Technology integration and optimization , 2017 .

[3]  Lide M. Rodriguez-Martinez,et al.  Cycle ageing analysis of a LiFePO4/graphite cell with dynamic model validations: Towards realistic lifetime predictions , 2014 .

[4]  Athanasios V. Vasilakos,et al.  Enhancing smart grid with microgrids: Challenges and opportunities , 2017 .

[5]  T. Schmidt,et al.  The economic viability of battery storage for residential solar photovoltaic systems – A review and a simulation model , 2014 .

[6]  Ali Ahmadian,et al.  Factor analysis based optimal storage planning in active distribution network considering different battery technologies , 2016 .

[7]  Stephane Avril,et al.  Multi-objective optimization of batteries and hydrogen storage technologies for remote photovoltaic systems , 2010 .

[8]  M. Raza,et al.  On recent advances in PV output power forecast , 2016 .

[9]  João F. D. Rodrigues,et al.  Analysis of feed-in tariff policies for solar photovoltaic in China 2011–2016 , 2017 .

[10]  M. Verbrugge,et al.  Cycle-life model for graphite-LiFePO 4 cells , 2011 .

[11]  J D Dogger,et al.  Characterization of Li-Ion Batteries for Intelligent Management of Distributed Grid-Connected Storage , 2011, IEEE Transactions on Energy Conversion.

[12]  Pasi Peltoniemi,et al.  On- and off-grid laboratory test setup for hydrogen production with solar energy in nordic conditions , 2015, 2015 17th European Conference on Power Electronics and Applications (EPE'15 ECCE-Europe).

[13]  T. Schmidt,et al.  Cost-Efficient Demand-Pull Policies for Multi-Purpose Technologies – The Case of Stationary Electricity Storage , 2015 .

[14]  Benedikt Battke,et al.  A review and probabilistic model of lifecycle costs of stationary batteries in multiple applications , 2013 .

[15]  Mazen Alamir,et al.  Battery sizing for PV power plants under regulations using randomized algorithms , 2017 .

[16]  C. Ziogou,et al.  Impact of the battery depth of discharge on the performance of photovoltaic hydrogen production unit with energy management strategy , 2015, 2015 International Conference on Renewable Energy Research and Applications (ICRERA).

[17]  Luis M. Fernández,et al.  Improving long-term operation of power sources in off-grid hybrid systems based on renewable energy, hydrogen and battery , 2014 .

[18]  J. F. Armendariz-Lopez,et al.  Life cycle cost of photovoltaic technologies in commercial buildings in Baja California, Mexico , 2016 .

[19]  Francisco Jurado,et al.  Optimized operation combining costs, efficiency and lifetime of a hybrid renewable energy system with energy storage by battery and hydrogen in grid-connected applications , 2016 .