mdh.sePublications
Change search
Link to record
Permanent link

Direct link
BETA
Anders, Lundblad
Publications (3 of 3) Show all publications
Zhang, Y., Campana, P. E., Anders, L., Zhang, C. & Yan, J. (2018). Building Energy System: From System Planning To Operation. In: : . Paper presented at Renewable Energy Integration with Mini/Microgrid REM2018.
Open this publication in new window or tab >>Building Energy System: From System Planning To Operation
Show others...
2018 (English)Conference paper, Oral presentation with published abstract (Refereed)
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-41682 (URN)
Conference
Renewable Energy Integration with Mini/Microgrid REM2018
Available from: 2018-12-18 Created: 2018-12-18 Last updated: 2018-12-21Bibliographically approved
Campana, P. E., Yang, Z., Anders, L., Li, H. & Yan, J. (2017). An Open-source Platform for Simulation and Optimization of Clean Energy Technologies. Paper presented at 8th International Conference on Applied Energy, ICAE 2016, 8 October 2016 through 11 October 2016. Energy Procedia, 105, 946-952
Open this publication in new window or tab >>An Open-source Platform for Simulation and Optimization of Clean Energy Technologies
Show others...
2017 (English)In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 105, p. 946-952Article in journal (Refereed) Published
Abstract [en]

This paper is to describe an open-source code for optimization of clean energy technologies. The model covers the whole chain of energy systems including mainly 6 areas: renewable energies, clean energy conversion technologies, mitigation technologies, intelligent energy uses, energy storage, and sustainability. Originally developed for optimization of renewable water pumping systems for irrigation, the open-source model is written in Matlab® and performs simulation, optimization, and design of hybrid power systems for off-grid and on-grid applications. The model uses genetic algorithm (GA) as optimization technique to find the best mix among power sources, storage systems, and back-up sources to minimize life cycle cost, and renewable power system reliability. 

Place, publisher, year, edition, pages
Elsevier Ltd, 2017
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-35990 (URN)10.1016/j.egypro.2017.03.423 (DOI)000404967901007 ()2-s2.0-85020730077 (Scopus ID)
Conference
8th International Conference on Applied Energy, ICAE 2016, 8 October 2016 through 11 October 2016
Available from: 2017-06-29 Created: 2017-06-29 Last updated: 2018-07-25Bibliographically approved
Zhang, Y., Campana, P. E., Anders, L. & Yan, J. (2017). Comparative study of hydrogen storage and battery storage in grid connected photovoltaic system: Storage sizing and rule-based operation. Applied Energy, 201, 397-411
Open this publication in new window or tab >>Comparative study of hydrogen storage and battery storage in grid connected photovoltaic system: Storage sizing and rule-based operation
2017 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 201, p. 397-411Article in journal (Refereed) Published
Abstract [en]

The paper studies grid-connected photovoltaic (PV)-hydrogen/battery systems. The storage component capacities and the rule-based operation strategy parameters are simultaneously optimized by the Genetic Algorithm. Three operation strategies for the hydrogen storage, namely conventional operation strategy, peak shaving strategy and hybrid operation strategy, are compared under two scenarios based on the pessimistic and optimistic costs. The results indicate that the hybrid operation strategy, which combines the conventional operation strategy and the peak shaving strategy, is advantageous in achieving higher Net Present Value (NPV) and Self Sufficiency Ratio (SSR). Hydrogen storage is further compared with battery storage. Under the pessimistic cost scenario, hydrogen storage results in poorer performance in both SSR and NPV. While under the optimistic cost scenario, hydrogen storage achieves higher NPV. Moreover, when taking into account the grid power fluctuation, hydrogen storage achieves better performance in all three optimization objectives, which are NPV, SSR and GI (Grid Indicator). 

National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-36008 (URN)10.1016/j.apenergy.2017.03.123 (DOI)000403416300031 ()2-s2.0-85017190863 (Scopus ID)
Available from: 2017-06-29 Created: 2017-06-29 Last updated: 2018-01-24Bibliographically approved
Organisations

Search in DiVA

Show all publications