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Small-Scale Decentralized Energy Systems: optimization and performance analysis
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Heat and Power Technology. (Polygeneration)
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Small-scale polygeneration energy systems, providing multiple energy services, such as heating, electricity, cooling, and clean water, using multiple energy sources (renewable and non-renewable) are considered an important component in the energy transition movement. Exploiting locally available energy sources and providing energy services close to the end users have potential environmental, economic, and societal benefits. Furthermore, integration of thermal and electro-chemical storages in the system can decrease fossil fuel consumption, particularly when applying a long-term perspective.

Despite their promising potential, the global share of power generation by these systems, including the combined heat and power (CHP) systems, is relatively low in the current energy market. To investigate the applicability of these systems, their competitiveness in comparison with conventional energy solutions should be carefully analyzed in terms of energy, economy, and the environment. However, determining whether the implementation of a polygeneration system fulfills economic, energetic, and environmental criteria is a challenging process. Additionally, the design of such systems is a complex task, due to a system design with various generation and storage modules, and the continuous interaction between the modules, load demand fluctuations, and the intermittent nature of renewable energy sources.

In this research study, a method to identify the optimal size for small-scale polygeneration systems and suitable operating strategies is proposed. Based on this method, a mathematical model is developed that can optimize the design in terms of energy, economy, and the environment relative to a reference system for a given application. Moreover, the developed model is used to investigate the effects of various parameters on the performance of the system, including, among others, the selected operating strategy and load characteristics as well the climate zones through a number of case studies. It is concluded that the application of a small-scale polygeneration energy system potentially has considerable energetic and environmental benefits. However, its economic feasibility varies from case to case. The concluding remarks are primarily intended to provide a general perception of the potential application of a polygeneration system as an alternative solution. It also provides a general understanding of the effects of various parameters on the design and performance of a complex polygeneration system.

The results from various case studies demonstrate that the developed model can efficiently identify the optimal size of a polygeneration system and its performance relative to a reference system. This can support engineers and researchers as well as investors and other decision makers to realize whether a polygeneration system is a good choice for a specific case.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2018. , p. 137
Series
TRITA-ITM-AVL ; 2018:20
Keywords [en]
Small-scale polygeneration energy systems, techno-economic optimization, renewable energy, operating strategy, particle swarm optimization, optimization algorithm, decentralized energy system
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-228078ISBN: 978-91-7729-808-3 (print)OAI: oai:DiVA.org:kth-228078DiVA, id: diva2:1206702
Public defence
2018-06-07, Kollegiesalen, Brinellvägen 8, Stockholm, 14:00 (English)
Opponent
Supervisors
Available from: 2018-05-18 Created: 2018-05-17 Last updated: 2019-05-10Bibliographically approved
List of papers
1. Optimal planning and design method for complex polygeneration systems: A case study for a residential building in Italy
Open this publication in new window or tab >>Optimal planning and design method for complex polygeneration systems: A case study for a residential building in Italy
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Polygeneration energy systems using multiple energy sources (e.g., wind, biomass, solar) and delivering multiple energy services (i.e., heating, cooling, and electricity) have potential economic and environmental benefits over traditional energy generation systems. However, for maximized benefits, such systems must be the correct size and have a suitable operating strategy implemented. In this study, an optimization model is proposed to identify the optimal design and operating strategy of a complex polygeneration system. The system includes photovoltaic modules, solar thermal units, wind turbines, combined heat and power units, energy storages (hot, cold, and electric), vapor compression and absorption chillers, and a boiler. The interactions between these units are managed based on the integrated operating strategies: following thermal load, following electric load and modified base load. A particle swarm optimization is used as an optimization algorithm and the objective function is defined to minimize the annualized total cost, fuel consumption, and carbon dioxide emissions using a weighting factor method. The careful incorporation of the realistic operation of the CHP is considered in the theoretical model. This includes the effects of the part-load operation and outdoor temperature on the efficiency and power output of the CHP. In addition, the size dependency of the unit cost of the chillers and CHP units over the search space is taken into account. With this approach, the achieved results would be as close to real conditions as possible. Six configuration scenarios are examined for a case study in a residential building complex located in northern Italy. It is concluded that implementation of the optimized polygeneration system has energetic, economic, and environmental conservation benefits in all these scenarios. The annualized cost and fuel consumption of the optimal solutions decreased by 3–19% and 10–37%, respectively, for the various scenarios compared to the separate generation system.

National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-228077 (URN)
Note

QC 20180529

Available from: 2018-05-17 Created: 2018-05-17 Last updated: 2018-05-29Bibliographically approved
2. Design Optimization of a Complex PolygenerationSystem for a Hospital
Open this publication in new window or tab >>Design Optimization of a Complex PolygenerationSystem for a Hospital
2018 (English)In: Energies, ISSN 1996-1073, E-ISSN 1996-1073, Vol. 11, no 1071Article in journal (Refereed) Published
Abstract [en]

Small-scale decentralized polygeneration systems have several energetic, economic and environmental benefits. However, using multiple energy sources and providing multiple energy services can lead to complicated studies which require advanced optimization techniques for determining optimal solutions. Furthermore, several parameters can influence the design and performance of a polygeneration system. In this study, the effects of heat load, renewable generation and storage units on the optimal design and performance of a polygeneration system for a hypothetical hospital located in northern Italy are investigated. The polygeneration system shows higher performance compared to the reference system, which is based on the separate generation of heat and power. It reduces fuel consumption by 14–32%, CO2 emissions by 10–29% and annualized total cost by 7–19%, for various studied scenarios. The avoided fuel and electricity purchase of the polygeneration system has a positive impact on the economy. This, together with the environmental and energetic benefits if the renewable generation and use of storage devices, indicate the viability and competitiveness of the system.

Keywords
polygeneration; decentralized energy system; optimization; multi-energy system; renewable energy system
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-227688 (URN)
Note

QC 20180531

Available from: 2018-05-11 Created: 2018-05-11 Last updated: 2018-05-31Bibliographically approved
3. Design optimization of a small-scale polygeneration energy system in different climate zones in Iran
Open this publication in new window or tab >>Design optimization of a small-scale polygeneration energy system in different climate zones in Iran
2018 (English)In: Energies, ISSN 1996-1073, E-ISSN 1996-1073, Vol. 11, no 5, article id 1115Article in journal (Refereed) Published
Abstract [en]

Design and performance of polygeneration energy systems are highly influenced by several variables, including the climate zone, which can affect the load profile as well as the availability of renewable energy sources. To investigate the effects, in this study, the design of a polygeneration system for identical residential buildings that are located in three different climate zones in Iran has been investigated. To perform the study, a model has previously developed by the author is used. The performance of the polygeneration system in terms of energy, economy and environment were compared to each other. The results show significant energetic and environmental benefits of the implementation of polygeneration systems in Iran, especially in the building that is located in a hot climate, with a high cooling demand and a low heating demand. Optimal polygeneration system for an identical building has achieved a 27% carbon dioxide emission reduction in the cold climate, while this value is around 41% in the hot climate. However, when considering the price of electricity and gas in the current energy market in Iran, none of the systems are feasible and financial support mechanisms or other incentives are required to promote the application of decentralized polygeneration energy systems.

Place, publisher, year, edition, pages
MDPI AG, 2018
Keywords
polygeneration system, climate zone, optimization, combined cooling, heating, and power generation (CCHP), renewable energy, particle swarm optimization (PSO) algorithm, Iran
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-227689 (URN)10.3390/en11051115 (DOI)000435610300093 ()2-s2.0-85047081323 (Scopus ID)
Note

QC 20180530

Available from: 2018-05-11 Created: 2018-05-11 Last updated: 2019-09-20Bibliographically approved
4. The choice of operating strategy for a complex polygeneration system: A case study for a residential building in Italy
Open this publication in new window or tab >>The choice of operating strategy for a complex polygeneration system: A case study for a residential building in Italy
2018 (English)In: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 163, p. 278-291Article in journal (Refereed) Published
Abstract [en]

The operating strategy can affect the optimal solution and performance of a polygeneration energy system. In this study, the effect of operating strategies: following thermal load; following electric load; and modified baseload on the optimal solution of a polygeneration system for a residential building complex in the northern part of Italy is investigated. For the optimal solutions, a comparative analysis is carried out considering the techno-economic and environmental performance of the system. The result elaborates on how the benefits achieved in a polygeneration system are influenced by the choice of operating strategy. In the building complex, implementation of the operating strategies shows considerable energetic, economic and environmental benefits compared to conventional separate heat and power generation. The ranges of annualized total cost reduction of 17–19%, carbon dioxide emission reduction of 35–43% and fuel consumption reduction of 30–38% are achieved for the various operating strategies. However, each of the operating strategies has its own advantages and drawbacks which emphasizes the importance of post-processing of the results in order to make the right choice. For example, the following thermal load shows the advantage of a higher carbon dioxide emission reduction. On the other hand, one drawback is its lower self-sustainability in terms of electric power compared to the other strategies.

Place, publisher, year, edition, pages
Elsevier, 2018
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-228076 (URN)10.1016/j.enconman.2018.02.066 (DOI)2-s2.0-8504240211 (Scopus ID)
Note

QC 20180518

Available from: 2018-05-17 Created: 2018-05-17 Last updated: 2018-05-18Bibliographically approved
5. Optimum design of a hybrid PV-CSP-LPG microgrid with Particle Swarm Optimization technique
Open this publication in new window or tab >>Optimum design of a hybrid PV-CSP-LPG microgrid with Particle Swarm Optimization technique
2016 (English)In: Applied Thermal Engineering, ISSN 1359-4311, E-ISSN 1873-5606, Vol. 109, p. 1031-1036Article in journal (Refereed) Published
Abstract [en]

Designing an energy system using multiple energy sources including renewables and providing multiple energy services (e.g. electricity, heating) can enhance the reliability and efficiency of the system while mitigating the environmental footprint. However, interaction among various components, variation of the energy demand profile, and local ambient conditions make design optimization a complex task, and suggesting that efficient simulation tools and optimization techniques can help designers to determine the best solutions within a reasonable timeframe and budget. Previous work on a dynamic microgrid simulation tool called "u-Grid" used an exhaustive search technique to find optimum configurations. However, the high computational cost of the exhaustive search was a motivation to explore alternative optimization methods to improve the optimization process and also to enhance search speed. In this paper Particle Swarm Optimization (PSO) has been presented as a global optimizer and incorporated within the problem context. Results from the exhaustive search have been used as a benchmark for testing and validation of the newly introduced optimization technique. The result shows that the PSO method is an efficient technique which has the ability to determine a high quality design solution for an optimized microgrid with a relatively low computational cost. Applying this PSO-based algorithm to the case study has reduced the total computation time a factor of about 6 in a significantly smaller computational platform.

Place, publisher, year, edition, pages
Elsevier, 2016
Keywords
Hybrid energy system, Polygeneration, Optimization, Particle Swarm Optimization, Microgrid
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-199979 (URN)10.1016/j.applthermaleng.2016.05.119 (DOI)000386738600023 ()2-s2.0-84992197068 (Scopus ID)
Funder
StandUp
Note

QC 20170206

Available from: 2017-02-06 Created: 2017-01-20 Last updated: 2018-05-17Bibliographically approved
6. Feasibility study of using a biogas engine as backup in a decentralized hybrid (PV/wind/battery) power generation system: Case study Kenya
Open this publication in new window or tab >>Feasibility study of using a biogas engine as backup in a decentralized hybrid (PV/wind/battery) power generation system: Case study Kenya
2015 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 90, no 2, p. 1830-1841Article in journal (Refereed) Published
Abstract [en]

In this study, a hybrid power system consisting of PV (Photovoltaics) panels, a wind turbine and a biogas engine is proposed to supply the electricity demand of a village in Kenya. The average and the peak load of the village are around 8kW and 16.5kW respectively.The feasibility of using locally produced biogas to drive a backup engine in comparison to using a diesel engine as backup has been explored through a techno-economic analysis using HOMER (Hybrid Optimization Model for Electric Renewables). This hybrid system has also been compared with a single diesel based power system.The results show that the hybrid system integrated with the biogas engine as backup can be a better solution than using a diesel engine as backup. The share of power generation by PV, wind and biogas are 49%, 19% and 32%, respectively. The LCOE (Levelized Cost of Electricity) of generated electricity by this hybrid system ($0.25/kWh) is about 20% cheaper than that with a diesel engine as backup ($0.31/kWh), while the capital cost and the total NPC (Net Present Cost) are about 30% and 18% lower, respectively.Regarding CO2 emissions, using a biogas engine as backup saves 17 tons of CO2 per year compared to using the diesel engine as backup.

Place, publisher, year, edition, pages
Elsevier, 2015
Keywords
Biogas engine, Decentralized energy system, HOMER, Polygeneration, Rural electrification, Techno-economic optimization
National Category
Energy Engineering
Research subject
Energy Technology
Identifiers
urn:nbn:se:kth:diva-175765 (URN)10.1016/j.energy.2015.07.008 (DOI)000364245300057 ()2-s2.0-84954398806 (Scopus ID)
Note

QC 20151023

Available from: 2015-10-20 Created: 2015-10-20 Last updated: 2019-10-02Bibliographically approved

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  • nn-NO
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  • Other locale
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Output format
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