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  • 1.
    Campana, Pietro Elia
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Jige Quan, S.
    Georgia Institute of Technology, US.
    Robbio, F.I.
    ABB AB, Västerås, Sweden.
    Lundblad, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH Royal Institute of Technology, Sweden.
    Zhang, Y.
    KTH Royal Institute of Technology, Sweden.
    Ma, Tao
    Shanghai Jiao Tong University, China.
    Karlsson, Björn
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Yan, Jinyue
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Optimization of a residential district with special consideration on energy and water reliability2017Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 194, s. 751-764Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Many cities around the world have reached a critical situation when it comes to energy and water supply, threatening the urban sustainable development. From an engineering and architecture perspective it is mandatory to design cities taking into account energy and water issues to achieve high living and sustainability standards. The aim of this paper is to develop an optimization model for the planning of residential urban districts with special consideration of renewables and water harvesting integration. The optimization model is multi-objective which uses a genetic algorithm to minimize the system life cycle costs, and maximize renewables and water harvesting reliability through dynamic simulations. The developed model can be used for spatial optimization design of new urban districts. It can also be employed for analyzing the performances of existing urban districts under an energy-water-economic viewpoint.

    The optimization results show that the reliability of the hybrid renewables based power system can vary between 40 and 95% depending on the scenarios considered regarding the built environment area and on the cases concerning the overall electric load. The levelized cost of electricity vary between 0.096 and 0.212 $/kW h. The maximum water harvesting system reliability vary between 30% and 100% depending on the built environment area distribution. For reliabilities below 20% the levelized cost of water is kept below 1 $/m3 making competitive with the network water tariff.

  • 2.
    Campana, Pietro Elia
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Quan, S. J.
    Georgia Institute of Technology, USA.
    Robbio, F. I.
    ABB AB, Västerås, Sweden.
    Lundblad, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH Royal Institute of Technology, Sweden.
    Zhang, Y.
    KTH Royal Institute of Technology, Sweden.
    Ma, T.
    KTH Royal Institute of Technology, Sweden.
    Yan, Jinyue
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH Royal Institute of Technology, Sweden.
    Spatial optimization of residential urban district - Energy and water perspectives2016Ingår i: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 88, s. 38-43Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Many cities around the world have reached a critical situation when it comes to energy and water supply, threatening the urban sustainable development. The aim of this paper is to develop a spatial optimization model for the planning of residential urban districts with special consideration of renewables and water harvesting integration. In particular, the paper analyses the optimal configuration of built environment area, PV area, wind turbines number and relative occupation area, battery and water harvester storage capacities, as a function of electricity and water prices. The optimization model is multi-objective which uses a genetic algorithm to minimize the system life cycle costs, and maximize renewables and water harvesting reliability. The developed model can be used for spatial optimization design of new urban districts. It can also be employed for analyzing the performances of existing urban districts under an energy-water-economic viewpoint. Assuming a built environment area equal to 75% of the total available area, the results show that the reliability of the renewables and water harvesting system cannot exceed the 6475 and 2500 hours/year, respectively. The life cycle costs of integrating renewables and water harvesting into residential districts are mainly sensitive to the battery system specific costs since most of the highest renewables reliabilities are guaranteed through the energy storage system.

  • 3.
    Campana, Pietro Elia
    et al.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Yang, Z.
    KTH Royal Institute of Technology, Sweden.
    Anders, Lundblad
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Li, Hailong
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Yan, Jinyue
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH Royal Institute of Technology, Sweden.
    An Open-source Platform for Simulation and Optimization of Clean Energy Technologies2017Ingår i: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 105, s. 946-952Artikel i tidskrift (Refereegranskat)
    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. 

  • 4.
    Zhang, Y.
    et al.
    KTH-Royal Institute of Technology, Stockholm, Sweden.
    Campana, Pietro Elia
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH-Royal Institute of Technology, Stockholm, Sweden.
    Yang, Ying
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Stridh, Bengt
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Lundblad, A.
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. RISE Research Institutes of Sweden, Borås, Sweden.
    Yan, Jinyue
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH-Royal Institute of Technology, Stockholm, Sweden.
    Energy flexibility from the consumer: Integrating local electricity and heat supplies in a building2018Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 223, s. 430-442Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The increasing penetration level of renewable energy requires more flexibility measures to be implemented in future energy systems. Integrating an energy consumer’s local energy supplies connects multiple energy networks (i.e., the electrical grid, the district heating network, and gas network) in a decentralized way. Such integration enhances the flexibility of energy systems. In this work, a Swedish office building is investigated as a case study. Different components, including heat pump, electrical heater, battery and hot water storage tank are integrated into the electricity and heat supply system of the building. Special focus is placed on the flexibility that the studied building can provide to the electrical grid (i.e., the building modulates the electricity consumption in response to the grid operator’s requirements). The flexibility is described by two metrics including the flexibility hours and the flexibility energy. Optimization of the component capacities and the operation profiles is carried out by using Mixed Integer Linear Programming (MILP). The results show that the system fully relies on electricity for the heat demand when not considering the flexibility requirements of the electrical grid. This suggests that district heating is economically unfavorable compared with using electricity for the heat demand in the studied case. However, when flexibility requirements are added, the system turns to the district heating network for part of the heat demand. The system provides great flexibility to the electrical grid through such integration. The flexibility hours can be over 5200 h in a year, and the flexibility energy reaches more than 15.7 MWh (36% of the yearly electricity consumption). The yearly operation cost of the system slightly increases from 62,273 to 65,178 SEK when the flexibility hours increase from 304 to 5209 h. The results revealed that flexibility can be provided from the district heating network to the electrical grid via the building.

  • 5.
    Zhang, Y.
    et al.
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Lundblad, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH Royal Institute of Technology, Stockholm, Sweden.
    Campana, Pietro Elia
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Benavente, F.
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Yan, Jinyue
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH Royal Institute of Technology, Stockholm, Sweden.
    Battery sizing and rule-based operation of grid-connected photovoltaic-battery system: A case study in Sweden2017Ingår i: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 133, s. 249-263Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The optimal components design for grid-connected photovoltaic-battery systems should be determined with consideration of system operation. This study proposes a method to simultaneously optimize the battery capacity and rule-based operation strategy. The investigated photovoltaic-battery system is modeled using single diode photovoltaic model and Improved Shepherd battery model. Three rule-based operation strategies—including the conventional operation strategy, the dynamic price load shifting strategy, and the hybrid operation strategy—are designed and evaluated. The rule-based operation strategies introduce different operation parameters to run the system operation. multi-objective Genetic Algorithm is employed to optimize the decisional variables, including battery capacity and operation parameters, towards maximizing the system's Self Sufficiency Ratio and Net Present Value. The results indicate that employing battery with the conventional operation strategy is not profitable, although it increases Self Sufficiency Ratio. The dynamic price load shifting strategy has similar performance with the conventional operation strategy because the electricity price variation is not large enough. The proposed hybrid operation strategy outperforms other investigated strategies. When the battery capacity is lower than 72 kW h, Self Sufficiency Ratio and Net Present Value increase simultaneously with the battery capacity.

  • 6.
    Zhang, Y.
    et al.
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Lundblad, Anders
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH Royal Institute of Technology, Stockholm, Sweden.
    Campana, Pietro Elia
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Yan, Jinyue
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH Royal Institute of Technology, Stockholm, Sweden.
    Employing battery storage to increase photovoltaic self-sufficiency in a residential building of Sweden2016Ingår i: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 88, s. 455-461Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Photovoltaic (PV) or hybrid PV-battery systems are promising to supply power for residential buildings. In this study, the load profile of a multi apartment building in Gothenburg and the PV production profile under local weather conditions are compared and analyzed. Three different types of batteries, including lead acid, NaNiCl (Sodium-Nickel-Chloride) and Lithium ion, are studied in combination with the PV systems. It is found that Lithium ion battery system is superior in achieving higher Self-Sufficiency Ratio (SSR) with the same Life Cycle Cost (LCC). Achieving high SSR with the hybrid PV-battery system is unrealistic because of the seasonal mismatch between the load and electricity production profile. The capacity match between the PV and battery to maximize SSR was investigated, showing different trends under system LCC range of 0.1-40 Million SEK (1SEK≈0.12USD). The system LCC should be lower than 10.6 Million SEK (at the SSR of 36%) in order to keep the payback time positive. 

  • 7.
    Zhang, Yang
    et al.
    KTH Royal Inst Technol, Sweden.
    Campana, Pietro Elia
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Anders, Lundblad
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Yan, Jinyue
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH Royal Inst Technol, Sweden.
    Comparative study of hydrogen storage and battery storage in grid connected photovoltaic system: Storage sizing and rule-based operation2017Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 201, s. 397-411Artikel i tidskrift (Refereegranskat)
    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). 

  • 8. Zhang, Yang
    et al.
    Campana, Pietro Elia
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Anders, Lundblad
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi.
    Zhang, Chi
    Yan, Jinyue
    Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, Framtidens energi. KTH, Sweden.
    Building Energy System: From System Planning To Operation2018Konferensbidrag (Refereegranskat)
1 - 8 av 8
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