Pei Huang
@du.se
Institution of Information and Technology
Dalarna University
RESEARCH, TEACHING, or OTHER INTERESTS
Energy, Engineering, Transportation, Civil and Structural Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Linfeng Zhang, Edgar Mauricio Ocampo Alvarez, and Pei Huang
Elsevier BV
Anthony Board, Yongjun Sun, Pei Huang, and Tao Xu
Elsevier BV
Maria Sandström, Pei Huang, Chris Bales, and Erik Dotzauer
Elsevier BV
Puneet Saini, Pei Huang, Frank fiedler, Anna Volkova, and Xingxing Zhang
Elsevier BV
Mengjie Han, Fatemeh Johari, Pei Huang, and Xingxing Zhang
Elsevier BV
Tao Xu, Jiaming Zhang, Gan Fan, Ting Zou, Huachong Hu, Yanliang Du, Yonggang Yang, Haiwen Li, and Pei Huang
Elsevier BV
Ross May and Pei Huang
Elsevier BV
M. Koubar, O. Lindberg, P. Huang, and J. Munkhammar
Institution of Engineering and Technology
Ieva Pakere, Marika Kacare, Lina Murauskaite, Pei Huang, and Anna Volkova
Walter de Gruyter GmbH
Abstract District Heating and Cooling (DHC) technology is widely recognised as a promising solution for reducing primary energy consumption and emissions. The 5th Generation District Heating and Cooling (5GDHC) network is the latest DHC concept characterised by low-temperature supply, bi-directional heating network operation, decentralised energy flows, and surplus heat sharing. Unlike the 4th Generation District Heating (4GDH) technology, the 5GDHC technology switched to a consumer/prosumer-oriented perspective. The introduction of 5GDHC solutions requires high investments, an important barrier to further developing DHC systems. Therefore, a novel pricing and business model could include introducing co-owners or energy managers into the system. Three different local market business models for 5GDHC at the community level have been tested. The reverse technical and economic simulation has been used for a feasibility study to determine the resources, business models, and combinations closest to the break-even point with lower costs and higher gains for all involved stakeholders.
Pei Huang and Xingxing Zhang
EDP Sciences
The use of electric vehicles (EVs) has been on the rise. Most of the existing EV smart charging controls can be categorized into three approaches according to their optimization principles: individual, bottom-up and top-down. Until now, systematic comparison and analysis of the different approaches are still lacking. It is still unknown whether a control approach performs better than others and, if yes, why is it so. This study aims to fill in such knowledge gaps by conducting a systematic comparison of these three different control approaches and analyzing their performances in depth. A representative control algorithm will be selected from each control approach, then the selected algorithms will be applied for optimizing EV charging loads in a building community in Sweden. Their power regulation performances will be comparatively investigated. This study will help pave the way for the developments of more sophisticated control algorithms for EV smart charging.
Pei Huang, Ran Tu, Xingxing Zhang, Mengjie Han, Yongjun Sun, Syed Asad Hussain, and Linfeng Zhang
Elsevier BV
Pei Huang, Mengjie Han, Xingxing Zhang, Syed Asad Hussain, Rohit Jayprakash Bhagat, and Deepu Hogarehalli Kumar
Elsevier BV
Jihui Yuan, Pei Huang, and Jiale Chai
Elsevier BV
Anna Volkova, Ieva Pakere, Lina Murauskaite, Pei Huang, Kertu Lepiksaar, and Xinxing Zhang
Elsevier BV
Pei Huang, Marco Lovati, Jingchun Shen, Jiale Chai, and Xingxing Zhang
Elsevier BV
Pei Huang, Joakim Munkhammar, Reza Fachrizal, Marco Lovati, Xingxing Zhang, and Yongjun Sun
Elsevier BV
Tomas Persson, Amélie Chaillou, and Pei Huang
Elsevier BV
Dian-ce Gao, Yongjun Sun, Xingxing Zhang, Pei Huang, and Yelin Zhang
Elsevier BV
Xingxing Zhang, Jingchun Shen, Puneet Kumar Saini, Marco Lovati, Mengjie Han, Pei Huang, and Zhihua Huang
Frontiers Media SA
A digital twin is regarded as a potential solution to optimize positive energy districts (PED). This paper presents a compact review about digital twins for PED from aspects of concepts, working principles, tools/platforms, and applications, in order to address the issues of both how a digital PED twin is made and what tools can be used for a digital PED twin. Four key components of digital PED twin are identified, i.e., a virtual model, sensor network integration, data analytics, and a stakeholder layer. Very few available tools now have full functions for digital PED twin, while most tools either have a focus on industrial applications or are designed for data collection, communication and visualization based on building information models (BIM) or geographical information system (GIS). Several observations gained from successful application are that current digital PED twins can be categorized into three tiers: (1) an enhanced version of BIM model only, (2) semantic platforms for data flow, and (3) big data analysis and feedback operation. Further challenges and opportunities are found in areas of data analysis and semantic interoperability, business models, data security, and management. The outcome of the review is expected to provide useful information for further development of digital PED twins and optimizing its sustainability.
Pei Huang, Yongjun Sun, Marco Lovati, and Xingxing Zhang
Elsevier BV
Marco Lovati, Pei Huang, Carl Olsmats, Da Yan, and Xingxing Zhang
MDPI AG
Urban Photovoltaic (PV) systems can provide large fractions of the residential electric demand at socket parity (i.e., a cost below the household consumer price). This is obtained without necessarily installing electric storage or exploiting tax funded incentives. The benefits of aggregating the electric demand and renewable output of multiple households are known and established; in fact, regulations and pilot energy communities are being implemented worldwide. Financing and managing a shared urban PV system remains an unsolved issue, even when the profitability of the system as a whole is demonstrable. For this reason, an agent-based modelling environment has been developed and is presented in this study. It is assumed that an optimal system (optimized for self-sufficiency) is shared between 48 households in a local grid of a positive energy district. Different scenarios are explored and discussed, each varying in number of owners (agents who own a PV system) and their pricing behaviour. It has been found that a smaller number of investors (i.e., someone refuse to join) provokes an increase of the earnings for the remaining investors (from 8 to 74% of the baseline). Furthermore, the pricing strategy of an agent shows improvement potential without knowledge of the demand of others, and thus it has no privacy violations.
Samer Quintana, Pei Huang, Mengjie Han, and Xingxing Zhang
MDPI AG
Urban energy mapping plays a crucial role in benchmarking the energy performance of buildings for many stakeholders. This study examined a set of buildings in the city of Borlänge, Sweden, owned by the municipality. The aim was to present a digital spatial map of both electricity use and district heating demand in the spatial–temporal dimension. A toolkit for top-down data processing and analysis was considered based on the energy performance database of municipality-owned buildings. The data were initially cleaned, transformed and geocoded using custom scripts and an application program interface (API) for OpenStreetMap and Google Maps. The dataset consisted of 228 and 105 geocoded addresses for, respectively, electricity and district heating monthly consumption for the year 2018. A number of extra parameters were manually incorporated to this data, i.e., the total floor area, the building year of construction and occupancy ratio. The electricity use and heating demand in the building samples were about 24.47 kWh/m2 and 268.78 kWh/m2, respectively, for which great potential for saving heating energy was observed. Compared to the electricity use, the district heating showed a more homogenous pattern following the changes of the seasons. The digital mapping revealed a spatial representation of identifiable hotspots for electricity uses in high-occupancy/density areas and for district heating needs in districts with buildings mostly constructed before 1980. These results provide a comprehensive means of understanding the existing energy distributions for stakeholders and energy advisors. They also facilitate strategy geared towards future energy planning in the city, such as energy benchmarking policies.
Samer Quintana, Pei Huang, Puneet Saini, and Xingxing Zhang
Informa UK Limited
ABSTRACT This paper proposes an integrated simulation framework for both building design and energy performance analysis. Literature review shows that, although many studies exist, most of them did not fully consider the integrated techno-economic evaluation of building-integrated photovoltaic (BIPV) system. Therefore, this research aims to use the interoperability potential offered by applying a building information modelling BIM-friendly software to an integrated simulation tool to conduct a comprehensive techno-economic evaluation of a BIPV system in a building cluster. Through visual integration in a digital mock-up, the solar irradiation, surrounding shadings, BIPV location, BIPV components/system (string, inverter, battery), and economic analysis have been performed on a residential building cluster located in Ludvika, Sweden. The results show the optimal location for the 615 m2 BIPV system with a yielding of 27,394 kWh/year. Under the defined boundary conditions, the payback period is 10 years in the mixed feed-in and self-consumption mode, over its 20 years’ life span. Further sensitivity analysis of 18 cases is carried out in order to evaluate the impact of installation position (capacity), future climate change, shadings, and operating mode. This study will help improve decision-making by analysing the impact of the aforementioned factors on a BIPV system techno-economic performance.
Xingxing Zhang, Filippo Pellegrino, Jingchun Shen, Benedetta Copertaro, Pei Huang, Puneet Kumar Saini, and Marco Lovati
Elsevier BV
Yelin Zhang, Xingxing Zhang, Pei Huang, and Yongjun Sun
Elsevier BV