Urban Energy Network Research Articles

A district-level building electricity use profile simulation model based on probability distribution inferences

District-level building energy systems play a significant role in urban energy networks in the future. Understanding the key distributive features of district electricity use profiles is essential for the optimal planning and design of energy networks. Due to the diversity of building electricity use characteristics, the district-level electricity use profile exhibits a prominent “peak staggering effect.” Current physics-based and statistical models cannot fully represent realistic distributions and the uncertainties of district profiles. Thus, it is critical to quantitatively investigate the changing patterns and distributive features of electricity use profiles at various district levels. This paper proposes a novel approach for district building electricity use profile simulation. Probability distribution inference methods integrating Gaussian Mixture Model (GMM)/lognorm distribution fitting, singular value decomposition (SVD)-based feature transformation, and distribution addition theorems have been proposed to generate the feature parameters of electricity use profiles at various district scales, thus generating simulated district electricity use profiles. The performance of the proposed model was validated using engineering-informed metrics, including peak demands, load duration curves, and standard deviations of the load parameters. The results of the case study suggest that the average relative error of the 99 % peak demand is reduced from 17.60 % in the baseline model to 3.48 % in the proposed model, the average relative error of the duration of 2Qm reduced from 40.82 % in the baseline model to 0.99 % in the proposed model, and the average relative error of the standard deviation of load parameters was reduced from >100 % in the baseline model to <35 % in the proposed model. The results indicate a better quantification of district electricity use distributions and uncertainties, providing practical tools to support the capacity design and optimization of integrated district energy systems.

Ice source heat pump system for energy supply via gas pipelines – Part1: Performance analysis in residential units

This study evaluates the performance of heat pumps using water or ice as the heat source, with energy transferred via repurposed gas delivery pipes. The proposed system offers significant benefits for urban energy networks, particularly in densely populated areas. The article is divided into two main sections: the first compares the thermal efficiency of the proposed system for residential heating against similar heat pumps. The second section examines the implementation, energy transfer capacity, and water requirements of using a gas pipeline network. The study models various heating systems, including electric-resistance, air-source, water-source, ground-source, and ice-source heat pumps, in Nottingham throughout the year. The results show that switching from gas to heat pumps significantly increases electricity demand, especially during peak periods. Specifically, electric-resistance heating, air-source, water-source, and ice-source heat pumps increase peak electricity consumption by factors of 7.5, 3.2, 2.5, and 2.7, respectively, compared to a gas boiler. Additionally, electricity consumption exceeds the current peak for 89 %, 47 %, 35 %, and 39 % of the hours in the year for each respective system. These findings emphasize the proposed system's role in managing peak electricity demand and enhancing generation and transmission capacity post-natural gas phase-out.

Statistical Evaluation of Sustainable Urban Planning: Integrating Renewable Energy Sources, Energy-Efficient Buildings, and Climate Resilience Measures

In the face of increasing climate-related challenges, sustainable urban energy networks must grapple with transmission congestion in deregulated power systems. This study introduces a novel statistical approach that synergizes two powerful methodologies for evaluating and managing urban energy networks: the integration of photovoltaic (PV) renewable energy sources and Gated Recurrent Unit (GRU)-based PV forecasting. By combining evolutionary optimization techniques with GRU forecasting, we aim to bolster the sustainability and reliability of urban energy networks while addressing climate change adaptation. In this study, we employ statistical methods, including generator sensitivity ratios and bus sensitivity ratios (BSR), to pinpoint optimal locations for PV power integration within urban networks. The Lion Optimization Algorithm (LOA), an evolutionary optimization method, is employed within a digital twin framework to optimize active power rescheduling values and congestion prices. The incorporation of GRU-based PV forecasting enhances the precision and resilience of our energy management approach. Through extensive simulations conducted on the New England 39-bus system, our findings reveal that the combination of the LOA method and GRU forecasting outperforms traditional optimization techniques such as the Ant Lion Optimizer (ALO) and Particle Swarm Optimization (PSO). This dual-optimization strategy leads to significantly reduced active power rescheduling values and congestion prices, underlining the potential of our statistical model to effectively manage congestion in transmission lines within sustainable urban energy networks. In the context of integrating renewable PV sources and adapting urban energy infrastructure to climate change impacts, the synergy of evolutionary optimization and GRU-based forecasting offers a robust pathway to enhance sustainability and reliability in urban energy networks.

Integrating photovoltaic noise barriers and electric vehicle charging stations for sustainable city transportation

Photovoltaic noise barriers (PVNBs) offer a dual advantage of reducing traffic noise pollution and providing renewable electricity to cities. However, how the effective integration of PVNB-generated power into urban energy networks remains a critical area lacking research. To bridge this gap, this study proposes PVNBs-energy storage (ES)-charging station (CS; PVNBs-ES-CS) strategy. It can facilitate the actual consumption of PVNBs power and the mitigation the burden on the grid posed by electric vehicles (EVs) charging demands. The case study conducted in Guangzhou, China, reveals that PVNBs can support up to 5% of the total power demand for EVCSs. Under the PVNBs power maximization consumption scenario, PVNBs can meet up to 30% of the power demands from 60 EVCSs, with 58% of PVNBs generated power being consumed. In the PVNBs-ES-CS future utilization scenario, up to 30% of the power demand of 125 EVCSs can be met, and 36% of the power of PVNBs can be consumed. The combination of PVNBs and EVCSs offers a practical solution for incorporating renewable energy sources into urban energy networks. This application mode can be applied in various cities with EV demands and PVNB power generation data.

Analysis of Communication Simulation Model of Urban Comprehensive Energy Network Based on the Internet of Things

In urban construction, all energy infrastructures have been realized by the information structure. However, due to the non-uniform structure of each energy network, the data cannot be more compatible, and the communication guarantee based on the Internet of Things is one of the most urgent problems to be solved. In this paper, a reasonable network computing offloading model is designed in the edge computing layer, and the computing offloading algorithm is introduced. Considering the dependency between subtasks, an optimization problem is established, and a central scheduling algorithm is proposed to solve it. An optimized distributed unloading algorithm is proposed according to the solution idea of the classical distributed unloading algorithm. Simulation results show that the optimized distributed unloading algorithm proposed in this paper has good solving efficiency and performance, and reduces the task processing delay. At the same time, the experimental simulation proves that the efficiency of multiple edge servers in processing subtasks is higher than that of a single server. It is established that changing the convergence speed and communication delay stability margin of the system by changing the system eigenvalue is beneficial to design a better communication network structure to keep the system stable.

Negative Effect Prediction and Refueling Traffic Flow Equilibrium of Urban Energy Supply Network during Weekends and Holidays

With the continuous improvement of people’s living standards, the travel demand for vehicles increases rapidly during weekends and holidays. This situation leads to a number of negative impacts on the transport network, such as traffic congestion, carbon emissions, and long queues at refueling stations. The impact of vehicles requiring energy replenishment on the negative effect is nonlinear. Therefore, the negative effect data of working days cannot be directly used to evaluate the cost, and the traffic equilibrium allocation problem also needs to be solved. An equilibrium allocation model of hybrid vehicles considering the energy replenishment demand in holidays is established, aiming at minimizing the total time cost and energy consumption cost. The Frank–Wolfe algorithm is used to solve the traffic allocation problem in advance, and the negative effect of the urban energy network during holidays is predicted by the Genetic Algorithm—Back Propagation (GA-BP) algorithm. Then, the energy-replenishing vehicles in the traffic network are induced to reduce the total cost. Finally, taking the actual road network in Jiulongpo District of Chongqing City, southwest of China, as an example, the negative effects of multiple stations are predicted. The results show that the prediction method proposed in this paper is effective during holiday periods. In addition, as the market share of electric vehicles increases, the negative cost can decrease gradually. The predicted results can provide a reference for traffic managers.

Day-Ahead Operation of an Urban Energy System Considering Traffic Flows and Peak Shaving

With the increasing penetration of new-type loads such as electric vehicles and hydrogen fuel vehicles in urban power grids, the peak-to-valley load difference increases sharply, and a multi-energy coordination model is desirable. This article proposes a day-ahead operation model of an urban energy system considering traffic flows and peak shaving, which can positively contribute to multi-energy complement and low-carbon emission. The proposed model minimizes the total cost of electricity and gas by optimizing the charging and discharging strategies of energy storage, in which the output of the wind turbine and energy management of the energy hub are adaptively adjusted. The urban energy system is represented by a second-order cone (SOC) energy flow model, and hence, the optimization problem is modeled as a mixed integer SOC programming (MISOCP). Finally, test results on an integrated urban energy network indicate that the energy storage and multi-energy coordination can alleviate the peak load cutting and valley filling. The relationship between urban grid operation cost and peak-valley difference is also discussed. The maximum utilization of renewable energy sources using gasoline vehicles has been presented in this study to illustrate cost and emission reductions for a sustainable integrated electricity and transportation infrastructure.

Investigation of performance parameters of building thermal battery

The concept of a building thermal battery refers to storing the supplied heat and releasing it the another time through radiation and convection. The introduction of building thermal battery performance has created a more convenient solution to the problems of building load estimation, control and optimization, building-grid integration, etc. Some literatures have expanded the original definition of building thermal batteries, including PV RE (photovoltaic renewable energy), HVAC and other units. Starting from the building body, this investigation studies a building energy system. With reference to the performance parameters of traditional rechargeable batteries, the corresponding performance parameters of building thermal batteries are developed. The RC model is further used to model the performance parameters of the building thermal battery respectively. Among them, the corresponding parameter values of the RC model are obtained by parameter identification. Finally, the heat storage and heat release characteristics of the building integrated energy system are obtained. It makes the application of buildings as batteries more flexible in the urban energy network.

Spatio-Temporal Modelling of the Change of Residential-Induced PM10 Pollution through Substitution of Coal with Natural Gas in Domestic Heating

Air pollution has been one of the most critical urban problems. Urban energy networks are among the major sources of air pollution, particularly in highly populated urban areas. Residential heating, which is the primary cause of particulate matter (PM) emissions, contributes to the problem through the use of low-quality fuels, such as coal. Natural gas, although a fossil fuel, is a modern, relatively clean, and more efficient alternative in residential energy use, which helps to reduce particulate matter emissions. Coal was widely used in residential heating in İzmir, Turkey, whereas natural gas is a relatively new alternative which started to be used domestically in 2006. Switching from coal and other highly polluting fossil fuels to natural gas in urban energy distribution network has contributed to the alleviation of air pollution in the city in the past decade. Spatiotemporal analyses of the PM10 concentrations, and their relation to the natural gas investments, have been conducted in geographical information systems (GIS). The spatial distribution of the change in PM10 levels has been modeled with ordinary kriging for the 2010–2011 and 2018–2019 winter seasons. Interpolated PM10 surfaces show that there is a significant decrease in the emissions throughout the city in the overall, while the highest levels of decrease are observed in the southern part of the city. Overlaying the interpolated PM10 surfaces and the natural gas pipeline investments enables the demonstration of the mutual relationship between the change in emission levels and the energy distribution network. Indeed, the spatial distribution of the pollution concentrations appears to be parallel to the natural gas investments. The pipeline investments were intensive during the 2010–2018 period in the southern districts when compared the rest of the city. The use of natural gas in residential heating contributed to the decrease in PM10 emissions.

Factors Influencing the Threats for Urban Energy Networks: The Inhabitants’ Point of View

Our paper focuses on eliciting the factors that constitute threats and dangers for urban energy networks, information networks, and energy grids in the cities. Moreover, we attempt to determine how these threats are perceived by the inhabitants of those cities. Urban energy networks tend to play an increasing role in achieving energy efficiency and environmental sustainability in large urban centers. Even though they do not necessarily correspond to reality, public opinions can substantially influence the adoption of relevant technologies in populous urban locations. We use the public opinion representative survey data from the Czech Republic (a sample of 1023 respondents) in order to show how people perceive the dangers and threats for urban energy networks from such events as: (i) Extensive and long-term power outage; (ii) service disruption of the Internet, mobile networks or telephone landlines; (iii) cyber-attacks, and (iv) the technological dependence of the state on multinational technological companies. Our results demonstrate that people who live in small rural settlements and medium-sized cities tend to be more afraid of the threats and dangers from urban energy networks such as electricity and Internet outages, compared to people residing in some smaller towns. As far as there would always be a fear of the new technologies and their vulnerabilities, the local governments, mass media, and Internet resources alike should pay more attention to providing the relevant and updated information on the threats to urban energy networks for the general public.

Opportunities for Integrating Underground Railways into Low Carbon Urban Energy Networks: A Review

Cities demand vast amounts of energy for their everyday operation, resulting in significant degradation of energy in the form of heat in the urban environment. This leads to high cooling requirements in cities, while also presenting the opportunity to reuse such waste heat in order to provide low-carbon heating for buildings and processes. Among the many potential energy sources that could be exploited in urban areas, underground railway tunnels are particularly attractive, as the operation of the trains produce considerable amounts of heat throughout the year. This paper reviews how secondary energy sources in urban areas can be integrated into heating and cooling networks, with emphasis on underground rail tunnels. This involves investigating potential urban waste heat sources and the existing state-of-the-art technologies that could be applied to efficiently recover this secondary energy, as well as analyzing how district heating and cooling networks have been a key mechanism to allow for a smooth transition from current fossil fuel based to future low-carbon energy sources.

Adaptive Robust Day-Ahead Dispatch for Urban Energy Systems

Increasing interactions between urban electrical and gas systems have the potential to transform smart grids into smart cities, where coordinated dispatch for interdependent urban infrastructure is desirable. This paper proposes an adaptive robust day-ahead energy-reserve co-optimization approach for urban energy systems, in which day-ahead energy-reserve dispatch and real-time energy-balancing regulation are employed as first- and second-stage decisions, respectively. By introducing an auxiliary variable to denote the worst-case balancing cost, we transform the trilevel optimization problem into a single-level model considering generated representative scenarios. Moreover, we propose an iterative algorithm composed of nested problems, where the master problem solves the single-level robust model considering the binding scenario subset identified by the subproblem. In this way, a more computationally tractable model can be obtained, owing to the greatly reduced number of scenarios. Finally, test results on an integrated urban energy network verify the computational superiority of the proposed solution methodology afforded by identifying the binding scenario subset. The economic benefits of the proposed adaptive robust framework are also discussed.

Northern European nearly zero energy building concepts for apartment buildings using integrated solar technologies and dynamic occupancy profile: Focus on Finland and other Northern European countries

The European Union introduced the concept of nearly zero energy buildings with the recast of the European Building Directive, requiring Member States to define nearly zero energy building in their national plans indicating a threshold value for primary energy consumption. This study investigates nearly zero energy building apartment building concepts for Northern European countries, focusing on Finland and extending the analysis to Sweden, Norway and Estonia. Particularly, different building design principles and use of building integrated solar technologies have been considered. Differently from the available studies and in accordance with recent literature, which has demonstrated the significant role of occupants in building energy consumption, the Authors considered dynamic user behaviour in order to emulate more realistic home appliances’ electricity consumption and internal heat gains. Results emphasize that one turnkey nearly zero energy building solution does not exist. Indeed, many nearly zero energy building concepts can be achieved by adopting more energy performant building design principles and/or installing onsite solar technologies. The selection of the right building design principles, typology and size of solar technologies depends on the main building heating source; typically, district heating and ground source heat pumps in Nordic countries. In Finland, nearly zero energy building concepts can be achieved by adopting the Finnish passive design principles without installing renewable energy systems onsite. Energy efficient or passive design principles lead to nearly zero energy buildings both in Norway and Finland, if ground source heat pump is used as main heating source. With regard to Sweden and Estonia, depending on the adopted building design principle and main heating source, different sizes of solar technologies should be installed onsite in order to meet nearly zero energy building requirements. In any case, at northern latitudes the energy generated onsite with conventional solar technologies is not enough to reach the Net Zero Energy target and research should focus on innovative solutions, such as seasonal storage and advanced “building to urban energy networks” solutions to go even beyond the Net Zero Energy horizon and achieve positive energy buildings.

Multi-objective optimization of a neighborhood-level urban energy network: Considering Game-theory inspired multi-benefit allocation constraints

By connecting stand-alone energy systems, the neighborhood-level urban energy network can serve several buildings in a more economic and ecological manner. In some cases, in order to achieve the best performance of the entire network, the benefit of some buildings within the network may not be guaranteed. Few attentions have been paid to the benefit allocation fairness for energy networks. This study proposes novel cost and emission benefit allocation constraints inspired from cooperative Game theory to ensure that each involved building shares the benefit together. A Mixed Integer Linear Programming (MILP) model is developed to investigate the impacts of benefit allocation constraints. The model offers different network topologies, i.e., centralized mode and distributed mode. Multi-objective optimization and decision-making are further conducted to assess the trade-offs between different objectives via generating the Pareto frontier. Through an illustrative case study, a three-building neighborhood-level energy network is optimal designed in Shanghai, China. The results indicate that when benefit allocation is considered, the solution space will slightly shrink compared to the scenario not considering benefit allocation. Meanwhile, distributed mode achieves better performance than the centralized mode. Overall, the analyses provide a solid approach to enhance infrastructure planning for urban energy networks particularly when the stakeholders of each participating building within a network are different.

Urban energy system planning from wide area network perspective

The urban energy system, consisting of multiple subsystems ranging from energy production, transformation, transmission, storage, to consumption, plays a critical role in the national and regional energy network. Due to its complexity, to optimize the urban energy system from multiple aspects and scales are necessary. Currently, a large number of urban energy planning studies have focused on optimization methods and theories targeting integrated energy systems at community scale. Several energy system optimization models have also been developed based on different technical ideas. However, from a wide area perspective, the integrated community energy system represents a small local network in the overall urban energy system network. Neglecting the mutual interaction between the local network and wide area network can result in a severe segmentation issue and low energy efficiency. But it is impractical to take into account each end-user individually during the optimization of the urban energy system, since the construction activities involved in the energy demand-supply planning cover a wide range of aspects and a long period. Therefore, the coordination between the local and overall energy networks requires in-depth exploration of the incidence relation among them. In this study, the formation of the urban energy demand and supply chains and the structure of urban energy flow network being described by tracking the energy flow from the end-users to the energy source extraction. Based on the concepts of primary energy market and secondary energy market in urban regions and local areas, respectively, the differences and connections between energy flow networks from the supply and demand sides have been discussed. Subsequently, a two-layer four-stage urban energy planning system was proposed based on the planning objects and contents. Furthermore, the typical nested and parallel relations between different local networks were proposed based on energy transformations and dissipation flows. From the structure investigation of urban energy network, such conclusions are listed as flows: (1) The overall energy flow network can be divided into two independent layers. The first network is responsible for the optimization of energy extraction from sources and the trade of energy between difference cities. The formation and evolution of the first network is dominated by the price mechanism of primary energy. The second network is focused on the local distribution of different energy resources (e.g., electricity, gas) based on the demand, and its formation and evolution are governed by the urban municipal plan (local regulations or policies). These two energy markets are independent systems interconnected by the energy price and the demand-supply information. (2) The topology of the primary energy market is flat, which indicated that there is no apparent monopoly of information or controlling center in the market. Therefore, the trading flow of energy resources forms naturally under the influence of price mechanisms. The secondary energy market is, however, controlled by an information center where the centralized processing of the scattered end-user information leads to a highly controlled limited energy market. (3) In order to integrate the different urban energy sources into an overall energy planning scheme, the current energy distribution situation with fixed beneficiaries should be changed drastically. However, there is a lack of leadership and motivation to drive such change. (4) The cost of electricity and gas used for cooling and heating in urban areas has a high impact on the secondary energy planning. An improper choice of energy price system will adversely affect the process of reducing energy consumption. (5) Establishing a smart energy supply system in urban areas requires a synergetic integration of information systems for both energy and social-economic systems. However, currently there is no study on the mutual interaction between energy systems and social-economic systems.

Learning from co-housing initiatives: Between Passivhaus engineers and active inhabitants

Following the UN world summits on Climate Change (Paris 2015) and Habitat (Quito 2016), most European cities assume an active role to implement internationally agreed goals related to climate change, translated in the so-called New Urban Agenda. At the same time, the urban housing market is increasingly inaccessible for low- and middle-income households. To overcome problems such as failing housing supply and high energy-bills, groups of residents take initiatives to create and manage housing projects collectively; these initiatives are further indicated as ‘co-housing’. The aim of this study is to create deeper understanding of the current rise of co-housing in Europe, and what it could mean in urban policies addressing energy transition and climate change. There are two domains where co-housing can become an important asset for urban development: design and maintenance of (semi-)public space for climate change mitigation, and the transition to a circular metabolism in housing. Based on empirical data, this thesis concludes that co-housing projects present relevant models and approaches for reducing the energy consumption and for integrating renewable energies in the general housing stock. Engineers can learn from co-housing pioneers to advance the targets for energy-transition and further develop sustainable cities. The thesis contributes to the emerging body of knowledge with a new understanding of co-housing, analysing its ‘key-features’ with an interdisciplinary framework, in a European context. It adds a new perspective to existing co-housing research, which is dominated by social sciences, by drawing attention to the physical characteristics of co-housing, produced in architectural, planning and engineering processes (the technosphere). The choices made during design and building are not only shaped by the residents’ aims and perception of sustainability, but also influenced by technosphere-related institutions, such as the building-components industry, energy or waste networks and providers, and planning regulations. The professional partners for the projects, such as housing associations and engineers, are equally affected by the institutional context, but their position is different from that of residents. They may for example be more anchored in governmental or professional regulations. To structure this dynamic, the research distinguishes three interrelated aspects: ACTORS / involved in the (realisation of) projects: social practices of residents and their professional partners in co-creation. CONTEXT / the structural forces surrounding the projects, specifically the macroinstitutional regimes. This also includes culturally determined interpretations of sustainability, technology, participation, societal roles, sharing, and so on. TECHNOSPHERE / specifically building technology and utilities, focussing on energyrelated design and engineering of the co-housing projects. The thesis is primarily based on qualitative methods, as it found that reliable quantitative data are as yet unavailable. Looking for effective low-impact energysolution in co-housing, quantitative data remain however necessary and this thesis elaborates on pitfalls and possibilities for their accumulation. Empirical material from Dutch case-studies form the core of the research. Examples were also taken from countries where the re-emergence of co-housing is most visible and articulate: Belgium, France, Germany, the UK and Switzerland. Co-housing continues to develop and gain experiences with competences, such as communication skills and the ability to work cross-disciplinarily. The building industry and engineering professions increasingly call for such capabilities, but resident-led urban development have not yet entered the urbanism and engineering curricula. Therefore, opportunities should be provided for future professionals not only to acquire such capabilities but also to address fundamental questions related to residentinvolvement and democracy. This will enable future professionals to create a balance between ‘bottom-up’ articulated needs on the quality of living environments with large-scale investments in new urban energy, mobility and mutual care networks.

Learning from co-housing initiatives — Between Passivhaus engineers and active inhabitants

Following the UN world summits on Climate Change (Paris 2015) and Habitat (Quito 2016), most European cities assume an active role to implement internationally agreed goals related to climate change, translated in the so-called New Urban Agenda. At the same time, the urban housing market is increasingly inaccessible for low- and middle-income households. To overcome problems such as failing housing supply and high energy-bills, groups of residents take initiatives to create and manage housing projects collectively; these initiatives are further indicated as ‘co-housing’. The aim of this study is to create deeper understanding of the current rise of co-housing in Europe, and what it could mean in urban policies addressing energy transition and climate change. There are two domains where co-housing can become an important asset for urban development: design and maintenance of (semi-)public space for climate change mitigation, and the transition to a circular metabolism in housing. Based on empirical data, this thesis concludes that co-housing projects present relevant models and approaches for reducing the energy consumption and for integrating renewable energies in the general housing stock. Engineers can learn from co-housing pioneers to advance the targets for energy-transition and further develop sustainable cities. The thesis contributes to the emerging body of knowledge with a new understanding of co-housing, analysing its ‘key-features’ with an interdisciplinary framework, in a European context. It adds a new perspective to existing co-housing research, which is dominated by social sciences, by drawing attention to the physical characteristics of co-housing, produced in architectural, planning and engineering processes (the technosphere). The choices made during design and building are not only shaped by the residents’ aims and perception of sustainability, but also influenced by technosphere-related institutions, such as the building-components industry, energy or waste networks and providers, and planning regulations. The professional partners for the projects, such as housing associations and engineers, are equally affected by the institutional context, but their position is different from that of residents. They may for example be more anchored in governmental or professional regulations. To structure this dynamic, the research distinguishes three interrelated aspects: • ACTORS / involved in the (realisation of) projects: social practices of residents and their professional partners in co-creation. • CONTEXT / the structural forces surrounding the projects, specifically the macroinstitutional regimes. This also includes culturally determined interpretations of sustainability, technology, participation, societal roles, sharing, and so on. • TECHNOSPHERE / specifically building technology and utilities, focussing on energyrelated design and engineering of the co-housing projects. The thesis is primarily based on qualitative methods, as it found that reliable quantitative data are as yet unavailable. Looking for effective low-impact energysolution in co-housing, quantitative data remain however necessary and this thesis elaborates on pitfalls and possibilities for their accumulation. Empirical material from Dutch case-studies form the core of the research. Examples were also taken from countries where the re-emergence of co-housing is most visible and articulate: Belgium, France, Germany, the UK and Switzerland. Co-housing continues to develop and gain experiences with competences, such as communication skills and the ability to work cross-disciplinarily. The building industry and engineering professions increasingly call for such capabilities, but resident-led urban development have not yet entered the urbanism and engineering curricula. Therefore, opportunities should be provided for future professionals not only to acquire such capabilities but also to address fundamental questions related to residentinvolvement and democracy. This will enable future professionals to create a balance between ‘bottom-up’ articulated needs on the quality of living environments with large-scale investments in new urban energy, mobility and mutual care networks.

The role of autonomous energy production systems in urban energy networks

The role of autonomous energy production systems in urban energy networks

A Switchable pH-differential Reactor with High Reactivity and Efficiency for CO2 Utilization

CO2 can be converted to useful fuels by electrochemistry method. As an effective strategy to address greenhouse effect and energy storage shortage, electrochemical reduction of CO2 still needs major improvements on its efficiency and reactivity. This work demonstrates a switchable pH-differential dual electrolyte microfluidic reactor (DEMR) that enhances the thermodynamic property and raises the electrochemical performance based on a laminar flow membrane-less architecture. It is the first time that the CO2 electrochemical reduction reaction is freed from the hindrances of thermodynamic limitation. DEMR has also achieved a high reactivity and Faradaic efficiency, revealing the potential for larger-scale applications in future urban energy network, such as a carbon-neutral energy conversion system.

Mixed integer linear programing based approach for optimal planning and operation of a smart urban energy network to support the hydrogen economy

The future of urban energy systems relies on the transition to “smart energy networks” which incorporate energy storage with renewable energy sources such as wind and solar. Hydrogen provides a desirable energy vector for both energy storage and exchange of energy between energy hubs within a smart energy network. This paper aims to develop a generic mathematical model for the optimal energy management of future communities where hydrogen is used as an energy vector. An energy hub is a novel concept that systematically and holistically considers the energy requirements of both mobility and stationary loads. In order to perform optimization studies, the minimization of capital cost of hydrogen refueling stations and operation and maintenance cost of all energy hubs within the network are considered. The modeling and optimization are undertaken and carried out in the General Algebraic Modeling Software (GAMS). The case study considers four energy hubs consisting of a commercial building, school, residential complex, as well as hydrogen refueling stations. The study investigates the optimal operation of different energy conversion and storage technologies in order to meet the demand of energy. The results showed that the optimum size of electrolyser and hydrogen tank for supplying the hydrogen demand in the energy hub network is two 290-kW electrolysers and four 30-kg tanks, respectively. The average daily strike price of electricity by which the electrolyser operates is $0.036 per kWh and will not operate when the average hourly Ontario electricity price is higher than $0.13 per kWh. The levelized cost of hydrogen produced by hydrogen refueling station is estimated to be $6.74 per kg. Moreover, the optimal operation of energy conversion and energy storage technologies within each hub and the optimal interaction between energy hubs with in the network are also investigated. In addition, it is shown that distributed hydrogen generation is more preferable than H2 delivery in environmental and economic comparison.