Remote areas of Nepal suffer from limited or no access to electricity.Providing electricity access in remote areas is one of the foremost challenges of any developing country.The purpose of this study is to develop an...Remote areas of Nepal suffer from limited or no access to electricity.Providing electricity access in remote areas is one of the foremost challenges of any developing country.The purpose of this study is to develop and propose a reliable and low-cost model for electrification.The study presents an optimized choice between decentralized renewable-energy systems and grid expansion.Opting for an analytical method for the modelling and analysis of electrification options based on life-cycle cost(LCC)and economic distance limit,each energy system for varied load conditions is compared for a better option.A framework for energy-system selection based on available resources is proposed.It compares the grid-expansion option with potential isolated renewable-energy systems to ensure energy access to the area under consideration.Additionally,off-grid configurations that rely on renewable energy sources are also considered for the necessity of backup supply to ensure continuous power to the research area.Techno-economic assessment is carried out for different off-grid and hybrid configurations proposed in this study and their feasibility checks are carefully examined.Commercial efficacy of the proposed hybrid energy systems is assessed by comparing the life cycle and energy cost and by performing different additional sensitivity analyses.The study concludes that reduced generation cost supports the increasing penetration of electrification.The LCC for grid expansion is the most economical under high-load conditions,whereas for the isolated and sparsely settled populations with low-load conditions,photovoltaic power backed up with a diesel generator is the most economical.展开更多
https://www.sciencedirect.com/journal/energy-and-buildings/vol/337/suppl/C Volume 337,15 June 2025[OA](1)From flexible building to resilient energy communities:A scalable decentralized energy management scheme based o...https://www.sciencedirect.com/journal/energy-and-buildings/vol/337/suppl/C Volume 337,15 June 2025[OA](1)From flexible building to resilient energy communities:A scalable decentralized energy management scheme based on collaborative agents by Mohammad Hosseini,Silvia Erba,Ahmad Mazaheri,et al,Article 115651 Abstract:Extreme conditions caused by climate change and other crises call for enhancing the resilience of buildings and urban energy systems.展开更多
Achieving SDG 7(Sustainable Development Goal 7)-ensuring universal access to clean,reliable,and affordable energy-requires technological innovations that can address technical,economic,and social challenges.Blockchain...Achieving SDG 7(Sustainable Development Goal 7)-ensuring universal access to clean,reliable,and affordable energy-requires technological innovations that can address technical,economic,and social challenges.Blockchain technology,with its inherent transparency,decentralization,and traceability,is emerging as a potential catalyst for accelerating this transition.This paper examines the main blockchain applications in the energy sector that support SDG 7,including solutions for decentralized grid management,renewable energy tracking,peer-to-peer energy trading,and innovative financing and incentive mechanisms.This research also investigates a set of case studies from diverse geographical and regulatory contexts,aiming to assess the effectiveness,scalability,and sustainability of ongoing initiatives.The academic implications of this paper lie in advancing the theoretical debate on integrating decentralized technologies into energy systems.Managerial and policy implications relate to strategies,business models,and regulations that enable the adoption of blockchain solutions consistent with global sustainability goals.展开更多
Following global catastrophic infrastructure loss(GCIL),traditional electricity networks would be damaged and unavailable for energy supply,necessitating alternative solutions to sustain critical services.These altern...Following global catastrophic infrastructure loss(GCIL),traditional electricity networks would be damaged and unavailable for energy supply,necessitating alternative solutions to sustain critical services.These alternative solutions would need to run without damaged infrastructure and would likely need to be located at the point of use,such as decentralized electricity generation from wood gas.This study explores the feasibility of using modified light duty vehicles to self-sustain electricity generation by producing wood chips for wood gasification.A 2004 Ford Falcon Fairmont was modified to power a woodchipper and an electrical generator.The vehicle successfully produced wood chips suitable for gasification with an energy return on investment(EROI)of 3.7 and sustained a stable output of 20 kW electrical power.Scalability analyses suggest such solutions could provide electricity to the critical water sanitation sector,equivalent to 4%of global electricity demand,if production of woodchippers was increased postcatastrophe.Future research could investigate the long-term durability of modified vehicles and alternative electricity generation,and quantify the scalability of wood gasification in GCIL scenarios.This work provides a foundation for developing resilient,decentralized energy systems to ensure the continuity of critical services during catastrophic events,leveraging existing vehicle infrastructure to enhance disaster preparedness.展开更多
In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent...In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.展开更多
A decentralized battery energy storage system(DBESS)is used for stabilizing power fluctuation in DC microgrids.Different state of charge(SoC)among various battery energy storage units(BESU)during operation will reduce...A decentralized battery energy storage system(DBESS)is used for stabilizing power fluctuation in DC microgrids.Different state of charge(SoC)among various battery energy storage units(BESU)during operation will reduce batteries’service life.A hierarchical distributed control method is proposed in this paper for SoC balancing and power control according to dispatching center requirement in DBESS.A consensus algorithm with pinning node is employed to allocate power among BESUs in the secondary control whereas in the primary control,the local controller of BESU adjusts output power according to the reference power from secondary control.Part of BESUs are selected to be pinning node for accepting command from dispatching center while other BESUs as following nodes which exchange output power and SoC information with the adjacent nodes through communication network.After calculating reference power of each BESU by adopting consensus algorithm,the power sharing in DBESS is achieved according to their respective SoC of BESUs.Meanwhile,the total output power of DBESS follows the varying requirements of dispatching center.The stability of DBESS is also improved because of having no center controller.The feasibility of the proposed control strategy is validated by simulation results.展开更多
Efficient and economic reuse of waste is one of the pillars of modern environmental engineering. In the field of domestic sewage management,source separation of yellow（urine）,brown（faecal matter）and grey waters ai...Efficient and economic reuse of waste is one of the pillars of modern environmental engineering. In the field of domestic sewage management,source separation of yellow（urine）,brown（faecal matter）and grey waters aims to recover the organic substances concentrated in brown water,the nutrients（nitrogen and phosphorous）in the urine and to ensure an easier treatment and recycling of grey waters. With the objective of emphasizing the potential of recovery of resources from sewage management,a lab-scale research study was carried out at the University of Padova in order to evaluate the performances of oleaginous plants（suitable for biodiesel production）in the phytotreatment of source separated yellow and grey waters. The plant species used were Brassica napus（rapeseed）,Glycine max（soybean）and Helianthus annuus（sunflower）. Phytotreatment tests were carried out using 20 L pots. Different testing runs were performed at an increasing nitrogen concentration in the feedstock. The results proved that oleaginous species can conveniently be used for the phytotreatment of grey and yellow waters from source separation of domestic sewage,displaying high removal efficiencies of nutrients and organic substances（nitrogen 〉 80%; phosphorous 〉 90%; COD nearly 90%）. No inhibition was registered in the growth of plants irrigated with different mixtures of yellow and grey waters,where the characteristics of the two streams were reciprocally and beneficially integrated.展开更多
Dynamic instability of decentralized wind energy farms is a major issue to deliver continuous green energy to electricity consumers.This instability is caused by variations of voltage and frequency parameters due to i...Dynamic instability of decentralized wind energy farms is a major issue to deliver continuous green energy to electricity consumers.This instability is caused by variations of voltage and frequency parameters due to intermittencies in wind power.Previously,droop control and inverter-based schemes have been proposed to regulate the voltage by balancing reactive power,while inertial control,digital mapping tech-nique of proportional-integral-differential(PID)controller and efficiency control strategy have been developed to regulate the frequency.In this paper,voltage stability is improved by a new joint strategy of distribution static compensator(DSTATCOM)six-pulse controller based reactive power management among decentralized wind turbines and controlled charging of capacitor bank.The frequency stability is ensured by a joint coordinated utilization of capacitor bank and distributed wind power turbines dispatching through a new DSTATCOM six-pulse controller scheme.In both strategies,power grid is contributed as a backup source with less priority.These new joint strategies for voltage and frequency stabilities will enhance the stable active power delivery to end users.A system test case is developed to verify the proposed joint strategies.The test results of the proposed new schemes are proved to be effective in terms of stability improvement of voltage,frequency and active power generation.展开更多
This study utilizes machine learning and,more specifically,reinforcement learning(RL)to allow for an optimized,real-time operation of large numbers of decentral flexible assets on private household scale in the electr...This study utilizes machine learning and,more specifically,reinforcement learning(RL)to allow for an optimized,real-time operation of large numbers of decentral flexible assets on private household scale in the electricity domain.The potential and current obstacles of RL are demonstrated and a guide for interested practitioners is provided on how to tackle similar tasks without advanced skills in neural network programming.For the application in the energy domain it is demonstrated that state-of-the-art RL algorithms can be trained to control potentially millions of small-scale assets in private households.In detail,the applied RL algorithm outperforms common heuristic algorithms and only falls slightly short of the results provided by linear optimization,but at less than a thousandth of the simulation time.Thus,RL paves the way for aggregators of flexible energy assets to optimize profit over multiple use cases in a smart energy grid and thus also provide valuable grid services and a more sustainable operation of private energy assets.展开更多
文摘Remote areas of Nepal suffer from limited or no access to electricity.Providing electricity access in remote areas is one of the foremost challenges of any developing country.The purpose of this study is to develop and propose a reliable and low-cost model for electrification.The study presents an optimized choice between decentralized renewable-energy systems and grid expansion.Opting for an analytical method for the modelling and analysis of electrification options based on life-cycle cost(LCC)and economic distance limit,each energy system for varied load conditions is compared for a better option.A framework for energy-system selection based on available resources is proposed.It compares the grid-expansion option with potential isolated renewable-energy systems to ensure energy access to the area under consideration.Additionally,off-grid configurations that rely on renewable energy sources are also considered for the necessity of backup supply to ensure continuous power to the research area.Techno-economic assessment is carried out for different off-grid and hybrid configurations proposed in this study and their feasibility checks are carefully examined.Commercial efficacy of the proposed hybrid energy systems is assessed by comparing the life cycle and energy cost and by performing different additional sensitivity analyses.The study concludes that reduced generation cost supports the increasing penetration of electrification.The LCC for grid expansion is the most economical under high-load conditions,whereas for the isolated and sparsely settled populations with low-load conditions,photovoltaic power backed up with a diesel generator is the most economical.
文摘https://www.sciencedirect.com/journal/energy-and-buildings/vol/337/suppl/C Volume 337,15 June 2025[OA](1)From flexible building to resilient energy communities:A scalable decentralized energy management scheme based on collaborative agents by Mohammad Hosseini,Silvia Erba,Ahmad Mazaheri,et al,Article 115651 Abstract:Extreme conditions caused by climate change and other crises call for enhancing the resilience of buildings and urban energy systems.
文摘Achieving SDG 7(Sustainable Development Goal 7)-ensuring universal access to clean,reliable,and affordable energy-requires technological innovations that can address technical,economic,and social challenges.Blockchain technology,with its inherent transparency,decentralization,and traceability,is emerging as a potential catalyst for accelerating this transition.This paper examines the main blockchain applications in the energy sector that support SDG 7,including solutions for decentralized grid management,renewable energy tracking,peer-to-peer energy trading,and innovative financing and incentive mechanisms.This research also investigates a set of case studies from diverse geographical and regulatory contexts,aiming to assess the effectiveness,scalability,and sustainability of ongoing initiatives.The academic implications of this paper lie in advancing the theoretical debate on integrating decentralized technologies into energy systems.Managerial and policy implications relate to strategies,business models,and regulations that enable the adoption of blockchain solutions consistent with global sustainability goals.
基金This work was funded in part by the Alliance to Feed the Earth in Disasters(ALLFED).
文摘Following global catastrophic infrastructure loss(GCIL),traditional electricity networks would be damaged and unavailable for energy supply,necessitating alternative solutions to sustain critical services.These alternative solutions would need to run without damaged infrastructure and would likely need to be located at the point of use,such as decentralized electricity generation from wood gas.This study explores the feasibility of using modified light duty vehicles to self-sustain electricity generation by producing wood chips for wood gasification.A 2004 Ford Falcon Fairmont was modified to power a woodchipper and an electrical generator.The vehicle successfully produced wood chips suitable for gasification with an energy return on investment(EROI)of 3.7 and sustained a stable output of 20 kW electrical power.Scalability analyses suggest such solutions could provide electricity to the critical water sanitation sector,equivalent to 4%of global electricity demand,if production of woodchippers was increased postcatastrophe.Future research could investigate the long-term durability of modified vehicles and alternative electricity generation,and quantify the scalability of wood gasification in GCIL scenarios.This work provides a foundation for developing resilient,decentralized energy systems to ensure the continuity of critical services during catastrophic events,leveraging existing vehicle infrastructure to enhance disaster preparedness.
文摘In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.
基金The part of establishing DBESS model was supported by National Natural Science Foundation of China(61473238,51407146)the primary droop control analysis got support of Sichuan Provincial Youth Science and Technology Fund(2015JQ0016)the part of distributed consensus algorithm was supported by Doctoral Innovation Funds of Southwest Jiaotong University(D-CX201714).
文摘A decentralized battery energy storage system(DBESS)is used for stabilizing power fluctuation in DC microgrids.Different state of charge(SoC)among various battery energy storage units(BESU)during operation will reduce batteries’service life.A hierarchical distributed control method is proposed in this paper for SoC balancing and power control according to dispatching center requirement in DBESS.A consensus algorithm with pinning node is employed to allocate power among BESUs in the secondary control whereas in the primary control,the local controller of BESU adjusts output power according to the reference power from secondary control.Part of BESUs are selected to be pinning node for accepting command from dispatching center while other BESUs as following nodes which exchange output power and SoC information with the adjacent nodes through communication network.After calculating reference power of each BESU by adopting consensus algorithm,the power sharing in DBESS is achieved according to their respective SoC of BESUs.Meanwhile,the total output power of DBESS follows the varying requirements of dispatching center.The stability of DBESS is also improved because of having no center controller.The feasibility of the proposed control strategy is validated by simulation results.
文摘Efficient and economic reuse of waste is one of the pillars of modern environmental engineering. In the field of domestic sewage management,source separation of yellow（urine）,brown（faecal matter）and grey waters aims to recover the organic substances concentrated in brown water,the nutrients（nitrogen and phosphorous）in the urine and to ensure an easier treatment and recycling of grey waters. With the objective of emphasizing the potential of recovery of resources from sewage management,a lab-scale research study was carried out at the University of Padova in order to evaluate the performances of oleaginous plants（suitable for biodiesel production）in the phytotreatment of source separated yellow and grey waters. The plant species used were Brassica napus（rapeseed）,Glycine max（soybean）and Helianthus annuus（sunflower）. Phytotreatment tests were carried out using 20 L pots. Different testing runs were performed at an increasing nitrogen concentration in the feedstock. The results proved that oleaginous species can conveniently be used for the phytotreatment of grey and yellow waters from source separation of domestic sewage,displaying high removal efficiencies of nutrients and organic substances（nitrogen 〉 80%; phosphorous 〉 90%; COD nearly 90%）. No inhibition was registered in the growth of plants irrigated with different mixtures of yellow and grey waters,where the characteristics of the two streams were reciprocally and beneficially integrated.
文摘Dynamic instability of decentralized wind energy farms is a major issue to deliver continuous green energy to electricity consumers.This instability is caused by variations of voltage and frequency parameters due to intermittencies in wind power.Previously,droop control and inverter-based schemes have been proposed to regulate the voltage by balancing reactive power,while inertial control,digital mapping tech-nique of proportional-integral-differential(PID)controller and efficiency control strategy have been developed to regulate the frequency.In this paper,voltage stability is improved by a new joint strategy of distribution static compensator(DSTATCOM)six-pulse controller based reactive power management among decentralized wind turbines and controlled charging of capacitor bank.The frequency stability is ensured by a joint coordinated utilization of capacitor bank and distributed wind power turbines dispatching through a new DSTATCOM six-pulse controller scheme.In both strategies,power grid is contributed as a backup source with less priority.These new joint strategies for voltage and frequency stabilities will enhance the stable active power delivery to end users.A system test case is developed to verify the proposed joint strategies.The test results of the proposed new schemes are proved to be effective in terms of stability improvement of voltage,frequency and active power generation.
基金funding by the German Federal Ministry of Education and Research(BMBF)obtained for the Kopernikus Project“ENSURE”(funding nos.03SFK1HO and 03SFK1C0-2)as well as helpful comments received from two anonymous reviewers.
文摘This study utilizes machine learning and,more specifically,reinforcement learning(RL)to allow for an optimized,real-time operation of large numbers of decentral flexible assets on private household scale in the electricity domain.The potential and current obstacles of RL are demonstrated and a guide for interested practitioners is provided on how to tackle similar tasks without advanced skills in neural network programming.For the application in the energy domain it is demonstrated that state-of-the-art RL algorithms can be trained to control potentially millions of small-scale assets in private households.In detail,the applied RL algorithm outperforms common heuristic algorithms and only falls slightly short of the results provided by linear optimization,but at less than a thousandth of the simulation time.Thus,RL paves the way for aggregators of flexible energy assets to optimize profit over multiple use cases in a smart energy grid and thus also provide valuable grid services and a more sustainable operation of private energy assets.
