With the establishment of labor market of China, market is playing a more and mare important role in allocation of human resources. However, with the transition of economy in China and industrial upgrading in recent y...With the establishment of labor market of China, market is playing a more and mare important role in allocation of human resources. However, with the transition of economy in China and industrial upgrading in recent years, many labor problems have occurred which do harm to the sustainable development of local economy. The paper researches on the labor market issues of China from the perspective of local labor market regulation. Firstly, it reviews the theories of local labor market regulation. And then the main components of local labor market regulation of China are identified and the evaluation index system is established. The results of analysis of the calculated output show that （1） the local labor market regulation of China has an obvious character of gradient distribution geographically and decreases gradually from east to west; （2） of all the regulations, the regulation of the development of human capital has the most significant impact on local economy currently which is followed by the regulation of labor relation and the regulation of market participation. As to the regulation of social security, it has no Significant impact on the development of local economy.展开更多
As a promising solution to address the“energy trilemma”confronting human society,peer-to-peer(P2P)energy trading has emerged and rapidly developed in recent years.When carrying out P2P energy trading,customers with ...As a promising solution to address the“energy trilemma”confronting human society,peer-to-peer(P2P)energy trading has emerged and rapidly developed in recent years.When carrying out P2P energy trading,customers with distributed energy resources(DERs)are able to directly trade and share energy with each other.This paper summarizes and analyzes the global development of P2P energy trading based on a comprehensive review of related academic papers,research projects,and industrial practice.Key aspects in P2P energy trading are identified and discussed,including market design,trading platforms,physical infrastructure and information and communication technology(ICT)infrastructure,social science perspectives,and policy.For each key aspect,existing research and practice are critically reviewed and insights for future development are presented.Comprehensive concluding remarks are provided at the end,summarizing the major findings and perspectives of this paper.P2P energy trading is a growing field with great potential and opportunities for both academia and industry across the world.展开更多
Promotion is becoming one of the most commonly and intentionally used by local government element of marketing mix. It can be either internal （addressed to the inhabitants of the unit） or external （aimed at people ...Promotion is becoming one of the most commonly and intentionally used by local government element of marketing mix. It can be either internal （addressed to the inhabitants of the unit） or external （aimed at people who are not residents of the unit）. The subject of the presented studies will be culture promotion of the region. One of the areas of promotion, little appreciated in Poland so far, is culture and culture heritage which are of greater and greater importance for the regional development. Culture heritage can be a resource to strengthen the region and improve the conditions for economic growth. Culture goods constitute an important factor in the development of socio-economic region. They increase tourist attractiveness contributing to the development of tourism and agro-tourism in the area. The rich history, multi-layered and diverse culture heritage, both tangible and intangible, can be one of the main assets of raising the competitiveness of the given region in the country and the European Union （EU）. It should be assumed that in a market economy town or municipality operate in a manner similar to enterprise, they produce products and services offered to the internal market （municipality） as well as to external one （surrounding of the municipality）. Competitive conditions require the use of all tools to increase the effectiveness of the operation, including marketing tools. Being a marketing issue a product, which is offered by a city/town, can be considered in two aspects： first as a mega-product （i.e., a city/town as a whole）, second as a distribution of a mega-product for individual municipal sub-products. Presented concept of a product offered by a city in its two distinctions can be also applied to a municipality. Market-based approach in relation to territorial units is usually called ＂territorial marketing＂. Alternatively, they can be also called ＂spatial marketing＂ and ＂area marketing＂. Depending on the type of territorial units and the scope of marketing activities various concepts are used （e.g., urban marketing and municipal marketing）. Currently in Poland these concepts are generally related to basic units of the administrative division of the country namely to urban and rural municipalities. Therefore, for this type of activities one can suggest the term ＂municipal marketing＂.展开更多
The article presents the development unemployment and interest rates against the average of important economic variables such as GDP dynamics, transaction prices in one of the local property markets in Poland in the y...The article presents the development unemployment and interest rates against the average of important economic variables such as GDP dynamics, transaction prices in one of the local property markets in Poland in the years 2000-2002. The strength, direction and time delay of the relationships between these variables and transaction prices have been considered during the only period of decline in property prices in the years 2000-2002. The specified relationships have been described using linear regression equations.展开更多
The chosen study mainly concerns on the migration issue,which has become a phenomenon in the European Union’s political economy in the contemporary era,within the recent years,which identifies the role of migrants in...The chosen study mainly concerns on the migration issue,which has become a phenomenon in the European Union’s political economy in the contemporary era,within the recent years,which identifies the role of migrants in Azerbaijani labor market and other areas of economic integration involving the current trends,challenges,and perspectives in the political or socio-economic fields.The long-brewing Civil War in Syria created a large-scale trajectory of migrants,resulting in a massive influx of refugees from Turkey to Greece and then to Germany.Recently,the issue of migration is now transforming into a phenomenon among the member states of the European Union prompting them to take immediate action and make crucial decisions in the country’s political economy.As a result,modern migration can play a pivotal role both for the EU and for Azerbaijan in the direction of flow of people,capital and services,remittances,improving socio-economic well-being and the cheap labor force in the international labor market.The key criterion of the study is to identify specific ways in which persons or migrants who are involved in the migration process can be able to also contribute to the sustainable economic development of the region by positively influencing IDPs on the local population,labor market activities,and overall political and economic activity.The main idea behind the research is to investigate the economic integration of immigrants in Azerbaijan through its original theoretical and empirical study of migration that plays an important role in the EU’s political economy.The research aims to better regulate labor migration processes in Azerbaijan with the help of the European Union and to optimize the impact on labor productivity in the country by providing economic integration of migrants in the local labor market.The main focus of this study is to identify the role of the European Union in the economic integration of immigrants in Azerbaijan,the legal migration and migration process,based on the Joint Declaration on Resettlement Partnership launched between the EU and Azerbaijan.展开更多
Scenario generation is a critical step in stochastic programming for energy systems applications,where accurate representation of uncertainty directly impacts the decision quality.Normalizing flows(NFs),a class of inv...Scenario generation is a critical step in stochastic programming for energy systems applications,where accurate representation of uncertainty directly impacts the decision quality.Normalizing flows(NFs),a class of invertible deep generative models,offer flexibility in learning complex distributions by maximizing the likelihood,but often suffer from limited accuracy in reproducing key statistical properties of real-world data.In this work we propose a moments-informed Normalizing Flows(MI-NF)framework,in which moment constraints are incorporated into the NF training process to improve the accuracy of scenario-based probabilistic forecasts.thermore,Fur-Gaussian Processes(GPs)are employed to adaptively determine the moment regularization weight.Case studies on the open-access dataset of the Global Energy Forecasting Competition 2014 demonstrate that scenarios generated by the MI-NF model achieve over 40%lower mean absolute error on the testing set.When applied within a stochastic programming framework for a local electricity-hydrogen market,the improved scenario accuracy leads to more cost-effective and robust operational decisions under uncertainty.展开更多
With an increase in the electrification of end-use sectors,various resources on the demand side provide great flexibility potential for system operation,which also leads to problems such as the strong randomness of po...With an increase in the electrification of end-use sectors,various resources on the demand side provide great flexibility potential for system operation,which also leads to problems such as the strong randomness of power consumption behavior,the low utilization rate of flexible resources,and difficulties in cost recovery.With the core idea of“access over ownership”,the concept of the sharing economy has gained substantial popularity in the local energy market in recent years.Thus,we provide an overview of the potential market design for the sharing economy in local energy markets(LEMs)and conduct a detailed review of research related to local energy sharing,enabling technologies,and potential practices.This paper can provide a useful reference and insights for the activation of demand-side flexibility potential.Hopefully,this paper can also provide novel insights into the development and further integration of the sharing economy in LEMs.展开更多
It is expected that multiple virtual power plants(multi-VPPs)will join and participate in the future local energy market(LEM).The trading behaviors of these VPPs needs to be carefully studied in order to maximize the ...It is expected that multiple virtual power plants(multi-VPPs)will join and participate in the future local energy market(LEM).The trading behaviors of these VPPs needs to be carefully studied in order to maximize the benefits brought to the local energy market operator(LEMO)and each VPP.We propose a bounded rationality-based trading model of multiVPPs in the local energy market by using a dynamic game approach with different trading targets.Three types of power bidding models for VPPs are first set up with different trading targets.In the dynamic game process,VPPs can also improve the degree of rationality and then find the most suitable target for different requirements by evolutionary learning after considering the opponents’bidding strategies and its own clustered resources.LEMO would decide the electricity buying/selling price in the LEM.Furthermore,the proposed dynamic game model is solved by a hybrid method consisting of an improved particle swarm optimization(IPSO)algorithm and conventional largescale optimization.Finally,case studies are conducted to show the performance of the proposed model and solution approach,which may provide some insights for VPPs to participate in the LEM in real-world complex scenarios.展开更多
High penetration of renewable energy generation(REG)in the distribution system increases both the power uncertainty at a given interval and the power variation between two intervals.Reserve markets addressing power un...High penetration of renewable energy generation(REG)in the distribution system increases both the power uncertainty at a given interval and the power variation between two intervals.Reserve markets addressing power uncertainty have been widely investigated.However,there is a lack of market mechanisms regarding the power variation of the load and REGs.This paper thus defines a planned ramping(PR)product to follow the net load variation and extends the local energy market to include the trading of PR products.Players are economically compensated for their PR products.Bidding models of dispatchable generators and flexible load aggregators in the joint market are investigated.To solve the market problem in polynomial time,a distributed market clearing method is developed based on the ADMM algorithm.The joint market is tested on a modified IEEE 33-bus system.It verifies that introducing the PR market can encourage flexible loads to provide more PR service to accommodate the net load variation.As such,the ramping cost of dispatchable generators is reduced by 29.09%in the test case.The planned energy curtailment from REG is also reduced.The computational efficiency of the proposed distributed clearing method is validated by comparing it with a centralized method.展开更多
This paper proposes a novel approach for the provision of non-frequency ancillary service(AS)by consumers connected to low-voltage distribution networks.The proposed approach considers an asymmetric pool-based local m...This paper proposes a novel approach for the provision of non-frequency ancillary service(AS)by consumers connected to low-voltage distribution networks.The proposed approach considers an asymmetric pool-based local market for AS negotiation,allowing consumers to set a flexibility quantity and desired price to trade.A case study with 98 consumers illustrates the proposed market-based non-frequency AS provision approach.Also,three different strategies of consumers’participation are implemented and tested in a real low-voltage distribution network with radial topology.It is shown that consumers can make a profit from the sale of their flexibility while contributing to keeping the network power losses,voltage,and current within pre-defined limits.Ultimately,the results demonstrate the value of AS coming directly from end-users.展开更多
In the past three decades, the Chinese hotel industry has developed at a rapid pace, with the number of hotels-especially high star hotels-growing fast.
Local energy markets are emerging as a tool for coordinating generation, storage, and consumption of energyfrom distributed resources. In combination with automation, they promise to provide an effective energymanagem...Local energy markets are emerging as a tool for coordinating generation, storage, and consumption of energyfrom distributed resources. In combination with automation, they promise to provide an effective energymanagement framework that is fair and brings system-level savings. The cooperative–competitive natureof energy markets calls for multi-agent based automation with learning energy trading agents. However,depending on the dynamics of the agent–environment interaction, this approach may yield unintended behaviorof market participants. Thus, the design of market mechanisms suitable for reinforcement learning agentsmust take into account this interplay. This article introduces autonomous local energy exchange (ALEX) asan experimental framework that combines multi-agent learning and double auction mechanism. Participantsdetermine their internal price signals and make energy management decisions through market interactions,rather than relying on predetermined external price signals. The main contribution of this article is examinationof compatibility between specific market elements and independent learning agents. Effects of different marketproperties are evaluated through simulation experiments, and the results are used for determine a suitablemarket design. The results show that market truthfulness maintains demand-response functionality, while weakbudget balancing provides a strong reinforcement signal for the learning agents. The resulting agent behavioris compared with two baselines: net billing and time-of-use rates. The ALEX-based pricing is more responsiveto fluctuations in the community net load compared to the time-of-use. The more accurate accounting ofrenewable energy usage reduced bills by a median 38.8% compared to net billing, confirming the ability tobetter facilitate demand response.展开更多
As the energy landscape evolves towards sustainability,the accelerating integration of distributed energy resources poses challenges to the operability and reliability of the electricity grid.One significant aspect of...As the energy landscape evolves towards sustainability,the accelerating integration of distributed energy resources poses challenges to the operability and reliability of the electricity grid.One significant aspect of this issue is the notable increase in net load variability at the grid edge.Transactive energy,implemented through local energy markets,has recently garnered attention as a promising solution to address the grid challenges in the form of decentralized,indirect demand response on a community level.Model-free control approaches,such as deep reinforcement learning(DRL),show promise for the decentralized automation of participation within this context.Existing studies at the intersection of transactive energy and model-free control primarily focus on socioeconomic and self-consumption metrics,overlooking the crucial goal of reducing community-level net load variability.This study addresses this gap by training a set of deep reinforcement learning agents to automate end-user participation in an economy-driven,autonomous local energy market(ALEX).In this setting,agents do not share information and only prioritize individual bill optimization.The study unveils a clear correlation between bill reduction and reduced net load variability.The impact on net load variability is assessed over various time horizons using metrics such as ramping rate,daily and monthly load factor,as well as daily average and total peak export and import on an open-source dataset.To examine the performance of the proposed DRL method,its agents are benchmarked against a optimal near-dynamic programming method,using a no-control scenario as the baseline.The dynamic programming benchmark reduces average daily import,export,and peak demand by 22.05%,83.92%,and 24.09%,respectively.The RL agents demonstrate comparable or superior performance,with improvements of 21.93%,84.46%,and 27.02%on these metrics.This demonstrates that DRL can be effectively employed for such tasks,as they are inherently scalable with near-optimal performance in decentralized grid management.展开更多
Distributed energy resources,connected to power distribution systems,are increasingly operated by ligent/intellearning agents.Such agents,looking to optimize their own payoff,can discover harmful ways to exploit the s...Distributed energy resources,connected to power distribution systems,are increasingly operated by ligent/intellearning agents.Such agents,looking to optimize their own payoff,can discover harmful ways to exploit the system.Hence,shielding critical systems of harmful agent behavior is of crucial importance.In this paper,the problem of designing an efficient operating mechanism for a power distribution system is taken on,considering the realistic case where the system’s resources do not possess this information and instead learn to improve their policies through experience.To that end,a multi-agent reinforcement learning algorithm is developed to model the participants’learning-to-act process and consider the agents’learning under different pricing schemes that shape the agents’reward functions.Two popular pricing schemes bid(pay-as-and distribution locational marginal pricing)are presented,exposing that learning agents can discover ways to exploit them,resulting in severe dispatch inefficiency.A game-theoretic pricing scheme is presented that theoretically incentivizes truthful agent behavior,and empirically demonstrate that this property improves the efficiency of the resulting dispatch also in the presence of learning agents.In particular,the proposed scheme is able to outperform the popular distribution locational marginal pricing scheme,in terms of efficiency,by a factor of 15-17%.展开更多
More customers are tending to install batteries with photovoltaic(PV), so they can better control their electricity bills. In this context, customers may be tempted to go offgrid at a substantial up-front cost, leadin...More customers are tending to install batteries with photovoltaic(PV), so they can better control their electricity bills. In this context, customers may be tempted to go offgrid at a substantial up-front cost, leading electricity companies into a death spiral, thereby raising electricity price further on those remaining on grid. Neighborhood energy markets can promote the sharing of locally generated renewable energy and encourage prosumers to stay on grid with financial incentives. A novel neighborhood energy trading(NET) mechanism is developed using the topology of existing radial distribution network to encourage sustainable energy sharing in neighborhood and encourage prosumers to stay on grid. This mechanism considers loss, congestion management, and voltage regulation, and it is scalable with low computation and communication overhead.An IEEE test system is used to validate the NET mechanism.The simulation shows that the price and flow results are obtained with fast computation speed(within 10 iterations) and with loss reflected, flow limit reinforced, and voltage regulated.This study proves that the economic demand-supply-based pricing mechanism can be applied effectively in distribution networks to help encourage more renewable energy sharing in sustainable neighborhood and avoid energy network death spiral.展开更多
基金supported by Knowledge Innovation Program of The Chinese Academy of Sciences (Grant No. O7Q70100AD).
文摘With the establishment of labor market of China, market is playing a more and mare important role in allocation of human resources. However, with the transition of economy in China and industrial upgrading in recent years, many labor problems have occurred which do harm to the sustainable development of local economy. The paper researches on the labor market issues of China from the perspective of local labor market regulation. Firstly, it reviews the theories of local labor market regulation. And then the main components of local labor market regulation of China are identified and the evaluation index system is established. The results of analysis of the calculated output show that （1） the local labor market regulation of China has an obvious character of gradient distribution geographically and decreases gradually from east to west; （2） of all the regulations, the regulation of the development of human capital has the most significant impact on local economy currently which is followed by the regulation of labor relation and the regulation of market participation. As to the regulation of social security, it has no Significant impact on the development of local economy.
基金the Horizon 2020 project P2P-SmarTest,EPSRC Supergen Hub on Energy Networks(EP/S00078X/1)and MISTRAL(EP/N017064/1).
文摘As a promising solution to address the“energy trilemma”confronting human society,peer-to-peer(P2P)energy trading has emerged and rapidly developed in recent years.When carrying out P2P energy trading,customers with distributed energy resources(DERs)are able to directly trade and share energy with each other.This paper summarizes and analyzes the global development of P2P energy trading based on a comprehensive review of related academic papers,research projects,and industrial practice.Key aspects in P2P energy trading are identified and discussed,including market design,trading platforms,physical infrastructure and information and communication technology(ICT)infrastructure,social science perspectives,and policy.For each key aspect,existing research and practice are critically reviewed and insights for future development are presented.Comprehensive concluding remarks are provided at the end,summarizing the major findings and perspectives of this paper.P2P energy trading is a growing field with great potential and opportunities for both academia and industry across the world.
文摘Promotion is becoming one of the most commonly and intentionally used by local government element of marketing mix. It can be either internal （addressed to the inhabitants of the unit） or external （aimed at people who are not residents of the unit）. The subject of the presented studies will be culture promotion of the region. One of the areas of promotion, little appreciated in Poland so far, is culture and culture heritage which are of greater and greater importance for the regional development. Culture heritage can be a resource to strengthen the region and improve the conditions for economic growth. Culture goods constitute an important factor in the development of socio-economic region. They increase tourist attractiveness contributing to the development of tourism and agro-tourism in the area. The rich history, multi-layered and diverse culture heritage, both tangible and intangible, can be one of the main assets of raising the competitiveness of the given region in the country and the European Union （EU）. It should be assumed that in a market economy town or municipality operate in a manner similar to enterprise, they produce products and services offered to the internal market （municipality） as well as to external one （surrounding of the municipality）. Competitive conditions require the use of all tools to increase the effectiveness of the operation, including marketing tools. Being a marketing issue a product, which is offered by a city/town, can be considered in two aspects： first as a mega-product （i.e., a city/town as a whole）, second as a distribution of a mega-product for individual municipal sub-products. Presented concept of a product offered by a city in its two distinctions can be also applied to a municipality. Market-based approach in relation to territorial units is usually called ＂territorial marketing＂. Alternatively, they can be also called ＂spatial marketing＂ and ＂area marketing＂. Depending on the type of territorial units and the scope of marketing activities various concepts are used （e.g., urban marketing and municipal marketing）. Currently in Poland these concepts are generally related to basic units of the administrative division of the country namely to urban and rural municipalities. Therefore, for this type of activities one can suggest the term ＂municipal marketing＂.
文摘The article presents the development unemployment and interest rates against the average of important economic variables such as GDP dynamics, transaction prices in one of the local property markets in Poland in the years 2000-2002. The strength, direction and time delay of the relationships between these variables and transaction prices have been considered during the only period of decline in property prices in the years 2000-2002. The specified relationships have been described using linear regression equations.
文摘The chosen study mainly concerns on the migration issue,which has become a phenomenon in the European Union’s political economy in the contemporary era,within the recent years,which identifies the role of migrants in Azerbaijani labor market and other areas of economic integration involving the current trends,challenges,and perspectives in the political or socio-economic fields.The long-brewing Civil War in Syria created a large-scale trajectory of migrants,resulting in a massive influx of refugees from Turkey to Greece and then to Germany.Recently,the issue of migration is now transforming into a phenomenon among the member states of the European Union prompting them to take immediate action and make crucial decisions in the country’s political economy.As a result,modern migration can play a pivotal role both for the EU and for Azerbaijan in the direction of flow of people,capital and services,remittances,improving socio-economic well-being and the cheap labor force in the international labor market.The key criterion of the study is to identify specific ways in which persons or migrants who are involved in the migration process can be able to also contribute to the sustainable economic development of the region by positively influencing IDPs on the local population,labor market activities,and overall political and economic activity.The main idea behind the research is to investigate the economic integration of immigrants in Azerbaijan through its original theoretical and empirical study of migration that plays an important role in the EU’s political economy.The research aims to better regulate labor migration processes in Azerbaijan with the help of the European Union and to optimize the impact on labor productivity in the country by providing economic integration of migrants in the local labor market.The main focus of this study is to identify the role of the European Union in the economic integration of immigrants in Azerbaijan,the legal migration and migration process,based on the Joint Declaration on Resettlement Partnership launched between the EU and Azerbaijan.
基金support from the Engineering&Physical Sciences Re-search Council(EPSRC),UK under the projects EP/T022930/1,EP/W003317/1 and EP/V051008/1,is gratefully acknowledged.
文摘Scenario generation is a critical step in stochastic programming for energy systems applications,where accurate representation of uncertainty directly impacts the decision quality.Normalizing flows(NFs),a class of invertible deep generative models,offer flexibility in learning complex distributions by maximizing the likelihood,but often suffer from limited accuracy in reproducing key statistical properties of real-world data.In this work we propose a moments-informed Normalizing Flows(MI-NF)framework,in which moment constraints are incorporated into the NF training process to improve the accuracy of scenario-based probabilistic forecasts.thermore,Fur-Gaussian Processes(GPs)are employed to adaptively determine the moment regularization weight.Case studies on the open-access dataset of the Global Energy Forecasting Competition 2014 demonstrate that scenarios generated by the MI-NF model achieve over 40%lower mean absolute error on the testing set.When applied within a stochastic programming framework for a local electricity-hydrogen market,the improved scenario accuracy leads to more cost-effective and robust operational decisions under uncertainty.
文摘With an increase in the electrification of end-use sectors,various resources on the demand side provide great flexibility potential for system operation,which also leads to problems such as the strong randomness of power consumption behavior,the low utilization rate of flexible resources,and difficulties in cost recovery.With the core idea of“access over ownership”,the concept of the sharing economy has gained substantial popularity in the local energy market in recent years.Thus,we provide an overview of the potential market design for the sharing economy in local energy markets(LEMs)and conduct a detailed review of research related to local energy sharing,enabling technologies,and potential practices.This paper can provide a useful reference and insights for the activation of demand-side flexibility potential.Hopefully,this paper can also provide novel insights into the development and further integration of the sharing economy in LEMs.
基金This work was supported by the National Key R&D Program of China(Grant No.2019YFE0123600)National Science Foundation of China(Grant No.52077146)Young Elite Scientists Sponsorship Program by CSEE(Grant No.CESS-YESS-2019027).
文摘It is expected that multiple virtual power plants(multi-VPPs)will join and participate in the future local energy market(LEM).The trading behaviors of these VPPs needs to be carefully studied in order to maximize the benefits brought to the local energy market operator(LEMO)and each VPP.We propose a bounded rationality-based trading model of multiVPPs in the local energy market by using a dynamic game approach with different trading targets.Three types of power bidding models for VPPs are first set up with different trading targets.In the dynamic game process,VPPs can also improve the degree of rationality and then find the most suitable target for different requirements by evolutionary learning after considering the opponents’bidding strategies and its own clustered resources.LEMO would decide the electricity buying/selling price in the LEM.Furthermore,the proposed dynamic game model is solved by a hybrid method consisting of an improved particle swarm optimization(IPSO)algorithm and conventional largescale optimization.Finally,case studies are conducted to show the performance of the proposed model and solution approach,which may provide some insights for VPPs to participate in the LEM in real-world complex scenarios.
文摘High penetration of renewable energy generation(REG)in the distribution system increases both the power uncertainty at a given interval and the power variation between two intervals.Reserve markets addressing power uncertainty have been widely investigated.However,there is a lack of market mechanisms regarding the power variation of the load and REGs.This paper thus defines a planned ramping(PR)product to follow the net load variation and extends the local energy market to include the trading of PR products.Players are economically compensated for their PR products.Bidding models of dispatchable generators and flexible load aggregators in the joint market are investigated.To solve the market problem in polynomial time,a distributed market clearing method is developed based on the ADMM algorithm.The joint market is tested on a modified IEEE 33-bus system.It verifies that introducing the PR market can encourage flexible loads to provide more PR service to accommodate the net load variation.As such,the ramping cost of dispatchable generators is reduced by 29.09%in the test case.The planned energy curtailment from REG is also reduced.The computational efficiency of the proposed distributed clearing method is validated by comparing it with a centralized method.
基金supported by the EU Horizon 2020 research and innovation program under project DOMINOES(No.771066)FEDER Funds through COMPETE program and National Funds through FCT under projects UID/EEA/00760/2019 and CEECIND/01811/2017supported by the Ph.D.grant SFRH/BD/133086/2017。
文摘This paper proposes a novel approach for the provision of non-frequency ancillary service(AS)by consumers connected to low-voltage distribution networks.The proposed approach considers an asymmetric pool-based local market for AS negotiation,allowing consumers to set a flexibility quantity and desired price to trade.A case study with 98 consumers illustrates the proposed market-based non-frequency AS provision approach.Also,three different strategies of consumers’participation are implemented and tested in a real low-voltage distribution network with radial topology.It is shown that consumers can make a profit from the sale of their flexibility while contributing to keeping the network power losses,voltage,and current within pre-defined limits.Ultimately,the results demonstrate the value of AS coming directly from end-users.
文摘In the past three decades, the Chinese hotel industry has developed at a rapid pace, with the number of hotels-especially high star hotels-growing fast.
文摘Local energy markets are emerging as a tool for coordinating generation, storage, and consumption of energyfrom distributed resources. In combination with automation, they promise to provide an effective energymanagement framework that is fair and brings system-level savings. The cooperative–competitive natureof energy markets calls for multi-agent based automation with learning energy trading agents. However,depending on the dynamics of the agent–environment interaction, this approach may yield unintended behaviorof market participants. Thus, the design of market mechanisms suitable for reinforcement learning agentsmust take into account this interplay. This article introduces autonomous local energy exchange (ALEX) asan experimental framework that combines multi-agent learning and double auction mechanism. Participantsdetermine their internal price signals and make energy management decisions through market interactions,rather than relying on predetermined external price signals. The main contribution of this article is examinationof compatibility between specific market elements and independent learning agents. Effects of different marketproperties are evaluated through simulation experiments, and the results are used for determine a suitablemarket design. The results show that market truthfulness maintains demand-response functionality, while weakbudget balancing provides a strong reinforcement signal for the learning agents. The resulting agent behavioris compared with two baselines: net billing and time-of-use rates. The ALEX-based pricing is more responsiveto fluctuations in the community net load compared to the time-of-use. The more accurate accounting ofrenewable energy usage reduced bills by a median 38.8% compared to net billing, confirming the ability tobetter facilitate demand response.
基金supported by the Natural Sciences and Engineering Research Council(NSERC)of Canada grant RGPIN-2024-04565by the NSERC/Alberta Innovates grant ALLRP 561116-20+5 种基金Part of this work has taken place in the Intelligent Robot Learning(IRL)Lab at the University of Alberta,which is supported in part by research grants from the Alberta Machine Intelligence Institute(Amii),Canadaa Canada CIFAR AI Chair,AmiiDigital Research Alliance of CanadaHuaweiMitacs,Canadaand NSERC,Canada.
文摘As the energy landscape evolves towards sustainability,the accelerating integration of distributed energy resources poses challenges to the operability and reliability of the electricity grid.One significant aspect of this issue is the notable increase in net load variability at the grid edge.Transactive energy,implemented through local energy markets,has recently garnered attention as a promising solution to address the grid challenges in the form of decentralized,indirect demand response on a community level.Model-free control approaches,such as deep reinforcement learning(DRL),show promise for the decentralized automation of participation within this context.Existing studies at the intersection of transactive energy and model-free control primarily focus on socioeconomic and self-consumption metrics,overlooking the crucial goal of reducing community-level net load variability.This study addresses this gap by training a set of deep reinforcement learning agents to automate end-user participation in an economy-driven,autonomous local energy market(ALEX).In this setting,agents do not share information and only prioritize individual bill optimization.The study unveils a clear correlation between bill reduction and reduced net load variability.The impact on net load variability is assessed over various time horizons using metrics such as ramping rate,daily and monthly load factor,as well as daily average and total peak export and import on an open-source dataset.To examine the performance of the proposed DRL method,its agents are benchmarked against a optimal near-dynamic programming method,using a no-control scenario as the baseline.The dynamic programming benchmark reduces average daily import,export,and peak demand by 22.05%,83.92%,and 24.09%,respectively.The RL agents demonstrate comparable or superior performance,with improvements of 21.93%,84.46%,and 27.02%on these metrics.This demonstrates that DRL can be effectively employed for such tasks,as they are inherently scalable with near-optimal performance in decentralized grid management.
文摘Distributed energy resources,connected to power distribution systems,are increasingly operated by ligent/intellearning agents.Such agents,looking to optimize their own payoff,can discover harmful ways to exploit the system.Hence,shielding critical systems of harmful agent behavior is of crucial importance.In this paper,the problem of designing an efficient operating mechanism for a power distribution system is taken on,considering the realistic case where the system’s resources do not possess this information and instead learn to improve their policies through experience.To that end,a multi-agent reinforcement learning algorithm is developed to model the participants’learning-to-act process and consider the agents’learning under different pricing schemes that shape the agents’reward functions.Two popular pricing schemes bid(pay-as-and distribution locational marginal pricing)are presented,exposing that learning agents can discover ways to exploit them,resulting in severe dispatch inefficiency.A game-theoretic pricing scheme is presented that theoretically incentivizes truthful agent behavior,and empirically demonstrate that this property improves the efficiency of the resulting dispatch also in the presence of learning agents.In particular,the proposed scheme is able to outperform the popular distribution locational marginal pricing scheme,in terms of efficiency,by a factor of 15-17%.
基金supported in part by the Australian Research Council Discovery Project (No. 160102570)。
文摘More customers are tending to install batteries with photovoltaic(PV), so they can better control their electricity bills. In this context, customers may be tempted to go offgrid at a substantial up-front cost, leading electricity companies into a death spiral, thereby raising electricity price further on those remaining on grid. Neighborhood energy markets can promote the sharing of locally generated renewable energy and encourage prosumers to stay on grid with financial incentives. A novel neighborhood energy trading(NET) mechanism is developed using the topology of existing radial distribution network to encourage sustainable energy sharing in neighborhood and encourage prosumers to stay on grid. This mechanism considers loss, congestion management, and voltage regulation, and it is scalable with low computation and communication overhead.An IEEE test system is used to validate the NET mechanism.The simulation shows that the price and flow results are obtained with fast computation speed(within 10 iterations) and with loss reflected, flow limit reinforced, and voltage regulated.This study proves that the economic demand-supply-based pricing mechanism can be applied effectively in distribution networks to help encourage more renewable energy sharing in sustainable neighborhood and avoid energy network death spiral.
