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Автор: Grafiati

Опубліковано: 6 вересня 2023

Оновлено: 7 вересня 2023

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Статті в журналах з теми "Incentive-based demand response strategies"

Deng, Chunyu, and Kehe Wu. "Residential Demand Response Strategy Based on Deep Deterministic Policy Gradient." Processes 9, no. 4 (April 9, 2021): 660. http://dx.doi.org/10.3390/pr9040660.

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With the continuous improvement of the power system and the deepening of electricity market reform, the trend of users’ active participation in power distribution is more and more significant. Demand response has become the promising focus of smart grid research. Providing reasonable incentive strategies for power grid companies and demand response strategies for customers plays a crucial role in maximizing the benefits of different participants. To meet different expectations of multiple agents in the same environment, deep reinforcement learning was adopted. The generative model of residential demand response strategy under different incentive policies can be trained iteratively through real-time interactions with the environmental conditions. In this paper, a novel optimization model of residential demand response strategy, based on a deep deterministic policy gradient (DDPG) algorithm, was proposed. The proposed work was validated with the actual electricity consumption data of a certain area in China. The results showed that the DDPG model could optimize residential demand response strategy under certain incentive policies. In addition, the overall goal of peak load-cutting and valley filling can be achieved, which reflects promising prospects of the electricity market.

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Alasseri, Rajeev, Ashish Tripathi, T. Joji Rao, and K. J. Sreekanth. "A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs." Renewable and Sustainable Energy Reviews 77 (September 2017): 617–35. http://dx.doi.org/10.1016/j.rser.2017.04.023.

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Domínguez-Garabitos, Máximo A., Víctor S. Ocaña-Guevara, Félix Santos-García, Adriana Arango-Manrique, and Miguel Aybar-Mejía. "A Methodological Proposal for Implementing Demand-Shifting Strategies in the Wholesale Electricity Market." Energies 15, no. 4 (February 11, 2022): 1307. http://dx.doi.org/10.3390/en15041307.

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The energy transition has shown that fossil generation can be complemented with renewable energy and other resources capable of providing flexibility to the energy system’s operation, in compliance with the wholesale electricity market’s rules. This paper proposes a market-based methodology for introducing flexible demand in the energy dispatch, optimizing the scheduling of electricity system operation in the short-term, and considers the challenge of implementing an incentive scheme for participants in demand-response programs. The scheme includes the criteria of the elasticity of substitution and a renewable energy quota. This methodology is focused on a strategic demand shift to minimize the cost of supply; increase the dispatch of renewable energy; control CO2 emissions; and satisfy the generation, demand, and transmission operating constraints. These conditions encourage the development of a simulation tool that allows a sensitivity analysis to aid decision-making by operators and agents. The proposed methodology optimizes the operational cost of generation supply and specific performance indicators to determine the percentages of demand shift, the amount of CO2 emissions, the ratio of unserved power, the demand benefits obtained from an incentive scheme, and the natural market behavior.

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Li, Yuling, Xiaoying Wang, and Peicong Luo. "Strategies for Datacenters Participating in Demand Response by Two-Stage Decisions." Mathematical Problems in Engineering 2020 (July 22, 2020): 1–15. http://dx.doi.org/10.1155/2020/5206082.

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Modern smart grids have proposed a series of demand response (DR) programs and encourage users to participate in them with the purpose of maintaining reliability and efficiency so as to respond to the sustainable development of demand-side management. As a large load of the smart grid, a datacenter could be regarded as a potential demand response participant. Encouraging datacenters to participate in demand response programs can help the grid to achieve better load balancing effect, while the datacenter can also reduce its own power consumption so as to save electricity costs. In this paper, we designed a demand response participation strategy based on two-stage decisions to reduce the total cost of the datacenter while considering the DR requirements of the grid. The first stage determines whether to participate in demand response by predicting real-time electricity prices of the power grid and incentive information will be sent to encourage users to participate in the program to help shave the peak load. In the second stage, the datacenter interacts with its users by allowing users to submit bid information by reverse auction. Then, the datacenter selects the tasks of the winning users to postpone processing them with awards. Experimental results show that the proposed strategy could help the datacenter to reduce its cost and effectively meet the demand response requirements of the smart grid at the same time.

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Leobner, Ines, Peter Smolek, Bernhard Heinzl, Philipp Raich, Alexander Schirrer, Martin Kozek, Matthias Rössler, and Benjamin Mörzinger. "Simulation-based Strategies for Smart Demand Response." Journal of Sustainable Development of Energy, Water and Environment Systems 6, no. 1 (March 2017): 33–46. http://dx.doi.org/10.13044/j.sdewes.d5.0168.

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Deltetto, Davide, Davide Coraci, Giuseppe Pinto, Marco Savino Piscitelli, and Alfonso Capozzoli. "Exploring the Potentialities of Deep Reinforcement Learning for Incentive-Based Demand Response in a Cluster of Small Commercial Buildings." Energies 14, no. 10 (May 19, 2021): 2933. http://dx.doi.org/10.3390/en14102933.

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Demand Response (DR) programs represent an effective way to optimally manage building energy demand while increasing Renewable Energy Sources (RES) integration and grid reliability, helping the decarbonization of the electricity sector. To fully exploit such opportunities, buildings are required to become sources of energy flexibility, adapting their energy demand to meet specific grid requirements. However, in most cases, the energy flexibility of a single building is typically too small to be exploited in the flexibility market, highlighting the necessity to perform analysis at a multiple-building scale. This study explores the economic benefits associated with the implementation of a Reinforcement Learning (RL) control strategy for the participation in an incentive-based demand response program of a cluster of commercial buildings. To this purpose, optimized Rule-Based Control (RBC) strategies are compared with a RL controller. Moreover, a hybrid control strategy exploiting both RBC and RL is proposed. Results show that the RL algorithm outperforms the RBC in reducing the total energy cost, but it is less effective in fulfilling DR requirements. The hybrid controller achieves a reduction in energy consumption and energy costs by respectively 7% and 4% compared to a manually optimized RBC, while fulfilling DR constraints during incentive-based events.

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Chen, Tang, Sun, Zhou, Wang, and Mao. "Reliability Evaluation Method Considering Demand Response (DR) of Household Electrical Equipment in Distribution Networks." Processes 7, no. 11 (November 3, 2019): 799. http://dx.doi.org/10.3390/pr7110799.

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The load characteristic of typical household electrical equipment is elaborately analyzed. Considering the electric vehicles’ (EVs’) charging behavior and air conditioning’s thermodynamic property, an electricity price-based demand response (DR) model and an incentive-based DR model for two kinds of typical high-power electrical equipment are proposed to obtain the load curve considering two different kinds of DR mechanisms. Afterwards, a load shedding strategy is introduced to improve the traditional reliability evaluation method for distribution networks, with the capacity constraints of tie lines taken into account. Subsequently, a reliability calculation method of distribution networks considering the shortage of power supply capacity and outages is presented. Finally, the Monte Carlo method is employed to calculate the reliability index of distribution networks with different load levels, and the impacts of different DR strategies on the reliability of distribution networks are analyzed. The results show that both DR strategies can improve the distribution system reliability.

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Liu, Shuxin, Jing Xu, Chaojian Xing, Yang Liu, Ersheng Tian, Jia Cui, and Junzhu Wei. "Study on Dynamic Pricing Strategy for Industrial Power Users Considering Demand Response Differences in Master–Slave Game." Sustainability 15, no. 16 (August 11, 2023): 12265. http://dx.doi.org/10.3390/su151612265.

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With the deepening of power market reform, further study on power trading mechanisms has become the core issue of power market study. The development stage of the industrial electricity market requires efficient and flexible pricing mechanisms. Currently available pricing strategies are inadequate for demand response management. Therefore, this paper provides an in-depth study of the pricing mechanism in the industrial electricity market in the context of electricity market reform. It proposes a demand–response-based dynamic pricing strategy for industrial parks. The method proposes a dynamic pricing strategy for demand-side response in industrial parks based on master–slave game by establishing an exogenous model of demand-side response and incentives. Compared with the existing strategies, the strategy is more efficient and flexible, and effectively improves the economic efficiency of power trading and load regulation. Firstly, an exogenous model of demand-side response and incentive is built to characterize the demand-side response cost. The method focuses more on describing the exogenous characteristics of user incentives and response quantities. It only needs to analyze the exogenous indicators and random errors in various typical scenarios. The description of user demand-side response is more efficient. Secondly, a master–slave-game-based dynamic pricing strategy for industrial parks with demand-side response is proposed. The strategy is composed of a two-stage optimization. The primary regulation of customers is achieved by day-ahead time-of-use tariffs. The secondary regulation of customers is achieved by means of the same-day regulation of demand and purchase regarding clean electricity. The proposed two-stage price formation mechanism is more economical, more effective in load regulation, and improves the flexibility of industrial pricing. Finally, a case study is conducted on an industrial power user in a park in Liaoning Province. The results show that the proposed method is significantly better than existing methods in terms of improving the economic efficiency and load control effectiveness of the pricing strategy.

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Muraña-Silvera, Jonathan, Sergio Enrique Nesmachnow-Cánovas, Santiago Damián Iturriaga-Fabra, Sebastián Montes De Oca, Gonzalo Belcredi, Pablo Ariel Monzón-Rangeloff, Vladimir Dmitrievitch Shepelev, and Andrei Nikolaevitch Tchernykh. "Smart grid demand response strategies for datacenters." Proceedings of the Institute for System Programming of the RAS 33, no. 2 (2021): 125–36. http://dx.doi.org/10.15514/ispras-2021-33(2)-7.

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This article presents demand response techniques for the participation of datacenters in smart electricity markets under the smart grid paradigm. The proposed approach includes a datacenter model based on empirical information to determine the power consumption of CPU-intensive and memory-intensive tasks. A negotiation approach between the datacenter and clients and a heuristic planning method for energy reduction optimization are proposed. The experimental evaluation is performed over realistic problem instances modeling different types of clients. Results indicate that the proposed approach is effective to provide appropriate demand response actions according to monetary incentives.

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Lahrsen, Inga-Marie, Mathias Hofmann, and Robert Müller. "Flexibility of Epichlorohydrin Production—Increasing Profitability by Demand Response for Electricity and Balancing Market." Processes 10, no. 4 (April 13, 2022): 761. http://dx.doi.org/10.3390/pr10040761.

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The increasing share of variable renewable energies in the power grid is an incentive to explore demand response strategies. Chlor-alkali processes are high potential candidates, according to previous publications. Within Germany’s chemical industry, chlorine production accounts for approximately 20% of electricity use and could play a significant role in power grid stabilisation on the consumer end. This study focuses on the feasibility of load flexibilisation in epichlorohydrin plants, with the second biggest estimated demand response potential for chlorine-based products in Germany. A plant model with allyl chloride storage was created based on real data and literature values. Results from this model, spot market and balancing power prices, and future electricity market scenarios were used in a mixed-integer linear optimisation. We find that benefits from demand response can be generated as soon as additional power and storage volume is provided. The composition of provided types of balancing power bids follows the price trend on the market. Additionally, the computation time could be lowered significantly by running the scenarios in parallel. The results encourage a practical validation of the flexibility of epichlorohydrin production.

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Більше джерел

Дисертації з теми "Incentive-based demand response strategies"

Ryckebusch, Gaëlle. "Analysis of Demand-Response Participation Strategies for Congestion Management in an Island Distribution Network." Thesis, KTH, Industriella informations- och styrsystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169220.

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The Master Thesis is part of the Smart Grid Gotlandproject. This project aims at implementing smart grid solutionson the island of Gotland in order to be able to efficientlyintegrate large quantities of renewable energy production.In situations of high wind power production and lowconsumption, energy export problems may occur betweenGotland and the mainland. A novel approach to manageanticipated congestions, compared to traditional gridreinforcements, consists of using flexibility from demandresponse(DR) resources. However, such an approach presentschallenges as it requires both technical and economic considerations.This Master Thesis proposes and analyses twomarket-based strategies applied to detached houses for dayaheadcongestion management. The strategies are implementedin an Ancillary Service toolbox developed in theMATLAB programming environment.The first strategy involves using a dynamic network tariffwhile the second uses spot price optimization. Simulationsare performed for seasonal worst-case congestion scenarioswhile satisfying comfort and economic constraints ofthe DR participants. A sensitivity analysis is carried out toassess the impact of different spot price profiles and windpower production prognosis errors on the results.Results show that congestions are managed with a feasiblenumber of participants, but that their savings are negligiblefor both strategies (between 2 and 40 SEK/participant).Moreover, using a dynamic network tariff strategy impliesa DSO cost in the range of 1700-89000 SEK. These resultsapply for a 3-days congestion period, which is estimated tooccur 5-6 times a year if the maximum hosting capacity isincreased by 5 MW.To conclude, an AS toolbox with economic constraintsis feasible for Gotland conditions with a reasonable numberof DR participants. However, the simple cost-benefitanalysis that was carried out showed that the AS toolboxapproach was still much more costly than traditional gridreinforcement.

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Hasan, Mehedi. "Aggregator-Assisted Residential Participation in Demand Response Program." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/32546.

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The demand for electricity of a particular location can vary significantly based on season, ambient temperature, time of the day etc. High demand can result in very high wholesale price of electricity. The reason for this is very short operating duration of peaking power plants which require large capital investments to establish. Those power plants remain idle for most of the time of a year except for some peak demand periods during hot summer days. This process is inherently inefficient but it is necessary to meet the uninterrupted power supply criterion. With the advantage of new technologies, demand response can be a preferable alternative, where peak reduction can be obtained during the short durations of peak demand by controlling loads. Some controllable loads are with thermal inertia and some loads are deferrable for a short duration without making any significant impact on usersâ lifestyle and comfort. Demand response can help to attain supply - demand balance without completely depending on expensive peaking power plants. In this research work, an incentive-based model is considered to determine the potential of peak demand reduction due to the participation of residential customers in a demand response program. Electric water heating and air-conditioning are two largest residential loads. In this work, hot water preheating and air-conditioning pre-cooling techniques are investigated with the help of developed mathematical models to find out demand response potentials of those loads. The developed water heater model is validated by comparing results of two test-case simulations with the expected outcomes. Additional energy loss possibility associated with water preheating is also investigated using the developed energy loss model. The preheating temperature set-point is mathematically determined to obtain maximum demand reduction by keeping thermal loss to a minimal level. Case studies are performed for 15 summer days to investigate the demand response potential of water preheating. Similarly, demand response potential associated with pre-cooling operation of air-conditioning is also investigated with the help of the developed mathematical model. The required temperature set-point modification is determined mathematically and validated with the help of known outdoor temperature profiles. Case studies are performed for 15 summer days to demonstrate effectiveness of this procedure. On the other hand, total load and demand response potential of a single house is usually too small to participate in an incentive-based demand response program. Thus, the scope of combining several houses together under a single platform is also investigated in this work. Monte Carlo procedure-based simulations are performed to get an insight about the best and the worst case demand response outcomes of a cluster of houses. In case of electrical water heater control, aggregate demand response potential of 25 houses is determined. Similarly, in case of air-conditioning control (pre-cooling), approximate values of maximum, minimum and mean demand reduction amounts are determined for a cluster of 25 houses. Expected increase in indoor temperature of a house is calculated. Afterwards, the air-conditioning demand scheduling algorithm is developed to keep aggregate air-conditioning power demand to a minimal level during a demand response event. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm.
Master of Science

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Sambasivam, Balasubramanian. "Demand Response Planning in a Transitioning Electricity System." Thesis, 2019. https://etd.iisc.ac.in/handle/2005/5031.

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Globally, the electricity systems are undergoing major transitions from robust, carbon intensive, and firm power conventional systems to uncertain, intermittent and variable renewable energy integrated low carbon systems. These transitioning electricity systems have moved from a situation of “matching available supply with dynamic demand” to “matching dynamic supply with dynamic demand”. These transformations in the electricity system have led to several new challenges - (i) significant mismatch in periods of high supply and high demand, (ii) shift in the method of accessing energy resources for electricity generation from “procure, store and generate when needed” to “generate when available”, (iii) continuous struggle to match variable supply with variable demand, and (iv) installed capacity redundancy, temporal as well as permanent leading to low plant load factors. Actions on the supply-side alone will not be enough to address these challenges and achieve optimal functioning of the electricity system. We need effective demand-side solutions too, to manage the variations in both electricity supply and demand. Thus. the relevant research question is – Can the demand-side interventions become the effective solutions for managing the variabilities introduced by the renewable energy mainstreaming? The Overall goal of the proposed research is to study the effectiveness of demand-side interventions as potential solutions for managing the uncertainties, intermittencies and variabilities introduced by the integration of renewable energy sources and technologies into the conventional electricity systems. The first part of the research problem deals with study of the dynamics of electricity demand and modelling the demand patterns and the variabilities. To address this problem, initially logical clustering is used to segment the daily load curves, and then Monte Carlo simulation is employed to model and recreate the load curves. Second part of the problem deals with identification and prioritization of demand-side interventions to moderate demand variations in such a way that they match with the supply variations. This is performed by developing, implementing and validating mathematical model-based approach that integrates both the demand- and supply-side requirements, constraints, etc. Finally, few scenarios are evaluated using the mathematical model to study the effectiveness of DSM options to solve the supply-side problems. The results and findings establish the importance of demand response in managing the variations in both the electricity supply- and demand-sides in ensuring an effective match between electricity supply and demand. Finally, based on the results and findings, inputs for policy formulation, planning and decision-making are put forth for all the stakeholders

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Книги з теми "Incentive-based demand response strategies"

Hrabowski, Freeman A., Kenneth I. Maton, Monica Greene, and Geoffrey L. Greif. Overcoming the Odds. Oxford University Press, 2001. http://dx.doi.org/10.1093/oso/9780195126426.001.0001.

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When Beating the Odds: Raising Academically Successful African American Males appeared in 1998, it was hailed as "a crucial book" (Baltimore Sun) and "undoubtedly one of the most important tools the African American parent can possess" (Kweisi Mfume, President NAACP). Now, in response to enormous demand, the authors turn their attention to African American young women. Statistics indicate that African American females, as a group, fare poorly in the United States. Many live in single-parent households-either as the single-parent mother or as the daughter. Many face severe economic hurdles. Yet despite these obstacles, some are performing at exceptional levels academically. Based on interviews with many of these successful young women and their families, Overcoming the Odds provides a wealth of information about how and why they have succeeded--what motivates them, how their backgrounds and family relationships have shaped them, even how it feels to be a high academic achiever. They also discuss the challenges of moving into African American womanhood, from maintaining self-esteem to making the right choices about their professional and personal lives. Most important, the book offers specific and inspiring examples of the practices, attitudes, and parenting strategies that have enabled these women to persevere and triumph. For parents, educators, policy makers, and indeed all those concerned about the education of young African American women, Overcoming the Odds is an invaluable guidebook on creating the conditions that lead to academic-and lifelong-success.

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Gallagher, Aisling. Childcare Provision in Neoliberal Times. Policy Press, 2022. http://dx.doi.org/10.1332/policypress/9781529206494.001.0001.

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In the absence of public provision, many governments rely on the market to meet childcare demand. But who are the actors shaping this market? What work do they do to marketize care? And what does it mean for how childcare is provided? Based on an innovative theoretical framework and an in-depth study of the New Zealand childcare market, the book examines the problematic growth of private, for-profit childcare. The book begins with an outline of the working definition of state-led marketization, as one way to apprehend how states are involved in the active construction of markets to solve social problems. It focuses on the growth of private, for-profit childcare centres, and it seeks to investigate the role of the state in actively producing the conditions for neoliberal childcare markets to operate. Delving into this process, the book examines the ways in which the childcare market is being shaped by the economic and financial strategies of a range of actors, in direct response to the conditions of state-led marketization. The book reflects on childcare as a market of collective concern in the context of the current post-neoliberal moment. It seeks to address some of the perplexing tensions inherent in neoliberal childcare markets: that they are tasked with achieving considerable social and economic outcomes, yet are organized through highly inequitable market-based systems; they receive considerable public funding, yet are privately delivered. The book discusses the benefits of taking childcare markets as an object of study through the lens of Social Studies of Marketization. It investigates how neoliberal childcare markets are assembled and held together over time, in the face of considerable criticisms and problems. The book points to some of the challenges in establishing new accountability structures for childcare markets, as they become increasingly interwoven with the economic logics and practices of other kinds of market actors, far removed from the care of children. Opening the ‘black box’ of childcare markets to closer scrutiny, the book brings to light complex political, social and economic work of making childcare markets.

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Lansford, Jennifer E., and Prerna Banati, eds. Handbook of Adolescent Development Research and Its Impact on Global Policy. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190847128.001.0001.

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Of 1.2 billion adolescents in the world today, 90% live in low- and middle-income countries. These adolescents not only face many challenges but also represent a resource to be cultivated through educational opportunities and vocational training to move them toward economic independence, through initiatives to improve reproductive health, and through positive interpersonal relationships to help them avoid risky behaviors and make positive decisions about their futures. This volume tackles the challenges and promise of adolescence by presenting cutting-edge research on adolescent social, emotional, behavioral, cognitive, and physical development; promising programs from different countries to promote adolescents’ positive development; and policies that can advance adolescents’ rights within the framework of international initiatives, such as the Convention on the Rights of the Child and Sustainable Development Goals, which are guiding the international development agenda through 2030. This volume seeks to provide actionable strategies for policymakers and practitioners working with adolescents. Disconnects between national-level policies and local services, as well as lack of continuity with early childhood responses, present a significant challenge to ensuring a coherent approach for adolescents. Increasingly, adolescent participation and demands for rights-based approaches are seen and often unfortunately conflated with violence. This volume adopts a positive framing of adolescence, representing young people as opportunities rather than threats, and a valued investment both at individual and societal levels, contributing to a positive shift in discourses around young people.

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Частини книг з теми "Incentive-based demand response strategies"

Du, Pengwei, Ning Lu, and Haiwang Zhong. "Coupon Incentive-Based Demand Response." In Demand Response in Smart Grids, 143–65. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19769-8_6.

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Wilson, Laurel Ann. "The impact of technological change on medieval fashion." In La moda come motore economico: innovazione di processo e prodotto, nuove strategie commerciali, comportamento dei consumatori / Fashion as an economic engine: process and product innovation, commercial strategies, consumer behavior, 93–118. Florence: Firenze University Press, 2022. http://dx.doi.org/10.36253/978-88-5518-565-3.08.

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In the early fourteenth century, a new fashion system appeared in Europe, one which was based on constant change and the privileging of the new. This paper argues that the new system did not appear simply as a response to consumer demand; it was also precipitated in part by two major technological innovations: the thirteenth-century development of the advanced broadloom, and the new tailoring techniques of the early fourteenth century. These technological innovations thus helped to precipitate the fashion revolution in obvious material ways, but they also led less directly to social and economic changes which were equally important to the development of fashion.

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Zhou, Kaile, and Lulu Wen. "Incentive-Based Demand Response with Deep Learning and Reinforcement Learning." In Smart Energy Management, 155–82. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9360-1_7.

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Abdolahi, Arya, Farhad Samadi Gazijahani, Navid Taghizadegan Kalantari, and Javad Salehi. "Techno-Economic Framework for Congestion Management of Renewable Integrated Distribution Networks Through Energy Storage and Incentive-Based Demand Response Program." In Demand Response Application in Smart Grids, 241–64. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32104-8_11.

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Olorunfemi, Tope Roseline, and Nnamdi Nwulu. "Optimal Grid-Connected Microgrid Scheduling Incorporating an Incentive-Based Demand Response Program." In Lecture Notes in Mechanical Engineering, 615–22. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5753-8_56.

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Jin, Peng, Hai Wu, Guo Hu, and Qian Shen. "Evaluation and Management of Operation State of Distribution Station Area Based on Incentive Demand Response." In Lecture Notes in Electrical Engineering, 219–31. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7156-2_15.

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Shao, Bowei, Hui Wang, He Wang, and Wenliang Li. "Real-Time Scheduling Strategy of Electric Vehicle Load Aggregation Quotient Based on Incentive and Price of Demand Response." In Lecture Notes in Electrical Engineering, 622–31. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1439-5_57.

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Singh, Balwant, Shefali Mishra, Deepak Singh Bisht, and Rohit Joshi. "Growing Rice with Less Water: Improving Productivity by Decreasing Water Demand." In Rice Improvement, 147–70. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66530-2_5.

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AbstractRice is a staple food for more than half of the global population. With the increasing population, the yield of rice must correspondingly increase to fulfill the requirement. Rice is cultivated worldwide in four different types of ecosystems, which are limited by the availability of irrigation water. However, water-limiting conditions negatively affect rice production; therefore, to enhance productivity under changing climatic conditions, improved cultivation practices and drought-tolerant cultivars/varieties are required. There are two basic approaches to cultivation: (1) plant based and (2) soil and irrigation based, which can be targeted for improving rice production. Crop plants primarily follow three mechanisms: drought escape, avoidance, and tolerance. Based on these mechanisms, different strategies are followed, which include cultivar selection based on yield stability under drought. Similarly, soil- and irrigation-based strategies consist of decreasing non-beneficial water depletions and water outflows, aerobic rice development, alternate wetting and drying, saturated soil culture, system of rice intensification, and sprinkler irrigation. Further strategies involve developing drought-tolerant cultivars through marker-assisted selection/pyramiding, genomic selection, QTL mapping, and other breeding and cultivation practices such as early planting to follow escape strategies and decreasing stand density to minimize competition with weeds. Similarly, the identification of drought-responsive genes and their manipulation will provide a technological solution to overcome drought stress. However, it was the Green Revolution that increased crop production. To maintain the balance, there is a need for another revolution to cope with the increasing demand.

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Wicaksono, Hendro, Tina Boroukhian, and Atit Bashyal. "A Demand-Response System for Sustainable Manufacturing Using Linked Data and Machine Learning." In Dynamics in Logistics, 155–81. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88662-2_8.

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AbstractThe spread of demand-response (DR) programs in Europe is a slow but steady process to optimize the use of renewable energy in different sectors including manufacturing. A demand-response program promotes changes of electricity consumption patterns at the end consumer side to match the availability of renewable energy sources through price changes or incentives. This research develops a system that aims to engage manufacturing power consumers through price- and incentive-based DR programs. The system works on data from heterogeneous systems at both supply and demand sides, which are linked through a semantic middleware, instead of centralized data integration. An ontology is used as the integration information model of the semantic middleware. This chapter explains the concept of constructing the ontology by utilizing relational database to ontology mapping techniques, reusing existing ontologies such as OpenADR, SSN, SAREF, etc., and applying ontology alignment methods. Machine learning approaches are developed to forecast both the power generated from renewable energy sources and the power demanded by manufacturing consumers based on their processes. The forecasts are the groundworks to calculate the dynamic electricity price introduced for the DR program. This chapter presents different neural network architectures and compares the experiment results. We compare the results of Deep Neural Network (DNN), Long Short-Term Memory Network (LSTM), Convolutional Neural Network (CNN), and Hybrid architectures. This chapter focuses on the initial phase of the research where we focus on the ontology development method and machine learning experiments using power generation datasets.

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Pichler, Christina, Arnulf J. Hartl, Renate Weisböck-Erdheim, and Michael Bischof. "Medical Evidence of Alpine Natural Resources as a Base for Health Tourism." In Digital and Strategic Innovation for Alpine Health Tourism, 1–30. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15457-7_1.

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AbstractThe Alpine space disposes of excellent prerequisites to respond to the increasing demand of nature-based health tourism. Despite a growing scientific knowledge on the manifold benefits of human interaction with Alpine natural resources, the health tourism potential has not yet been fully exploited by Alpine regions. Based on major push and pull factors, the current state of scientific knowledge on the healing potential of nine selected natural Alpine resources is presented and discussed with regard to their health tourism potential. Major research gaps as well as starting points for future studies are demonstrated. In this way, the present work contributes to an applicable knowledge base on the health benefits of Alpine resources to enhance regional innovation capacity in terms of sustainable health tourism development. As tourism regions are increasingly taking evidence-based approaches to health tourism and regional development, the resulting lighthouses will contribute to the positioning of the Alpine space as globally attractive healing environment.

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Тези доповідей конференцій з теми "Incentive-based demand response strategies"

Hajibandeh, N., M. Ehsan, S. Soleymani, M. Shafie-khah, and J. P. S. Catalao. "Modeling price- and incentive-based demand response strategies in the renewable-based energy markets." In 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE, 2017. http://dx.doi.org/10.1109/eeeic.2017.7977701.

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Fu, Xin, Qibo He, and Yufan Ge. "Strategic Bidding Model for Load Service Entities Considering Priced-Based and Incentive-Based Demand Response." In 2023 5th Asia Energy and Electrical Engineering Symposium (AEEES). IEEE, 2023. http://dx.doi.org/10.1109/aeees56888.2023.10114274.

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Liu, Bo. "Scheduling Strategies of Smart Community with Load Aggregator-based Demand Response." In 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2018. http://dx.doi.org/10.1109/ei2.2018.8582656.

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Zhang, Chunyu, Qi Wang, and Jianhui Wang. "Real-time procurement strategies of a proactive distribution company with aggregator-based demand response." In 2017 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2017. http://dx.doi.org/10.1109/pesgm.2017.8273987.

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Zunnurain, Izaz, and Md Nasimul Islam Maruf. "Automated demand response strategies using home energy management system in a RES-based smart grid." In 2017 4th International Conference on Advances in Electrical Engineering (ICAEE ). IEEE, 2017. http://dx.doi.org/10.1109/icaee.2017.8255439.

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Dababneh, Fadwa, Mariya Atanasov, Zeyi Sun, and Lin Li. "Simulation-Based Electricity Demand Response for Combined Manufacturing and HVAC System Towards Sustainability." In ASME 2015 International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/msec2015-9278.

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In this paper, we introduce a simulation-based method to implement electricity demand response for manufacturers considering both heating ventilation and air conditioning (HVAC) and manufacturing systems. Compared with the existing literature where the demand response implementation for manufacturing system and HVAC system is usually conducted separately, this paper advances the state of the art by combining two systems together in demand response. A joint simulation model is established using ProModel and EnergyPlus. ProModel is first used to simulate the demand response for the manufacturing system to obtain the demand response actions without influencing production. After that, these actions are used as input information in EnergyPlus where the HVAC and building models are developed. The interaction between the heat generated due to manufacturing machine operation and the indoor heat demand is explored. Three different demand response strategies, i.e., 1) the baseline model that neither manufacturing system nor HVAC is considered for demand response; 2) only manufacturing system is considered for demand response; and 3) both the HVAC and manufacturing systems are considered for demand response, are presented and compared. The results show that the combined model can achieve high power demand reduction during demand response event.

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Dunbar, Samuel, and Scott Ferguson. "The Impact of Consumer Preference Distributions on Dynamic Electricity Pricing for Residential Demand Response." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98219.

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Abstract Demand Response (DR) is the adjustment of consumer electricity demand through the deployment of one or more strategies, e.g. direct load control, policy implementation, dynamic pricing, or other economic incentives. Widespread implementation of DR is a promising solution for addressing energy challenges such as the integration of intermittent renewable energy resources, reducing capacity cost, and improving grid reliability. Understanding residential consumer preferences for shifting product usage and how these preferences are distributed amongst a population are key to predicting the effectiveness of different DR strategies. In addition, there is a need for a better understanding of how different DR programs, system level objectives, and preference distributions will impact different segments of consumers within a population. Specifically, the impacts on their product use behavior and electricity bill. To address this challenge, a product based approach to modeling consumer decisions about altering their electricity consumption is proposed, which links consumer value to their products, instead of directly to the amount of electricity they consume. This model is then used to demonstrate how population level preference distributions for altering product use impact system level objectives.

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Xue, Bai, and Qi TIAN. "Research on energy saving operation strategies of railway station district heating system based on temperature response of demand side." In Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022), edited by Said Easa. SPIE, 2022. http://dx.doi.org/10.1117/12.2645984.

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Dunbar, Samuel, and Scott Ferguson. "A Consumer Dissatisfaction Model Linking Dynamic Pricing With Shifted Product-Use in Residential Electricity Markets." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22499.

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Abstract Demand Response (DR) is the implementation of a specific strategy or set of strategies, with the goal of altering consumer energy demand, such that some system level objectives are improved. These strategies typically include dynamic pricing, direct load control, policy implementation, or other financial incentives. DR will become a crucial tool for managing growing global energy demand in conjunction with higher penetration rates of intermittent renewable energy resources. Effective implementation of a DR strategy requires a realistic understanding of how consumers will respond to that strategy and how they will be affected by it. Here, a product-based decision model for residential consumers, that links consumer decisions directly to product-use, is revisited and adapted from a continuous time formulation to discrete time. The relationship between financial incentives, consumer preferences, and demand flexibility at the population level is then quantified. The model is used for exploring the tradeoffs between typical objectives for a dynamic pricing residential DR program and evaluating the characteristics of well-performing pricing solutions.

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Dierks, Ludwig, and Sven Seuken. "The Competitive Effects of Variance-based Pricing." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/51.

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In many markets, like electricity or cloud computing markets, providers incur large costs for keeping sufficient capacity in reserve to accommodate demand fluctuations of a mostly fixed user base. These costs are significantly affected by the unpredictability of the users' demand. Nevertheless, standard mechanisms charge fixed per-unit prices that do not depend on the variability of the users' demand. In this paper, we study a variance-based pricing rule in a two-provider market setting and perform a game-theoretic analysis of the resulting competitive effects. We show that an innovative provider who employs variance-based pricing can choose a pricing strategy that guarantees himself a higher profit than using fixed per-unit prices for any individually rational response of a provider playing a fixed pricing strategy. We then characterize all equilibria for the setting where both providers use variance-based pricing strategies. We show that, in equilibrium, the providers' profits may increase or decrease, depending on their cost functions. However, social welfare always weakly increases.

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Звіти організацій з теми "Incentive-based demand response strategies"

Wintjes, Rene, and Fernando Vargas. Digital Innovation Hubs: Insights from European Experience in Supporting Business Digitalization. Inter-American Development Bank, July 2023. http://dx.doi.org/10.18235/0004995.

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Digital technologies can boost regional and sectoral productivity, yet firms in Latin American and Caribbean (LAC) countries are experiencing shortfalls in digital uptake and innovation. This is partly due to a scarcity of knowledge suppliers able to respond to the region's or countries' diverse needs. Digital innovation hubs (DIHs) can offer a collaborative, location-based approach and address these gaps. This study analyzes data from over 300 DIHs in Europe, revealing that university-affiliated DIHs offer sophisticated services, such as collaborative research and testing facilities, while industry-affiliated DIHs focus on activities closer to the market, including mentoring and ecosystem building. Three case studies show that establishing a DIH is not achieved overnight but is instead a learning and improvement process; that a DIH evolves in response to regional needs and assets; and that DIHs require reliable funding for their development, particularly public financing, in their early stages. Hence, LAC policymakers should take in to account the need for a context-sensitive, context-adaptive strategy when promoting DIHs as a tool for public policy. Voucher programs and regional policies for productive development, such as smart specialization strategies, could also refine and mobilize the demand for specific digital technologies, facilitating the establishment of DIH-type initiatives.

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Lenhardt, Amanda. Development Finance for Socioeconomic Programming in Response to Covid-19. Institute of Development Studies (IDS), November 2021. http://dx.doi.org/10.19088/cc.2021.009.

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The Covid-19 crisis led multilateral and bilateral donors to revise their funding strategies to respond to the crisis and to adapt existing programming to the new context it created. This resulted in changes to overall allocations, with some countries increasing aid commitments and institutions like the World Bank scaling up lending to low- and middle-income countries while others have cut aid budgets due to low economic growth and demands on domestic resources at home. Changes in aid volumes and disbursal mechanisms are anticipated to have significant impacts on low- and middle-income countries’ abilities to cope with the crisis in the short term, and the targeting of these investments are likely to have a lingering effect on recoveries for years to come. Although aid makes up a small proportion of countries’ available finance to tackle the Covid-19 crisis, “other financing options such as foreign direct investment, workers’ remittances, and taxes – have fallen and are slow to recover” (Prizzon, 2021). Aid finance will therefore be critical to many countries’ short-term responses to Covid-19 and capacities to abate longer-term negative impacts on social and economic outcomes as countries begin to recover. This report gives a broad overview of trends in bilateral, multilateral, and private foundations’ funding strategies over the course of the pandemic to highlight observable shifts in practice. The review is based on a rapid search of funding announcements from a selection of bilateral donors, a selection of multilateral institutions, and overall trends reported by foundations. The report also includes evidence reported by secondary literature on finance for development over the course of the Covid-19 crisis.

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The Competitive Advantage of Nations: A Successful Experience, Realigning the Strategy to Transform the Economic and Social Development of the Basque Country. Universidad de Deusto, 2015. http://dx.doi.org/10.18543/xiqr3861.

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Why do the new economy and welfare societies recommend a new station on the long journey towards competitiveness initiated within the framework of “The Competitive Advantage of Nations”, published as long as 25 years ago? A little more than twenty-five years ago, the Basque Country decided to equip itself with its own development strategy, undertaking to meet the challenge of designing its own future. The Basque Country aspired to give itself the maximum degree of self-government as a nation without a State, following its release from a long dictatorship which had plunged it into autarchy and isolation from the Western democracies around it, limiting its ability and responsibility to shape its own destiny and to offer its Society the highest standards of welfare, facing one of the greatest economic, political and social crises of its history and suffering from the ravages of terrorism within an economy castigated by soaring unemployment above 25%, a drop in its GDP, the fall, like dominoes, of its key industrial sectors, locked into the monoculture of the steel and metal working industry, outside the Europe which was being constructed by the then Economic Community of the Six, marginalized as a peripheral area from the future axis and development of the so-called “blue banana” of the London-Milan backbone and with an incipient and inexperienced administration, full of youth and enthusiasm, and a business world undergoing conversion, learning to live with a trade union phenomenon that the former dictatorship had bypassed. Faced with this complex and exciting challenge, those of us who had the privilege of addressing the aforementioned proposal, interpreting (by means of our analyses, as well as the wish to make our desires and dreams come true) the main keys to explain the state of the world economy, the main trends of change and their foreseeable impact on the Basque economy (“What the world economy taught us”), began the task of defining what we call “A strategy for the modernization and internationalization of our economy and our Country” trying to give some meaning to the role expected of the new players (States, city-regions, provinces, etc.), a role in which our small Country, with features of a City-Region, a sub-national entity, an invertebrate area on the two sides of the Pyrenees, could assume the figure of co-protagonist and provide society with a prosperous future. We also needed the framework and tools desirable for tackling the success strategy. We identified the gap between the needs that would be generated by the new paradigms and the tools offered by the existing political-economic framework (contents, skills, potential developments), accompanied by our own Country-strategy, with special emphasis on the initiatives, factors and critical vectors our society would demand and its aspirations for well-being and development. Within this context, the Basque Government approached Michael E. Porter, his ideas and concepts of the moment, and we began a collaborative process (which lasts until this day), constructing much more than our “Competitive Advantage of the Basque Country” in a thrilling and unfinished “Journey towards Competitiveness and Prosperity”. The Basque Country enjoys the privilege of having been the first nation to apply, in a strategic and comprehensive manner, the concepts which, a few years later, came to light in the prestigious publication we celebrate today, titled “The Competitive Advantage of Nations”, which has inspired the design of numerous policies and strategies throughout the world, which has brought about a proliferation of followers, which has trained instructors and which has generated a large number of new researchers and academics, new policy makers, new instruments for competitiveness and extraordinary levels of prosperity throughout the world. Since then, we have shared our own particular project which, alive and changing, responds to the new economic and social challenges and conflicts by constructing and applying a Country strategy with distinctive achievements and results beyond our economic environment. It lies within the conceptual framework inspired by the complementary tripod of Michael E. Porter's conceptual movement in his Competitive Advantage (Competitiveness, Shared Value Initiative and Social Progress) and our contributions learned from day to day in keeping with our vocation, identity, will and commitment. It is a never-ending process based on a model and a way of understanding the former pledge to give ourselves a single strategy designed by and for people.

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