Extended multi‐energy demand response scheme for industrial integrated energy system

Jiang, Ziqing; Hao, Ran; Ai, Qian; Yu, Zhen; Xiao, Fei

doi:10.1049/iet-gtd.2017.0630

Cited by 30 publications

(22 citation statements)

References 24 publications

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“…Then in a second stage, the economic dispatch considers the uncertainty of the response based on the settings provided by industrial users concerning the processes steps that can be interrupted with their user satisfaction parameters. Optimization of the internal reserve capacities, selfgeneration of the industries and the coupling characteristics for the multi-energy demands like CCHP, aims to establish a model reflecting the mutual influence of the different energy sources in the presence of DRPs as in [19], [4] and to minimize the dispatch cost. In [20], the authors tried to combine a model of DRP for large customers in the presence of storage to reduce the procurement cost from multiple sources of energy.…”

Section: B Industrial Drp and Cost Optimization And Investmentmentioning

confidence: 99%

“…In [3], a multi-agent system is used to connect these aggregated categories to one higher level through multiple agents. In [4], DSO, producing entities like Combined Cooling Heat Power (CCHP), consuming entities and large industrial consumers can communicate for the various transactions. Having resort to Industrial Customers, studies show that the network stress could be reduced if industrial activities are planned and synchronized according to the generation constraints and other customers' requirements.…”

Section: Introductionmentioning

confidence: 99%

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Industrial Loads Used as Virtual Resources for a Cost-Effective Optimized Power Distribution

et al. 2020

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Industrial Customers are dispersed at various levels of the electrical network and fed together with other customers' categories in a distributed environment. Optimizing industrial processes in the presence of other customers' categories supplied by the same infrastructure is a challenging issue. Existing studies have analyzed the effect of different Industrial Demand Response Programs on the distribution network, which also supplies other customers' categories. They show the need for improving the distribution performance although multiple demand response programs have been suggested for this purpose. In this paper, a new approach is presented considering an optimal synchronized process among all consumers' categories. It shows that the balance between generation and demand is maintained, the customer satisfaction is guaranteed, the profit is maximized and the cost is minimized for all customers. Various time constraints set by different industry productions are considered in the optimization process. Fairness problems, multiple pricing schemes and formulation for the same are elaborated. The method is validated through a simulation on Matlab using K-Means Clustering and multi-objective particle swarm optimization (MOPSO) along with data prediction. INDEX TERMS Multiple demand response programs, MOPSO, group method of data handling (GMDH), Kmeans, clustering, smart grid, industrial customers.

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Section: B Industrial Drp and Cost Optimization And Investmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Industrial Loads Used as Virtual Resources for a Cost-Effective Optimized Power Distribution

et al. 2020

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“…This provides a shortcut for efficient integration and unified planning of multi-energy sources in IP. According to [7], [8] considers the price and demand differences of various energy sources in the electric-thermal system and establishes the DR scheme and optimization model for the coupling system. A price-based control strategy for district heating networks is proposed in [9], but it is limited to thermal systems.…”

Section: Introductionmentioning

confidence: 99%

Integrated Demand Response Characteristics of Industrial Park: A Review

Chen¹,

Sun

Xin

et al. 2020

Journal of Modern Power Systems and Clean Energy

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With the gradual upgradation of global energy consumption and the associated development of multi-energy sources, the pace of unified energy planning and design has been accelerated and the concept of multi-energy system (MES) has been formed. The industrial structure of industrial park (IP) consists of production and marketing of multi-energy sources, which makes IP become an ideal application scenario for MES. The coupling between multi-sources raises the complexity level of IP, which requires the demand side analysis in IP as it enables customers to actively participate in energy planning and development. This paper presents the concept and operation strategies of integrated demand response (IDR), and its model classification is analyzed in detail. Optimization model and IDR with varying time period are studied in IP to determine their impacts on the system. A detailed survey of different techniques in both operation strategies and model classification is presented and the classification is based on pros and cons. Finally, key issues and outlooks are discussed. Index Terms-Industrial park (IP), multi-energy system (MES), integrated demand response (IDR), integrated direct load control (IDLC), demand side management (DSM), demand side comfort index.

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“…An effort-based reward approach was proposed in [8] for the allocation of load shedding amount in microgrids. An extended multi-energy DR scheme for an integrated energy system was established in [9] with the objective of shaving peak load and minimizing total costs. Nevertheless, the incentive prices in these studies are mostly set as constants and less on a theoretical basis.…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Enabled Demand Response Scheme with Individualized Incentive Pricing Mode

Guo

Wang

2020

Energies

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Demand response (DR) can offer a wide range of advantages for electrical systems by facilitating the interaction and balance between supply and demand. However, DR always requires a central agent, giving rise to issues of security and trust. Besides this, differences in user response cost characteristics are not taken into consideration during incentive pricing, which would affect the equal participation of users in DR and increase the costs borne by the electricity retail company. In this paper, a blockchain-enabled DR scheme with an individualized incentive pricing mode is proposed. First, a blockchain-enabled DR framework is proposed to promote the secure implementation of DR. Next, a dual-incentive mechanism is designed to successfully implement the blockchain to DR, which consists of a profit-based and a contribution-based model. An individualized incentive pricing mode is adopted in the profit-based model to decrease the imbalance in response frequency of users and reduce the costs borne by the electricity retail company. Then, the Stackelberg game model is constructed and Differential Evolution (DE) is used to produce equilibrium optimal individualized incentive prices. Finally, case studies are conducted. The results demonstrate that the proposed scheme can reduce the cost borne by the electricity retail company and decrease the imbalance among users in response frequency.

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Extended multi‐energy demand response scheme for industrial integrated energy system

Cited by 30 publications

References 24 publications

Industrial Loads Used as Virtual Resources for a Cost-Effective Optimized Power Distribution

Industrial Loads Used as Virtual Resources for a Cost-Effective Optimized Power Distribution

Integrated Demand Response Characteristics of Industrial Park: A Review

Blockchain-Enabled Demand Response Scheme with Individualized Incentive Pricing Mode

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