Cost-benefit analysis of integrated energy system planning considering demand response

Xiang, Yue; Cai, Hanhu; Gu, Chenghong; Shen, Xiaodong

doi:10.1016/j.energy.2019.116632

Cited by 149 publications

(39 citation statements)

References 24 publications

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“…, , Constraints (7) and ( 8) limit the GSP's active and reactive power output, respectively. When bus i is the GSP, Constraints (2) and ( 3) can be replaced with Constraints ( 9) and ( 10): , ,…”

Section: ) Numerous Constraintsmentioning

confidence: 99%

Evaluating Connectable Capacity of Distributed Wind Generation in Distribution Networks Through a Bayesian Integrated Optimization Method

Chen

Xiang

Sun

et al. 2022

IEEE Systems Journal

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The effective evaluation of the connectable capacity of renewable energy plays a vital role in the development of a sustainable distribution network. Quantifying the capacity while considering network security and the local renewable accommodation policy is a challenge. This paper proposes a scenario-based bi-level mathematical model using a Bayesian integrated optimization method to evaluate and quantify the connectable capacity of distributed wind generation in distribution networks, which effectively integrates the characteristics of wind power and the local accommodation policy. The constraint on the generation curtailment ratio (CR) is innovatively designed to represent the renewable accommodation policy and integrated with network security constraints to coordinatively quantify the capacity. The model is solved by the Bayesian integrated optimization method. The regression-based algorithm greatly reduces the complexity of alternating iteration and improves the calculation efficiency. Practical cases are used to verify the effectiveness of the proposed method. Results indicate that the method is more efficient than traditional optimization algorithms, and CR integration ensures that the connectable capacity fits local renewable energy development policies well.

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Section: ) Numerous Constraintsmentioning

confidence: 99%

Evaluating Connectable Capacity of Distributed Wind Generation in Distribution Networks Through a Bayesian Integrated Optimization Method

Chen

Xiang

Sun

et al. 2022

IEEE Systems Journal

Self Cite

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“…In this situation, comprehensive energy supply services characterized by the comprehensive and efficient utilization of multiple energy sources have attracted attention for the various energy needs of end users, such as electricity, heating, cooling, and gas [4,5]. e planning, design, and optimization operation research of the integrated energy supply system have focused on the overall planning and scheduling methods of energy production, conversion, storage equipment, and end energy users within the energy supply range [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Rapid Identification of Economic Indicators of Integrated Energy Systems Based on Data Analysis

He¹,

Liu

et al. 2022

Mathematical Problems in Engineering

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The construction of integrated energy systems has received widespread attention. In addition to system design and operating optimization, clarifying the internal relationship between the project’s own characteristics and its economic indicators is also important for high-value project selection and implementation. Based on various energy prices and the climatic characteristics of typical cities, 60 integrated energy supply projects in 4 typical cities were used as a case study, and the cold and heat source system solutions with the shortest investment payback period for each project were calculated through a system optimization model. We calculated the correlation coefficient between the initial investment of system equipment, annual energy supply, annual energy sales revenue, annual equivalent full-load energy supply hours, initial equipment investment indicators for annual unit energy supply, and the project’s static investment payback period. The key factors affecting the static investment payback period of the project were identified. The results show that, under the optimal system scheme, even for buildings of the same type in the same area, the economic indicators of different integrated energy projects are still quite different. Under the current design, operation, and operation conditions, load distribution is the decisive factor for the economic feasibility of the project. The static investment payback period of the project can be quickly calculated based on the equivalent full-load energy supply hours of the project throughout the year. Compared with the current numerical and system dynamics model for point-to-point single system optimizing modeling, the proposed statistical regression model can help reveal the main factors of integrated energy system’s economically feasible.

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“…In Refs. [23,24], the impact of IDR on operation of system is not considered. In the literature [25][26][27], IDR is considered but the benefits of users and carbon emissions are ignored.…”

Section: Introductionmentioning

confidence: 99%

“…[30,31]. In addition, although in the literatures [23,24,28,29], carbon emissions are considered, only the impact of carbon emissions fines on economic benefits is considered, and carbon emissions are disregarded as the optimization objective. Therefore, in the current scenario of supply and demand interaction, how to optimize the low-carbon operation of MES is still a difficult problem.…”

Section: Introductionmentioning

confidence: 99%

Transaction Model Based on Stackelberg Game Method for Balancing Supply and Demand Sides of Multi-Energy Microgrid

et al. 2022

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To improve the coordination and complementarity of multiple energy sources, balancing the interests of different participants in a multi-energy system is of great importance. However, traditional centralized optimization can hardly reflect the game relationship between supply side and demand sides. A trading model based on the Stackelberg game model is proposed in this paper to balance the interests of the supply side and demand side and reduce the carbon emissions. First of all, the process of trading between the supply side and demand side based on smart contracts is described. A contractual consensus is obtained through an internal game, and the transaction is completed automatically. Secondly, a bilevel optimization model is established to coordinate the benefits of both parties based on the Stackelberg game model. The energy operator acts as a leader, and considers the two objectives, i.e., maximizing net income and minimizing carbon emissions, and uses the linear weighting method to convert the dual objectives into single objective. Users act as followers and aim to increase the comprehensive benefits, including energy cost and comfort. Then, Karush–Kuhn–Tucker optimality condition is used to transform the bilevel optimization model into an equivalent single-level model. Finally, simulation results show that the proposed method can coordinate the economic interests of both sides of supply and demand and effectively reduce the carbon emissions of the energy operator.

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Cost-benefit analysis of integrated energy system planning considering demand response

Cited by 149 publications

References 24 publications

Evaluating Connectable Capacity of Distributed Wind Generation in Distribution Networks Through a Bayesian Integrated Optimization Method

Evaluating Connectable Capacity of Distributed Wind Generation in Distribution Networks Through a Bayesian Integrated Optimization Method

Rapid Identification of Economic Indicators of Integrated Energy Systems Based on Data Analysis

Transaction Model Based on Stackelberg Game Method for Balancing Supply and Demand Sides of Multi-Energy Microgrid

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