Planning and operation method of the regional integrated energy system considering economy and environment

Wang, Yongli; Wang, Yudong; Huang, Yujing; Li, Fang; Zhang, Ming; Li, Jiapu; Wang, Xiaohai; Zhang, Fuwei

doi:10.1016/j.energy.2019.01.036

Cited by 160 publications

(33 citation statements)

References 16 publications

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“…The operation cycle is 24 hours, and the optimal operation cycle is 1 hour. 25 The basic PV power forecast data and loads forecast data are referred from Reference 27. The basic wind power forecast data are referred from Reference 28.…”

Section: Datamentioning

confidence: 99%

“…The operation cost of each device is listed in Table 3. 8,25,26 Pollutant emissions and environmental cost factors for important pollutant sources is shown in Table 4. 26 The time-of-use power price is adopted according to the real-world price ( Figure 5).…”

Section: Datamentioning

confidence: 99%

“…In this article, the interval numbers are utilized to depict the uncertainties of PV power output, WT power output, and varies loads. For operational optimization, economy, environment pollution emission penalty, and so on are considered as the objective function 25,26 . Inspired by References 25 and 26, this article focuses on the operation and environmental cost of the IES.…”

Section: Introductionmentioning

confidence: 99%

“…For operational optimization, economy, environment pollution emission penalty, and so on are considered as the objective function 25,26 . Inspired by References 25 and 26, this article focuses on the operation and environmental cost of the IES. Then, we propose an interval optimization operation approach for IES considering generation and loads uncertainties.…”

Section: Introductionmentioning

confidence: 99%

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Interval optimization based operational strategy of integrated energy system under renewable energy resources and loads uncertainties

Wang

Gao

et al. 2020

Int J Energy Res

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Summary Uncertainties from renewable energy resources (RESs) and energy demands have brought enormous challenges to the optimal operation of integrated energy system (IES). An interval optimization based operational strategy for IES is proposed to overcome uncertainties. Firstly, embarking from a deterministic IES operation model, an interval method is presented to quantify the uncertainties instead of possibility distribution so as to better characterize the impact of RESs and loads on the operation of the IES. Secondly, the interval optimization model under multiple uncertainties is presented. In the proposed model, the total daily cost is optimized and system operation constraints are fully considered. Thirdly, the order interval relation and possibility degree are adopted to transform the interval model to deterministic model, which is solved by CPLEX optimizer. Finally, case studies considering influence of different uncertainty objects and uncertainty possibility degree levels are performed and analyzed extensively. The simulation results show that the optimized interval numbers will be increased gradually as uncertainty fluctuation degree increased from ±5% to ±25%. Comparing with automatic robust convex optimization method, the robust optimized values are in accordance with the upper values of optimized interval number optimization method, and the midpoints of interval results optimized by interval method are 4.1%, 8.7%, 11.7%, 16.5%, and 8.0% less than robust optimization results, respectively.

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Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Interval optimization based operational strategy of integrated energy system under renewable energy resources and loads uncertainties

Wang

Gao

et al. 2020

Int J Energy Res

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“…The proposed method can improve the extension flexibility of the system optimal planning model with expected accuracy. Wang et al [8] presented a two-stage optimisation method for a coupled capacity planning and operation problem, cast within the economical operation of regional IES. The non-dominated sorting genetic algorithm-II (NSGA-II) algorithm and the mixed-integer linear programming method are implemented to solve the model based on simulation.…”

Section: Introductionmentioning

confidence: 99%

IES configuration method considering peak‐valley differences of tie lines and operation costs of power grids

Zhang

et al. 2020

IET Energy Systems Integration

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The peak-valley difference of power grid will be enlarged significantly with the increasing number of integrated energy systems (IESs) connecting to power grids, which may cause a high operation cost and voltage violations. This study proposes an IES configuration method considering the peak-valley difference of the tie line between IES and power grid. An optimal configuration model of IES is established, which takes the sum of the annual operating cost of the power grid and annual cost of IES as objectives, while the tie line transmission power between IES and power grid are considered as constraints. The elite energy reserve genetic algorithm and branch and bound method are used to solve the proposed model, while the optimal power flow is used to calculate the grid operation cost under a given transmission power of the tie line. The simulation results of an improved IEEE30 node system verify the validity of the proposed method.

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Comprehensive energy cooperative optimization model based on energy conversion efficiency considering investment benefit

Peng¹,

Wu²

2021

Int J Energy Res

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In order to solve the problem of low utilization efficiency and high operating cost of a single energy system among various types of energy, a comprehensive energy system was constructed, which considering P2G equipment, CCHP cogeneration equipment, electric refrigerators, and other multi-source systems. Based on the design of the multi-source collaborative optimization operation structure of the integrated energy system, multiple objective functions are set, including the maximization of investment return rate, the maximization of carbon emission reduction rate, and the minimization of energy abandonment rate. The calculation example analysis shows that when multi-energy energy conversion equipment participates in the system for coordinated operation, it will cause the depreciation cost of the unit to increase continuously, resulting in a certain increase in the net benefit of the integrated energy system. In addition, electrical conversion equipment can effectively reduce waste energy and improve the effective utilization of clean energy, thereby increasing the carbon emission reduction rate. The results of the calculation examples effectively verify that optimizing energy conversion efficiency has a positive effect on alleviating clean energy consumption.

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Planning and operation method of the regional integrated energy system considering economy and environment

Cited by 160 publications

References 16 publications

Interval optimization based operational strategy of integrated energy system under renewable energy resources and loads uncertainties

Interval optimization based operational strategy of integrated energy system under renewable energy resources and loads uncertainties

IES configuration method considering peak‐valley differences of tie lines and operation costs of power grids

Comprehensive energy cooperative optimization model based on energy conversion efficiency considering investment benefit

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