Distributionally robust planning for integrated energy systems incorporating electric-thermal demand response

He, Shuaijia; Gao, Hongjun; Wang, Lingfeng; Xiang, Yingmeng; Liu, Junyong

doi:10.1016/j.energy.2020.118783

Cited by 52 publications

(8 citation statements)

References 23 publications

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“…Upward and downward adjustment flexibility margin is presented in ( 16) and (17). Flexibility surplus can be expressed by (18). This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.…”

Section: A Flexibility Surplusmentioning

confidence: 99%

“…The parallel of many distributed power sources brings uncertainty to the distribution network system, so the fluctuation and intermittence of their output should be fully considered in the optimal dispatching of the system. At present, the main methods to study the output uncertainty of distributed power generation are stochastic optimization, chance-constrained optimization, robust optimization and distributed robust optimization [18], [19]. Stochastic optimization reduces DERs output scenario by sampling and sets it to obey a certain probability to transform it into a scene-based optimization model.…”

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confidence: 99%

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Optimal Dispatching of Distribution Network Considering System Flexibility and User Thermal Comfort

et al. 2021

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To solve the problem that the uncertainty of distributed generation output seriously affects the safe and stable operation of distribution network, heat load, as a potential flexibility resource, can improve flexibility and eliminate system fluctuation without increasing new equipment. Therefore, an optimal dispatching model of the distribution network is proposed in this paper to improve the system flexibility while ensuring human comfort and operation economy. Firstly, the virtual energy storage model and human thermal comfort model of electric water heater (EWH) and air conditioning (AC) load are established. Secondly, a flexibility evaluation method is proposed based on the virtual energy storage of heat load. Furthermore, to decrease comprehensive operation cost and increase system flexibility, a two-stage distributed robust optimal dispatching model, which considers three kinds of flexible resources of EWH, AC and gas turbine (GT) is constructed. Then, the norm is used to constrain the uncertainty probability of wind turbine and photovoltaic output, and the column and constraints generation (C&CG) algorithm is used to solve the model. Finally, a simulation is given to verify the effectiveness of the proposed method in improving the flexibility of distribution network.

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Section: A Flexibility Surplusmentioning

confidence: 99%

mentioning

confidence: 99%

Optimal Dispatching of Distribution Network Considering System Flexibility and User Thermal Comfort

et al. 2021

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“…By leveraging the advantages of stochastic programming and robust optimization, distributionally robust optimization (DRO) has gain increasing popularity in recent integrated energy system planning and operations studies [17][18][19][20][21][22][23]. It brings important characteristics such as adjustable conservativeness level and not requiring the uncertainty source's true probability distribution [19,20].…”

Section: Reversible Voltage U Tnmentioning

confidence: 99%

“…There are different paradigms to construct the ambiguity set in the literature. The studies [9,[22][23][24] constructed their ambiguity sets based on the first and second order moment information, while in [17,21] more general moment information was adopted to achieve less conservative results. The authors in [19] built the ambiguity set based on 1-norm and inf-norm constraints, which allows a simpler solution method.…”

Section: Reversible Voltage U Tnmentioning

confidence: 99%

Distributionally Robust Chance-Constrained Flexibility Planning for Integrated Energy System

Zhan¹,

Hou²,

Yang³

2021

Preprint

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Inflexible combined heat and power (CHP) plants and uncertain wind power production result in excess power in distribution networks, which leads to inverse power flow challenging grid operations. Power-to-X facilities such as electrolysers and electric boilers can offer extra flexibility to the integrated energy system. In this regard, we aim to jointly determine the optimal Power-to-X facility sizing and integrated energy system operations in this study. To account for wind power uncertainties, a distributionally robust chance-constrained model is developed to characterize wind power uncertainties using ambiguity sets. Linear decision rules are applied to analytically express real-time recourse actions when uncertainties are exposed, which allows the propagation of wind power uncertainties to gas and heat systems. Accordingly, the developed three-stage distributionally robust chance-constrained model is converted into a computationally tractable single-stage mixed-integer conic model. A case study validates the effectiveness of introducing the electrolyser and electric boiler into the integrated energy system, with respect to the decreased system cost, expanded CHP plant flexibility and reduced inverse power flow. The developed distributionally robust optimization model exhibits better effectiveness and robustness compared to a chance-constrained optimization model assuming wind forecast errors follow Gaussian distribution. Detailed profit analysis reveals that although the overall system cost is minimized, the profit is distributed unevenly across various stakeholders in the system. The profit mainly falls with the wind power plants, which therefore are most motivated to make investments in the flexibility resources. Other parties rely on additional policies such as bilateral contracts with the wind power plants to gain incentives to invest. The findings from this study can be used to motivate policy-makers to make proper regulations to incentivize investments in flexibility resources and establish a more reliable power grid.

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“…On the one hand, energy can support each other to improve the reliability of energy supply; on the other hand, due to the multi‐energy coupling, the failure of one energy supply system may affect the overall system. In addition, under the background of energy Internet, the traditional power demand response is gradually developed into a comprehensive demand response suitable for energy Internet [3]. It has become an urgent problem to evaluate the reliability of regional energy Internet (REI) under multi‐energy coupling and integrated demand response.…”

Section: Introductionmentioning

confidence: 99%

Reliability evaluation of regional energy Internet considering electricity–gas coupling and coordination between energy stations

Liu

Zhao

et al. 2021

IET Energy Syst Integration

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In view of the issues that the current comprehensive energy supply reliability evaluation mainly focuses on the distributed energy system and rarely involves the mutual coupling of energy supply networks and the coordination of energy stations in the regional energy Internet, an evaluation method of energy supply reliability considering electricity-gas coupling and coordination between energy stations was proposed. First, the framework of regional energy Internet (REI) is established, the energy flow relationship among the main parts in the REI and the influence of electricity-gas coupling on reliability are analysed; second, considering building virtual energy storage and demand response, the rigid and flexible reliability evaluation indexes are proposed from the energy and time levels; third, the operation strategies of normal, failure and repair periods of each energy station are put forward, and the optimal load reduction model of REI aiming at the minimum total rigid energy shortage is established. Moreover, the method and process of energy supply reliability evaluation combining fault mode effect analysis (FMEA) and Monte Carlo simulation are proposed. Finally, through a practical example, the impact of demand response, multiple energy storage resources, electricity-gas coupling and interstation coordination on reliability is analysed.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Distributionally robust planning for integrated energy systems incorporating electric-thermal demand response

Cited by 52 publications

References 23 publications

Optimal Dispatching of Distribution Network Considering System Flexibility and User Thermal Comfort

Optimal Dispatching of Distribution Network Considering System Flexibility and User Thermal Comfort

Distributionally Robust Chance-Constrained Flexibility Planning for Integrated Energy System

Reliability evaluation of regional energy Internet considering electricity–gas coupling and coordination between energy stations

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