Coordinated Optimization of Electric-Heating Flexible Resources Considering Sub-Regional Autonomy in Regional Integrated Energy Systems

LIU Dong, LIU Jialing, LI Fan, WANG Dan, SI Yuan, QIN Boyu, WANG Xiuli

Electric Power Construction ›› 2026, Vol. 47 ›› Issue (10) : 85-96.

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Electric Power Construction ›› 2026, Vol. 47 ›› Issue (10) : 85-96. DOI: 10.12204/j.issn.1000-7229.2026.10.007
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Coordinated Optimization of Electric-Heating Flexible Resources Considering Sub-Regional Autonomy in Regional Integrated Energy Systems

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Abstract

[Objective] With the growing demand for efficient energy management, regional integrated energy systems (RIES) urgently need to tap the multi-type flexible regulation potential. However, the benefit allocation among multiple types of participants and the coordinated operation of diverse flexible regulation resources face significant challenges. This paper proposes a coordinated optimization method for multiple flexible resources considering the autonomy capability of sub-regions. [Methods] First, a system operation architecture and trading mechanism are established, covering multiple flexible regulation resources such as energy storage, user-side demand response, and controllable electric/thermal sources. A quantitative index system for regional autonomy capability is proposed and embedded into the operational constraints of sub-regions. Second, a master-slave game-based bi-level coordinated scheduling model is proposed that accounts for the cooperation between the RIES and sub-regional systems (SRS). The RIES supplier and SRS operators act as responsive entities in a single-leader multi-follower game optimization framework. At the upper level, the RIES supplier formulates energy pricing mechanisms with the objective of maximizing revenue, thereby incentivizing SRS followers to actively participate in peak-period regulatory dispatching activities. At the lower level, multiple sub-regional aggregator operators act as followers, performing optimal scheduling with the objective of minimizing daily operational costs while satisfying autonomy capability constraints and coordinating leased energy storage, and feeding back the electricity demand to the upper level. Finally, the effectiveness of the proposed model is verified through case studies. [Results] Compared with the scenario that disregards regional autonomy requirements and lacks energy storage sharing, the proposed method effectively enhances the regulation capability of each sub-region, and the overall system autonomy capability is improved by 3.466%. [Conclusions] The master-slave game-based coordinated optimization method constructed in this paper can effectively leverage the regulation potential of energy storage, providing a feasible solution for improving the economic efficiency and operational performance of multi-sub-regional interconnected systems.

Key words

integrated energy system / regional autonomy capability / multiple flexible resources / master-slave game / optimized operation

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LIU Dong , LIU Jialing , LI Fan , et al . Coordinated Optimization of Electric-Heating Flexible Resources Considering Sub-Regional Autonomy in Regional Integrated Energy Systems[J]. Electric Power Construction. 2026, 47(10): 85-96 https://doi.org/10.12204/j.issn.1000-7229.2026.10.007

附录A

A.1 均衡解存在证明

根据构建的模型可知,上层领导者区域运营商策略集为 $\mathit{\lambda }=\{{\mathit{\lambda }}_{\mathrm{e},\mathit{t}}^{\mathrm{G}\mathrm{O},\mathrm{s}},{\mathit{\lambda }}_{\mathrm{e},\mathit{t}}^{\mathrm{G}\mathrm{O},\mathrm{b}},{\mathit{\lambda }}_{\mathrm{h},\mathit{t}}^{\mathrm{G}\mathrm{O}}\}$,跟随者子区域聚合运营商策略集为 ${\mathit{X}}_{\mathit{l}}=\{\mathrm{\Delta }{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{L},\mathrm{s}},{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{H},\mathrm{e}},{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{e}\mathrm{s}\mathrm{s}},\mathrm{\Delta }{\mathit{W}}_{\mathit{l},\mathit{t}}^{\mathrm{H}\mathrm{L},\mathrm{c}}\}$,根据文献[1]可知,当博弈满足以下条件时,Stackelberg博弈均衡解存在:1)博弈参与的领导者与跟随者的效用函数均为关于各自策略集合的非空连续函数;2)跟随者的效用函数是关于其策略集合的连续拟凹/凸函数。

证明1):对于所有博弈参与者的策略集合均为博弈策略空间中的有界闭集,显然成立。

证明2): ${\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{L},\mathrm{c}\mathrm{l}}>0$, ${\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{e}\mathrm{s}\mathrm{s}}>0$(其余情况同理可证明),子区域聚合商收益可表示为:

$\begin{aligned} F_{l}^{\mathrm{SAGG}}= & \sum_{t=1}^{N_{\mathrm{T}}}\left[v_{\mathrm{e}} L_{\mathrm{e}, t} \Delta t-\frac{\alpha_{\mathrm{e}}}{2} L_{\mathrm{e}, t}^{2} \Delta t^{2}+v_{\mathrm{h}} L_{\mathrm{h}, t} \Delta t-\right. \\ & \frac{\alpha_{\mathrm{h}}}{2} L_{\mathrm{h}, t}^{2} \Delta t^{2}+c-\lambda_{\mathrm{e}, t}^{\mathrm{GO}, \mathrm{~s}} P_{l, t}^{\mathrm{ELecl}} \Delta t- \\ & \lambda_{\mathrm{h}, t}^{\mathrm{GO}} W_{l, t}^{\mathrm{HL}, \mathrm{cl}} \Delta t-F_{l, t}^{\text {ser }}-\beta^{\mathrm{HL}, \mathrm{c}} \Delta W_{l, t}^{\mathrm{HL}, \mathrm{c} 2}- \\ & \left.\mu_{t}^{\text {ser }} P_{l, t}^{\text {ess }} \Delta t\right]+F_{l}^{\mathrm{tr}} \end{aligned}$

式中: ${\mathit{L}}_{\mathrm{e},\mathit{t}}={\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{L},\mathrm{f}}+{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{L},\mathrm{s}}+\mathrm{\Delta }{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{L},\mathrm{s}}+{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{H},\mathrm{e}}+{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{e}\mathrm{s}\mathrm{s}}$, ${\mathit{L}}_{\mathrm{h},\mathit{t}}={\mathit{W}}_{\mathit{l},\mathit{t}}^{\mathrm{H}\mathrm{L},\mathrm{f}}+{\mathit{W}}_{\mathit{l},\mathit{t}}^{\mathrm{H}\mathrm{L},\mathrm{c}}+\mathrm{\Delta }{\mathit{W}}_{\mathit{l},\mathit{t}}^{\mathrm{H}\mathrm{L},\mathrm{c}}$均为决策变量的线性函数; ${\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{L},\mathrm{c}\mathrm{l}}$和 ${\mathit{W}}_{\mathit{l},\mathit{t}}^{\mathrm{H}\mathrm{L},\mathrm{c}\mathrm{l}}$由功率平衡方程表达为决策变量的线性函数。目标函数中一次项均为决策变量的线性函数,二次项各系数均为正实数,故均为严格凹函数。 ${\mathit{F}}_{\mathit{l}}^{\mathrm{t}\mathrm{r}}$和c为常数项。线性函数与凹函数的有限正线性组合仍为凹函数。

A.2 均衡解唯一证明

根据文献[2]可知,当博弈满足以下条件时,Stackelberg博弈均衡解唯一:1)对于领导者给出的策略,跟随者存在唯一最优策略;2)对于跟随者给出的策略,领导者存在唯一最优策略。

证明1):以 ${\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{L},\mathrm{c}\mathrm{l}}>0$, ${\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{e}\mathrm{s}\mathrm{s}}>0$为例(其余情况同理可证明)。对 ${\mathit{F}}_{\mathit{l}}^{\mathrm{S}\mathrm{A}\mathrm{G}\mathrm{G}}$分别求关于 $\mathrm{\Delta }{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{L},\mathrm{s}},{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{H},\mathrm{e}},{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{e}\mathrm{s}\mathrm{s}},{\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{P}\mathrm{V}},\mathrm{\Delta }{\mathit{W}}_{\mathit{l},\mathit{t}}^{\mathrm{H}\mathrm{L},\mathrm{c}},{\mathit{W}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{H},\mathit{h}}$的二阶偏导,如式(A2)—(A5)所示,该函数分别关于各策略存在极大值点。因此,当领导者策略给定以后,跟随者也存在唯一最优解。

$\frac{\partial^{2} F_{l}^{\text {SAGG }}}{\partial\left(\Delta P_{l, t}^{\text {EL, s }}\right)^{2}}=-\alpha_{e}<0$
$\frac{\partial^{2} F_{l}^{\mathrm{SAGG}}}{\partial\left(P_{l, t}^{\mathrm{EH}, \mathrm{e}}\right)^{2}}=-\alpha_{\mathrm{e}}<0
$\frac{\partial^{2} F_{l}^{\mathrm{SAGG}}}{\partial\left(P_{l, t}^{\mathrm{ess}}\right)^{2}}=-\alpha_{\mathrm{e}}<0$
$\frac{\partial^{2} F_{l}^{\text {SAGG }}}{\partial\left(\Delta W_{l, t}^{\text {HL, c }}\right)^{2}}=-\alpha_{\mathrm{h}}<0$

证明2):以 ${\mathit{P}}_{\mathit{l},\mathit{t}}^{\mathrm{E}\mathrm{L},\mathrm{c}\mathrm{l}}>0$, ${\mathit{W}}_{\mathit{l},\mathit{t}}^{\mathrm{H}\mathrm{L},\mathrm{c}\mathrm{l}}>0$为例,其余情况类似。将跟随者一组最优解代入FGO,由于领导者策略空间由价格边界约束,领导者FGO效益函数的Hessian矩阵如式(A6)所示。Hessian矩阵是负定的,因此存在极大值点。

$\mathit{H}=\left[\begin{array}{ccc}-1/{\mathit{\alpha }}_{\mathrm{e}}& 0& 0\\ 0& -1/{\mathit{\alpha }}_{\mathrm{e}}& 0\\ 0& 0& -1/{\mathit{\alpha }}_{\mathrm{h}}\end{array}\right]<0$

当跟随者取其他极值点时,同理也可证明领导者存在唯一最优解,证明与上述过程类似。综上所述,所提主从博弈模型存在唯一的Stackelberg均衡解。

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Footnotes

利益冲突声明(Conflict of Interests): 所有作者声明不存在利益冲突。

作者贡献声明(Authors’ Contributions): 刘栋提出研究概念与基本框架,明确研究方向,设计论文整体框架,负责数据收集与采集,并参与论文修订;刘佳玲负责论文初稿的起草与后续修订工作;李凡参与研究方向的制定,确定研究对象与范围,设计研究思路与整体研究方案,并参与论文修订;王丹开展研究方案的可行性调查与分析,实施研究过程,并承担数据清洗与分析工作;司远提供软件支持,保障研究所需技术工具的开发与应用;秦博宇设计研究思路,承担数据清洗与分析工作;王秀丽参与论文修订,协助完善论文内容表达。所有作者均阅读并同意了终稿内容。

Funding

2024 Special Major Science and Technology Project for the "Scaling Heights" Action Plan on New Power System Technology Innovation(1400-202456361A-3-1-DG)
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