Robust energy systems scheduling considering uncertainties and demand side emission impacts

Wang, Yunqi; Qiu, Jing; Tao, Yuechuan

doi:10.1016/j.energy.2021.122317

Cited by 25 publications

(6 citation statements)

References 32 publications

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“…As shown in Table 8, Case 1 is the proposed WTG-DSB coordinated expansion planning considering the BCT mechanism. Cases 2 and 3 are the WTG and DSB coordinated expansion planning only consider- ing the source-side or load-side unilateral carbon trading (UCT) referenced from [25,39]. The specific results of WTG and DSB capacity planning are shown in Figure 10.…”

Section: Comparison Of Results Under Different Carbon Trading Mechanismsmentioning

confidence: 99%

A bi‐layer stochastic coordinated planning framework for wind‐battery power systems considering bilateral carbon trading

Nan

Feng

Deng

et al. 2022

IET Generation Trans & Dist

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Renewable energy and energy storage are essential technologies for decarbonizing energy systems. Expansion planning of the two technologies considering source-side carbon responsibility has been well studied. However, expansion planning considering both source-side and load-side carbon responsibility, which may simultaneously stimulate the carbon reduction potential of source and load, has been rarely studied. To fill this research gap, this paper proposes a bi-layer wind turbine generator (WTG) and demand-side battery (DSB) coordinated planning framework considering wind power and load uncertainties. Moreover, a novel source-load bilateral carbon trading (BCT) mechanism based on the Aumann-Shapley method is proposed to stimulate the WTG and DSB configuration. In the bi-layer planning framework with BCT mechanism, WTG and DSB capacity planning with the two-stage stochastic optimization are conducted in the upper and lower layer, respectively. Finally, test results on a modified IEEE 24-bus system demonstrate that the proposed framework with BCT mechanism can effectively motivate the planning configuration of WTG and DSB and carbon mitigation. Compared with the models with unilateral carbon trading mechanisms, the proposed model has advantages in stimulating configuration of WTG and DSB, reducing carbon emissions, and balancing source-load economic burden from carbon trading.

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Section: Comparison Of Results Under Different Carbon Trading Mechanismsmentioning

confidence: 99%

A bi‐layer stochastic coordinated planning framework for wind‐battery power systems considering bilateral carbon trading

Nan

Feng

Deng

et al. 2022

IET Generation Trans & Dist

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“…ADNs locally contribute to the power generation process through the integration of DG and ESS units. As a result, rather than minimizing total planning and operating costs, distribution companies (DISCOs) tend to increase their profit from selling energy to end users [15]. In deregulated electricity markets, electricity companies at different levels aim to maximize their revenues.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Conventional methods, such as the analytical method proposed in [11], have been used. Linear programming (LP) [20], mixed-integer LP (MILP) [21], and mixed-integer nonlinear programming (MINLP) [13,15] have been applied to build the proposed models. The main advantage of LP and NLP methods is their solvability with a variety of commercial solvers such as MOSEK [13] and IPOPT [15].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Linear programming (LP) [20], mixed-integer LP (MILP) [21], and mixed-integer nonlinear programming (MINLP) [13,15] have been applied to build the proposed models. The main advantage of LP and NLP methods is their solvability with a variety of commercial solvers such as MOSEK [13] and IPOPT [15]. Nonetheless, the functions and codes of these solvers are masked and cannot be edited or modified.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Evolutionary Approach for DISCO Profit Maximization by Optimal Planning of Distributed Generators and Energy Storage Systems in Active Distribution Networks

Mahfoud,

Alkayem,

Fernandez-Rodriguez

et al. 2024

Mathematics

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Distribution companies (DISCOs) aim to maximize their annual profits by performing the optimal planning of distributed generators (DGs) or energy storage systems (ESSs) in the deregulated electricity markets. Some previous studies have focused on the simultaneous planning of DGs and ESSs for DISCO profit maximization but have rarely considered the reactive powers of DGs and ESSs. In addition, the optimization methods used for solving this problem are either traditional or outdated, which may not yield superior results. To address these issues, this paper simultaneously performs the optimal planning of DGs and ESSs in distribution networks for DISCO profit maximization. The utilized model not only takes into account the revenues of trading active and reactive powers but also addresses the active and reactive powers of DGs and ESSs. To solve the optimization problem, a new hybrid evolutionary algorithm (EA) called the oppositional social engineering differential evolution with Lévy flights (OSEDE/LFs) is proposed. The OSEDE/LFs is applied to optimize the planning model using the 30-Bus and IEEE 69-Bus networks as test systems. The results of the two case studies are compared with several other EAs. The results confirm the significance of the planning model in achieving higher profits and demonstrate the effectiveness of the proposed approach when compared with other EAs.

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“…CRO formulates the source-load uncertainty with the uncertainty set, i.e., the maximum possible space of uncertain scenarios. A two-stage robust unit commitment based on it is established (Bertsimas et al, 2013;Zhou et al, 2019), and the day-ahead scheduling is usually solved with the Benders duality method (Yang and Su, 2021) or column and constraint generation (C&CG) methods (Wang et al, 2022). Moreover, the regulation of energy storages is incorporated in the unit commitment, and a nested C&CG is developed to address the integer state variables of energy storages in the intraday regulation (Cobos et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Real-time low-carbon scheduling for the wind–thermal–hydro-storage resilient power system using linear stochastic robust optimization

Qiu

Zhang³

et al. 2023

Front. Energy Res.

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With the large-scale wind power integration, power systems have to address not only the conventional power demand fluctuations but also the wind uncertainty. To improve the economical effectiveness, resilience, and environmental protection of power systems in the source-load uncertainty, a real-time low-carbon scheduling for the wind–thermal–hydro-storage integrated system is proposed. The power imbalance caused by the uncertainty is neutralized by the synergetic linear decision of multiple resources. To address the source-load uncertainty, a stochastic robust optimization is introduced, which establishes the system constraints by robust optimization for the resilience operation, while optimizing the expected operation cost in the empirical uncertainty distribution for economic efficiency. Moreover, a multi-point estimation is applied to formulate the expected operation cost precisely and quickly. By using the dual theory, the proposed real-time power scheduling is derived as a mixed integer bilinear constrained programming. A multi-step sequential convexified solution is developed to solve the complex scheduling problem, which linearizes the bilinear constraints with alternate optimization and relaxes the state variables of energy storages with an “estimation–correction” strategy. Finally, case studies show the superiority of the proposed scheduling method and convexified solution.

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Robust energy systems scheduling considering uncertainties and demand side emission impacts

Cited by 25 publications

References 32 publications

A bi‐layer stochastic coordinated planning framework for wind‐battery power systems considering bilateral carbon trading

A bi‐layer stochastic coordinated planning framework for wind‐battery power systems considering bilateral carbon trading

Evolutionary Approach for DISCO Profit Maximization by Optimal Planning of Distributed Generators and Energy Storage Systems in Active Distribution Networks

Real-time low-carbon scheduling for the wind–thermal–hydro-storage resilient power system using linear stochastic robust optimization

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