Modeling and optimal dispatch of a carbon-cycle integrated energy system for low-carbon and economic operation

Zhang, Guangming; Wang, Wei; Chen, Zhenyu; Li, Ruilian; Niu, Yuguang

doi:10.1016/j.energy.2021.122795

Cited by 73 publications

(16 citation statements)

References 18 publications

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“…X. Zhang et al, [19] also integrate PCC into MES infrastructure with the aim of utilizing the captured CO2 as synthetic fuel. G. Zhang et al [20] went a step further with the introduction of supercritical-CO2 unit to aid power generation using the captured CO2 within the MES. However, none of these studies considered the PCC capacity constraint on the amount of captured CO2 and the possible release CO2 to the environment.…”

Section: Related Research Workmentioning

confidence: 99%

Automated deep reinforcement learning for real-time scheduling strategy of multi-energy system integrated with post-carbon and direct-air carbon captured system

et al. 2023

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Section: Related Research Workmentioning

confidence: 99%

Automated deep reinforcement learning for real-time scheduling strategy of multi-energy system integrated with post-carbon and direct-air carbon captured system

et al. 2023

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“…The model of the CC unit can be written as follows [66]:

\begin{equation}\left\{ \def\eqcellsep{&}\begin{array}{l} P_t^{cc} = {P}^{cc,b} + P_t^{cc,r}\\[4pt] P_t^{cc,r} = {\varepsilon }^{e,cc}m_t^{c{o}_2,c} = {\varepsilon }^{e,cc}{\eta }^{cc}m_t^{c{o}_2}\\[4pt] m_t^{c{o}_2} = {\varepsilon }^{gt,c{o}_2}P_t^{gt} + {\varepsilon }^{gb,c{o}_2}Q_t^{gb} \end{array} \right.\end{equation}

where

P_t^{cc}

{P}^{cc,b}

and

P_t^{cc,r}

are the total energy consumption, the basic energy consumption, and the operating energy consumption of the CC unit in the period t , respectively;

{\varepsilon }^{e,cc}

and

{\eta }^{cc}

are the electric power consumed by capturing a unit quantity of CO 2 and the carbon capture efficiency;

m_t^{c{o}_2}

and

m_{t}^{c o_{2}, c}

…”

Section: System Descriptionmentioning

confidence: 99%

Low‐carbon economic dispatch of the combined heat and power‐virtual power plants: A improved deep reinforcement learning‐based approach

Tan

Shen

et al. 2022

IET Renewable Power Gen

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To realize the national strategies for carbon emission reduction, electric power industries should undergo reforms to cope with the multiple challenges of decarbonization, marketization, and energy transition. How to design a dispatch strategy that considers both low‐carbon demand and economic cost has become a major concern in integrated energy systems. To realize multi‐energy complementation and low‐carbonization, a scheduling framework of combined heat and power‐virtual power plants (CHP‐VPPs) considering carbon capture and power‐to‐gas is proposed. The stochastic dynamic optimization problem is modelled as a Markov decision process. An improved deep reinforcement learning‐based algorithm named multi‐level backtracking prioritized experience replay‐twin delayed deep deterministic policy gradient (MBEPR‐TD3) is employed to solve the low‐carbon economic dispatch problem. The results show that: (1) The profits have been increased by 85.8% and carbon emissions have been reduced by 30.3% because of the addition of power‐to‐gas in CHP‐VPP; (2) the revenues have been improved by 22.24% and carbon emissions have been decreased by 37.04% owing to the introduction of carbon capture and trading; (3) compared with results using DQN, DDPG, and TD3, the optimal dispatch strategy obtained by MBEPR‐TD3 has higher reward returns and more stable convergence.

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“…At the same time, the integrated energy system (IES) integrates various energy forms and includes the links between energy production, transmission, and consumption [2]. The construction of IES is an important technical means to improve the consumption of high-proportion renewable energies and control carbon dioxide emissions, which is of great practical significance for promoting energy transformation and ensuring low-carbon economic operation of the system [3].…”

Section: Introductionmentioning

confidence: 99%

Two-Stage Low-Carbon Economic Dispatch of Integrated Demand Response-Enabled Integrated Energy System with Ladder-Type Carbon Trading

Zhang¹,

Li²,

Zhao³

et al. 2023

Energy Engineering

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Driven by the goal of "carbon neutrality" and "emission peak", effectively controlling system carbon emissions has become significantly important to governments around the world. To this end, a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response (IDR) is proposed in this paper for the integrated energy system (IES), where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR. In contrast, the second stage minimizes the system total cost to optimize the outputs of generations with consideration of the uncertainty of renewables. In addition, to fully exploit the system's emission reduction potential, a carbon trading cost model with segmented CO 2 emission intervals is built by introducing a reward-penalty ladder-type carbon trading mechanism, and the flexible thermal comfort elasticity of customers is taken into account by putting forward a predicted mean vote index on the load side. The CPLEX optimizer resolves the two-stage model, and the study results on a modified IES situated in North China show the proposed model can effectively reduce carbon emissions and guarantee economical efficiency operation of the system. KEYWORDS Integrated energy system; low-carbon economic dispatch; integrated demand response; ladder-type carbon trading; thermal comfort elasticity

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Modeling and optimal dispatch of a carbon-cycle integrated energy system for low-carbon and economic operation

Cited by 73 publications

References 18 publications

Automated deep reinforcement learning for real-time scheduling strategy of multi-energy system integrated with post-carbon and direct-air carbon captured system

Automated deep reinforcement learning for real-time scheduling strategy of multi-energy system integrated with post-carbon and direct-air carbon captured system

Low‐carbon economic dispatch of the combined heat and power‐virtual power plants: A improved deep reinforcement learning‐based approach

Two-Stage Low-Carbon Economic Dispatch of Integrated Demand Response-Enabled Integrated Energy System with Ladder-Type Carbon Trading

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