Shiwei Su^1,2, Guangyong Hu², Xianghua Li³, Xin Li², Wei Xiong^2,*

Energy Engineering, Vol.120, No.10, pp. 2343-2368, 2023, DOI:10.32604/ee.2023.028500 - 28 September 2023

Abstract As new power systems and dual carbon policies develop, virtual power plant cluster (VPPC) provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems. To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant, a multi-virtual power plant (VPP) electricity-carbon interaction optimal scheduling model considering integrated demand response (IDR) is proposed. Firstly, a multi-VPP electricity-carbon interaction framework is established. The interaction of electric energy and carbon quotas can realize energy complementarity, reduce energy waste and promote low-carbon operation. Secondly, in order to coordinate the… More > Graphic Abstract

Song Zhang¹, Wensheng Li², Zhao Li², Xiaolei Zhang¹, Zhipeng Lu¹, Xiaoning Ge^3,*

Energy Engineering, Vol.120, No.1, pp. 181-199, 2023, DOI:10.32604/ee.2022.022228 - 27 October 2022

Abstract 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 More >

Jian Dong, Haixin Wang, Junyou Yang^*, Liu Gao, Kang Wang, Xiran Zhou

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 319-340, 2022, DOI:10.32604/cmes.2022.020394 - 02 June 2022

Abstract Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy. This paper studies an electric-gas-heat integrated energy system, including the carbon capture system, energy coupling equipment, and renewable energy. An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost, carbon emission and enhance the power supply reliability. Firstly, the low-carbon mathematical model of combined thermal and power unit, carbon capture system and power to gas unit (CCP) is established. Subsequently, we establish a low carbon multi-objective optimization model considering system operation cost, carbon emissions cost, integrated demand More >