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

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 the uncertainty of renewables. In… More >

G. Girishkumar^1,*, S. Ganesan², N. Jayakumar³, S. Subramanian⁴

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 609-625, 2023, DOI:10.32604/iasc.2023.027514

Abstract The optimization field has grown tremendously, and new optimization techniques are developed based on statistics and evolutionary procedures. Therefore, it is necessary to identify a suitable optimization technique for a particular application. In this work, Black Widow Optimization (BWO) algorithm is introduced to minimize the cost functions in order to optimize the Multi-Area Economic Dispatch (MAED). The BWO is implemented for two different-scale test systems, comprising 16 and 40 units with three and four areas. The performance of BWO is compared with the available optimization techniques in the literature to demonstrate the strategy’s efficacy. Results show that the optimized cost… 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

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 response, wind and photovoltaic curtailment,… More >

Murad A. A. Almekhlafi¹, Fahd N. Al-Wesabi^2,3, Anwer Mustafa Hilal⁴, Manar Ahmed Hamza^4,*, Abdelzahir Abdelmaboud⁵, Mohammed Rizwanullah⁴

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 557-571, 2022, DOI:10.32604/iasc.2022.020576

Abstract Using fossil fuels and non-renewable forms of energy has many adverse effects on the global ecosystem, and global demand exceeds the limited available resources. Renewable energy is one of the essential elements of social and economic development in any civilized country. This study comprises a feasibility study of the implementation of PV systems in a hybrid diesel network and analyzes the relationship between the effective uses of photovoltaic systems, the return of energy to the environment, and that country’s national economy. As a potential solution for the public and private utilities, the sunny web design application was used to calculate… More >

M. Bhoopathi^1,*, P. Palanivel²

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 143-159, 2022, DOI:10.32604/iasc.2022.017705

Abstract At present, the restructured electricity market has been a prominent research area and attracted attention. The motivation of the restructuring in the power system is to introduce the competition at various levels and to generate a correct economic signal to reduce the generation cost. As a result, it is required to have an effective price scheme to deliver useful information about the power. The pricing mechanism is dependent on the demand at the load level, the generator bids, and the limits of the transmission network. To address the congestion charges, Locational Marginal Pricing (LMP) is utilized in restructured electricity markets.… More >

Jagannath Paramguru¹, Subrat Kumar Barik¹, Ajit Kumar Barisal², Gaurav Dhiman³, Rutvij H. Jhaveri⁴, Mohammed Alkahtani^5,6, Mustufa Haider Abidi^5,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2863-2882, 2021, DOI:10.32604/cmc.2021.016002

Abstract Economic dispatch has a significant effect on optimal economical operation in the power systems in industrial revolution 4.0 in terms of considerable savings in revenue. Various non-linearity are added to make the fossil fuel-based power systems more practical. In order to achieve an accurate economical schedule, valve point loading effect, ramp rate constraints, and prohibited operating zones are being considered for realistic scenarios. In this paper, an improved, and modified version of conventional particle swarm optimization (PSO), called Oscillatory PSO (OPSO), is devised to provide a cheaper schedule with optimum cost. The conventional PSO is improved by deriving a mechanism… More >