Cuiping Li¹, Jiacheng Sun¹, Qiang Li², Qi Guo², Junhui Li^1,*, Shuo Yu², Jingbo Wang², Wenze Li²

Energy Engineering, Vol.122, No.8, pp. 3055-3077, 2025, DOI:10.32604/ee.2025.064440 - 24 July 2025

Abstract The penetration rate of new wind and photovoltaic energy in the power system has increased significantly, and the dramatic fluctuation of the net load of the grid has led to a severe lack of flexibility in the regional grid. This paper proposes a hierarchical optimal dispatch strategy for a high proportion of new energy power systems that considers the balanced response of grid flexibility. Firstly, various flexibility resource regulation capabilities on the source-load side are analyzed, and then flexibility demand and flexibility response are matched, and flexibility demand response assessment is proposed; then, a hierarchical… More >

Yunfeng Liu, Ximin Cao^*, Yanchi Zhang

Energy Engineering, Vol.122, No.7, pp. 2865-2890, 2025, DOI:10.32604/ee.2025.065419 - 27 June 2025

Abstract Against the backdrop of China’s “dual-carbon” target, clean energy generation currently accounts for about 3.8 trillion kilowatt-hours, or 39.7 percent of total power generation, establishing a reasonable market trading mechanism while enhancing the low-carbon economic benefits of the integrated energy system (IES) and optimizing the interests of various entities within the distribution system has become a significant challenge. Consequently, this paper proposes an optimization strategy for a low-carbon economy within a multi-agent IES that considers carbon capture systems (CCS) and power-to-gas (P2G). In this framework, the integrated energy system operator (IESO) acts as the primary… More >

Bin Jiang¹, Houbin Wang^2,*

Energy Engineering, Vol.122, No.5, pp. 2001-2057, 2025, DOI:10.32604/ee.2025.062765 - 25 April 2025

Abstract Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality, strong coupling, nonlinearity, and non-convexity, a GA-DE multi-objective optimization algorithm based on dual-population pseudo-parallel genetic algorithm-differential evolution is proposed in this paper. The algorithm is based on external elite archive and Pareto dominance, and it adopts the cooperative co-evolution mechanism of differential evolution and genetic algorithm. Average entropy and cubic chaotic mapping initialization strategies are proposed to increase population diversity. In the proposed method, we analyze the distribution of neighboring solutions and apply a new Pareto solution set pruning approach.… More >

Ziwen Cai^1,2, Yun Zhao^1,2, Zongyi Wang^1,2, Tonghe Wang^3,*, Yunfeng Li^1,2, Hao Wang³

Energy Engineering, Vol.122, No.4, pp. 1221-1248, 2025, DOI:10.32604/ee.2025.061452 - 31 March 2025

Abstract With the severe challenges brought by global climate change, exploring and developing clean and renewable energy systems to upgrade the energy structure has become an inevitable trend in related research. The comprehensive park systems integrated with photovoltaic, energy storage, direct current, and flexible loads (PEDF) is able to play an important role in promoting energy transformation and achieving sustainable development. In order to fully understand the advantages of PEDF parks in energy conservation and carbon reduction, this paper summarizes existing studies and prospects future research directions on the low-carbon operation of the PEDF park. This… More >

Zhihui Feng¹, Jun Zhang¹, Jun Lu¹, Zhongdan Zhang¹, Wangwang Bai¹, Long Ma¹, Haonan Lu², Jie Lin^2,*

Energy Engineering, Vol.122, No.4, pp. 1531-1560, 2025, DOI:10.32604/ee.2025.060795 - 31 March 2025

Abstract In the background of the low-carbon transformation of the energy structure, the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy systems (IES) is becoming increasingly obvious. In this case, to promote the low-carbon operation of IES and renewable energy consumption, and to improve the IES anti-interference ability, this paper proposes an IES scheduling strategy that considers CCS-P2G and concentrating solar power (CSP) station. Firstly, CSP station, gas hydrogen doping mode and variable hydrogen doping ratio mode are applied to IES, and combined with… More >

Yaming Ren^1,*, Xing Deng²

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4503-4533, 2025, DOI:10.32604/cmc.2024.059864 - 06 March 2025

Abstract The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution, particularly within multi-area interconnected power grids. This complexity necessitates the employment of distributed solution methodologies, which are not only essential but also highly desirable. In the realm of computational modelling, the multi-area economic dispatch problem (MAED) can be formulated as a linearly constrained separable convex optimization problem. The proximal point algorithm (PPA) is particularly adept at addressing such mathematical constructs effectively. This study introduces parallel (PPPA) and serial (SPPA) variants of the PPA… More >

Shiqian Wang¹, Bo Liu¹, Yuanpeng Hua¹, Qiuyan Li¹, Binhua Tang^2,*, Jianshu Zhou², Yue Xiang²

Energy Engineering, Vol.122, No.1, pp. 129-152, 2025, DOI:10.32604/ee.2024.054867 - 27 December 2024

Abstract This paper introduces a method for modeling the entire aggregated electric vehicle (EV) charging process and analyzing its dispatchable capabilities. The methodology involves developing a model for aggregated EV charging at the charging station level, estimating its physical dispatchable capability, determining its economic dispatchable capability under economic incentives, modeling its participation in the grid, and investigating the effects of different scenarios and EV penetration on the aggregated load dispatch and dispatchable capability. The results indicate that using economic dispatchable capability reduces charging prices by 9.7% compared to physical dispatchable capability and 9.3% compared to disorderly More >

Weidong Chen^1,2,*, Yun Zhao³, Xiaorui Wu^1,2, Ziwen Cai³, Min Guo^1,2, Yuxin Lu³

Energy Engineering, Vol.121, No.10, pp. 3075-3093, 2024, DOI:10.32604/ee.2024.051404 - 11 September 2024

Abstract The integration of photovoltaic, energy storage, direct current, and flexible load (PEDF) technologies in building power systems is an important means to address the energy crisis and promote the development of green buildings. The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid. For this purpose, this work introduces a framework of multiple incentive mechanisms for a PEDF park, a building energy system that implements PEDF technologies. The incentive mechanisms proposed in this paper include both economic and noneconomic… More >

Kaicheng Liu^1,3, Chen Liang², Naiyue Wu^1,3, Xiaoyang Dong², Hui Yu^1,*

Energy Engineering, Vol.121, No.9, pp. 2621-2637, 2024, DOI:10.32604/ee.2024.050001 - 19 August 2024

Abstract This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices. This method integrates features including photovoltaic (PV) systems, energy storage coupling, varied energy roles, and energy supply and demand dynamics. The system model is developed by considering energy devices as versatile units capable of fulfilling various functionalities and playing multiple roles simultaneously. To strike a balance between optimality and feasibility, renewable energy resources are modeled with considerations for forecasting errors, Gaussian distribution, and penalty factors. Furthermore, this study introduces a distributed event-triggered surplus algorithm designed to address the More >

Zhan Shi^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 973-994, 2024, DOI:10.32604/cmc.2024.051530 - 18 July 2024

Abstract The convergence of Internet of Things (IoT), 5G, and cloud collaboration offers tailored solutions to the rigorous demands of multi-flow integrated energy aggregation dispatch data processing. While generative adversarial networks (GANs) are instrumental in resource scheduling, their application in this domain is impeded by challenges such as convergence speed, inferior optimality searching capability, and the inability to learn from failed decision making feedbacks. Therefore, a cloud-edge collaborative federated GAN-based communication and computing resource scheduling algorithm with long-term constraint violation sensitiveness is proposed to address these challenges. The proposed algorithm facilitates real-time, energy-efficient data processing by More >