A novel forecast scenario-based robust energy management method for integrated rural energy systems with greenhouses

Tan, Hong; Liu, Zhenxing; Wang, Qiujie; Mohamed, Mohamed A.

doi:10.1016/j.apenergy.2022.120343

Cited by 23 publications

(5 citation statements)

References 35 publications

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“…Currently, biogas plants (BP) usually adopt medium-temperature fermentation process, the internal temperature of biogas digester is controlled at about 35-40 ℃, which is the most economical temperature range for the operation of biogas digesters. Tan et al [7] proposed increased the biogas yield by injecting hot water into the digester, at the same time a storage tank was set up outside the digester to ensure the reliability of the biogas supply. However, this method did not consider the effect of the uncertainty of ambient temperature on the system.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The operation of IES relies on the synergistic cooperation of multiple stakeholders, and the basic problem to be solved is how to describe the large-scale complex system and the interaction between different stakeholders [6][7][8] . Stackelberg game is one of the most important methods to solve the conflict of interests of different market players.…”

Section: Introduction 1backgroundmentioning

confidence: 99%

“…( 6) Calculate the fitness function, output and record the best individual whose fitness value is the largest. (7) The new population with higher fitness is generated through the process of mutation, crossover and selection. The mutation strategy is the composite strategy introduced above.…”

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confidence: 99%

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Scheduling of integrated biogas energy system for rural areas using improved differential evolutionary algorithm

Lv,

Gao

2024

Infor. Syst. Smart. City

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Due to lack of rational system design, an enormous amount of energy and resources are wasted or ineffectively utilized in China’s rural areas. Therefore, it is crucial to develop a practical energy system that applies to rural areas. In this paper, a Stackelberg game model is established for optimization of integrated energy system (IES) in rural areas. As a leader, new energy supplier (NES) develops price strategy for electricity and heat, the flexible users and biogas plant (BP) as followers receive price information and make energy consumption plans. Then NES adjusts equipment output based on followers’ feedback on energy loads. The objective of our Stackelberg game is to maximize the profit of NES while taking into account the costs of followers. Furthermore, our study designs an improved differential evolutionary algorithm (DEA) to achieve Stackelberg balance. The optimization scheduling result shows that the proposed model can obviously increase the profit of NES by 5.4% and effectively decrease the cost of biogas plant by 4.5%.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introduction 1backgroundmentioning

confidence: 99%

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Scheduling of integrated biogas energy system for rural areas using improved differential evolutionary algorithm

Lv,

Gao

2024

Infor. Syst. Smart. City

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“…The model further resolved the problem of asynchrony between the electric load and the thermal load. Tan et al (2023) introduced a cooperative operation framework for an integrated rural energy system with greenhouses. The framework utilizes a rural biogas digester to supply fuel to CHP.…”

Section: Introductionmentioning

confidence: 99%

Integrated energy system optimization and scheduling method considering the source and load coordinated scheduling of thermal-storage electric boilers and electric vehicles

Yang,

Wu,

Zhang

et al. 2023

Front. Energy Res.

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The northern regions of China face the challenges of the mismatch of the power supply and demand, as well as serious wind curtailment issues, caused mainly by the limitation of the “with heat to determine electricity” mode for combined heat and power generation during the winter season. To further absorb the surplus wind power and alleviate restrictions, a comprehensive energy system optimization method for parks based on coordinated scheduling between sources and loads is proposed in this paper. First, the implementation of a heat-storage electric boiler on the source side further achieves the decoupling of heat and power. Second, an optimized scheduling method for electric vehicles combining incentive scheduling and orderly scheduling is proposed on the load side, which helps flatten the load curve. Finally, a tiered carbon trading mechanism is introduced and a community integrated energy system (CIES) optimization scheduling model is established with the aim of minimizing the total cost of the CIES, and the problem is solved using the CPLEX commercial solver. The simulation results indicate that the overall system efficiency is significantly improved through the coordinated scheduling of power sources and loads. Specifically, the integration rate of wind power increases by 3.91% when compared to the sole consideration of the integrated demand response. Furthermore, the peak shaving and off-peak filling effect is considerably enhanced compared to the utilization of only thermal-storage electric boilers. Additionally, the implementation of coordinated scheduling leads to a reduction in the total system cost by 2764.32 yuan and a decrease in total carbon emissions by 3515.4 kg. These findings provide compelling evidence that the coordinated scheduling of power sources and loads surpasses the limitations of thermal power units, strengthens the demand response capability of electric vehicles, and enhances the economic benefits of the CIES.

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“…In [14], energy management approach for integrated rural energy systems (IRES) with greenhouses addresses the inefficiency and environmental concerns of traditional rural energy sources. The proposed method incorporates local renewable resources like biogas and wind power while optimizing electricity and heat supply.…”

Section: Introductionmentioning

confidence: 99%

PSO-ANFIS-Based Energy Management in Hybrid AC/DC Microgrid along with Plugin Electric Vehicle

Ashokkumar,

Venkatramanan

2023

International Journal of Photoenergy

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This study proposes a hybrid AC/DC microgrid with plugin EVs, leveraging PSO-tuned ANFIS for voltage and power control. With the existing control, which faced challenges such as instability and complexity, the proposed approach is aimed at simplifying control through PSO, efficient power sharing, and reduced sample requirements. This innovative method contributes to improved energy management in hybrid microgrids, bridging existing research gaps. This approach streamlines neural transmission in microgrid control, addressing challenges in distributed generation power, load demand, energy storage system SOC, and AC grid power integration. Notably, the proposed PSO-ANFIS simplifies electric vehicle power references using distinct inputs for each mode, trained through PSO. This methodology is tailored for microgrids with varying power profiles, presenting a promising solution for efficient energy management. The proposed EMS was experimentally verified using MATLAB simulations of a small-scale hybrid AC/DC microgrid for every operating mode. The financial dynamics of a microgrid’s power exchange with the main grid are examined through three distinct methodologies: fuzzy logic, ANFIS (adaptive neurofuzzy inference system), and PSO-ANFIS (ANFIS optimized using particle swarm optimization). In case 1, the PSO-ANFIS approach demonstrates its superiority by achieving the lowest grid purchase power cost of 1995.24 Rs/day compared to fuzzy (2243.63 Rs/day) and ANFIS (2150.45 Rs/day), while also yielding the highest revenue from power selling to the microgrid: PSO-ANFIS (668.84 Rs/day) surpassing fuzzy (536.12 Rs/day) and ANFIS (575.35 Rs/day). Similarly, in case 2, PSO-ANFIS proves its efficiency with the lowest net price of 8619.192 Rs/day, showcasing its effectiveness in optimizing financial dynamics. Furthermore, in case 3, the revenue aligns precisely with net prices, indicating the PSO-ANFIS method’s financial advantage, generating the highest revenue of 6544.0224 Rs/day compared to fuzzy (6025.36 Rs/day) and ANFIS (6153.214 Rs/day). These findings underscore the potential utility of the PSO-ANFIS approach in optimizing microgrid operations and enhancing cost-effectiveness across various scenarios.

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A novel forecast scenario-based robust energy management method for integrated rural energy systems with greenhouses

Cited by 23 publications

References 35 publications

Scheduling of integrated biogas energy system for rural areas using improved differential evolutionary algorithm

Scheduling of integrated biogas energy system for rural areas using improved differential evolutionary algorithm

Integrated energy system optimization and scheduling method considering the source and load coordinated scheduling of thermal-storage electric boilers and electric vehicles

PSO-ANFIS-Based Energy Management in Hybrid AC/DC Microgrid along with Plugin Electric Vehicle

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