A data-driven approach for microgrid distributed generation planning under uncertainties

Yin, Mingjia; Li, Kang; Yu, James

doi:10.1016/j.apenergy.2021.118429

Cited by 28 publications

(10 citation statements)

References 36 publications

(51 reference statements)

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“…In this paper, the probability characteristic information of distributed energy to reduce the conservatism of decision results. In view of the uncertainty of distributed energy that can be represented as a normal distribution prediction error, this paper optimizes the interval [39,40].…”

Section: Two-stage Robust Optimization Modelmentioning

confidence: 99%

A Two-Stage Robust Optimization Microgrid Model Considering Carbon Trading and Demand Response

Zhang,

Lan,

2023

Sustainability

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To enhance the low-carbon level and economic performance of microgrid systems while considering the impact of renewable energy output uncertainty on system operation stability, this paper presents a robust optimization microgrid model based on carbon-trading mechanisms and demand–response mechanisms. Regarding the carbon-trading mechanism, the baseline allocation method is utilized to provide carbon emission quotas to the system at no cost, and a ladder carbon price model is implemented to construct a carbon transaction cost model. Regarding uncertainty set construction, the correlation of distributed generation in time and space is considered, and a new uncertainty set is constructed based on historical data to reduce the conservative type of robust optimization. Based on the column constraint generation algorithm, the model is solved. The findings indicate that upon considering the carbon-trading mechanism, the microgrid tends to increase the output of low-carbon units and renewable energy units, and the carbon emissions of the microgrid can be effectively reduced. However, due to the increase in power purchase from the distribution network and the increase in carbon transaction costs, the operating costs of the microgrid increase. Secondly, through the utilization of demand–response mechanisms, the microgrid can achieve load transfer between peaks and troughs. It is imperative to establish appropriate compensation costs for demand and response that balances both economic efficiency and system stability. At the same time, due to the time-of-use electricity price, the energy storage equipment can also play a load transfer effect and improve the system’s economy. Finally, sensitivity analysis was conducted on the adjustment parameters of distributed power sources and loads that have uncertain values. A comparison was made between the deterministic scheduling model and the two-stage robust optimization model proposed in this study. It was proved that this model has great advantages in coordinating the economy, stability and low carbon level of microgrid operations.

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Section: Two-stage Robust Optimization Modelmentioning

confidence: 99%

A Two-Stage Robust Optimization Microgrid Model Considering Carbon Trading and Demand Response

Zhang,

Lan,

2023

Sustainability

View full text Add to dashboard Cite

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“…At present, there is a loss in the process of regional dispatching and transmission, which increases the demand for power generation and the transmission efficiency of the power grid needs to be improved. China plans to prioritize the dispatch of clean energy, increase the proportion of clean energy, and realize energy substitution and intelligence [ 23 ]. The smart grid is upgraded to displace the high energy consumption and reduce the energy consumption in the transmission process [ 24 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Influencing Factors and Realization Path of Power Decarbonization—Based on Panel Data Analysis of 30 Provinces in China from 2011 to 2019

Ren

Zhang

Fan

2022

IJERPH

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2011–2019 was the critical period of the low-carbon transformation of the power industry, reflecting the deepening influence of market mechanisms. Decarbonization of the new power system is a systematic project that needs to strengthen the top-level design and overall planning. Therefore, the paper first evaluates the decarbonization of the existing power system and controls the grid architecture, power structure, energy utilization, supply chain, and trading market to further optimize the system by strengthening the basic theoretical research of the new power system, exploring the key elements of the low-carbon development of the power system, promoting the breakthrough of the key subjects, and formulating the new power system decarbonization path. In the international push for carbon neutrality goals, identifying key factors in the decarbonization of the power system is critical to achieving low-carbon development in the power sector. Combined with the characteristics and development trends of the power industry, the five dimensions of “Power generation decarbonization (SP)”, “Energy utilization efficiency (EU)”, “Supply chain decarbonization (SC)”, and “Power grid decarbonization (PG)”, and “the Trading system (TS)” are selected to construct an evaluation index system for the power decarbonization and identify the key factors. The Analytic Network Process (ANP) Method is used to calculate the index weight and measure the decarbonization level of the power industry in 30 provinces in China from 2011 to 2019. The evaluation results reveal that the overall decarbonization level of the power industry is on the rise and has stabilized after peaking in 2016. The regression results of the systematic GMM estimation show that “the intensity of cross-regional transmission”, “the degree of carbon market participation”, “technology innovation”, and “policy support” can significantly promote power decarbonization, and different regions have heterogeneity. Therefore, we propose to achieve technological innovation and upgrading in the eastern region, strengthen the construction of smart grids in the central region, optimize the power structure in the western region, and improve the market mechanism as a whole, to form a low-carbon development path for the power industry.

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“…New swarm intelligence algorithms have been gradually developed and applied to microgrid economic dispatch models. Reference [ 21 ] proposed an economic dispatch model using the cuckoo algorithm to optimize multiple microgrids and determined the power supply strategy by predicting the best state of charge of the battery. This method has a significant improvement over PSO.…”

Section: Introductionmentioning

confidence: 99%

Research on Economic Optimal Dispatching of Microgrid Based on an Improved Bacteria Foraging Optimization

Zhou

2023

Biomimetics

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This paper proposes an improved Bacterial Foraging Optimization for economically optimal dispatching of the microgrid. Three optimized steps are presented to solve the slow convergence, poor precision, and low efficiency of traditional Bacterial Foraging Optimization. First, the self-adaptive step size equation in the chemotaxis process is present, and the particle swarm velocity equation is used to improve the convergence speed and precision of the algorithm. Second, the crisscross algorithm is used to enrich the replication population and improve the global search performance of the algorithm in the replication process. Finally, the dynamic probability and sine-cosine algorithm are used to solve the problem of easy loss of high-quality individuals in dispersal. Quantitative analysis and experiments demonstrated the superiority of the algorithm in the benchmark function. In addition, this study built a multi-objective microgrid dynamic economic dispatch model and dealt with the uncertainty of wind and solar using the Monte Carlo method in the model. Experiments show that this model can effectively reduce the operating cost of the microgrid, improve economic benefits, and reduce environmental pollution. The economic cost is reduced by 3.79% compared to the widely used PSO, and the economic cost is reduced by 5.23% compared to the traditional BFO.

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A data-driven approach for microgrid distributed generation planning under uncertainties

Cited by 28 publications

References 36 publications

A Two-Stage Robust Optimization Microgrid Model Considering Carbon Trading and Demand Response

A Two-Stage Robust Optimization Microgrid Model Considering Carbon Trading and Demand Response

Influencing Factors and Realization Path of Power Decarbonization—Based on Panel Data Analysis of 30 Provinces in China from 2011 to 2019

Research on Economic Optimal Dispatching of Microgrid Based on an Improved Bacteria Foraging Optimization

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