Integrated grid, coal-fired power generation retirement and GESS planning towards a low-carbon economy

Yang, Yi; Qiu, Jing; Ma, Jin; Zhang, Chenxi

doi:10.1016/j.ijepes.2020.106409

Cited by 26 publications

(6 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [11] the authors propose a methodology to find near-optimal alternatives for the planning of a renewable-dominated power system considering the expansion of existing transmission system capacity, and new capacity of solar photovoltaic, wind and combined cycle gas units, as well as battery-based and H 2 -based storage. The installation of H 2 -fired gas turbines is considered in [12], where the authors present a methodology for the planning of power systems aimed to the design of roadmaps for system operators in the de-carbonization transition. The proposed methodology considers the installation of new transmission lines, new photovoltaic generation and gas energy storage systems, as well as the retirement of traditional coal-fired power plants.…”

Section: Introductionmentioning

confidence: 99%

Generation Capacity Expansion Considering Hydrogen Power Plants and Energy Storage Systems

et al. 2023

View full text Add to dashboard Cite

The design of decarbonized power systems is one of the most relevant and challenging problems that power system planners are facing nowadays. In this sense, the replacement of natural gas turbines by H 2 -fired gas turbines in future power systems may constitute a solution to reduce greenhouse gas emissions maintaining the dispatchability of the system. This work develops a novel generation capacity expansion formulation that considers the possibility of installing new H 2 -fired gas turbines, as well as renewable generation and different storage technologies. The proposed model also determines the investment decisions related to the installation of electrolyzers to produce H 2 , as well as H 2 storage facilities. The provision of reserve capacity by generating units, storage and electrolyzers is also considered to determine the optimal investment decisions. The uncertainty related to the demand growth and the capital costs of electrolyzers and H 2 storage is explicitly considered by using a stochastic programming formulation. A realistic case study based on an actual isolated power system is solved to test the proposed formulation. The obtained results indicate that H 2 power plants are installed in all cases in which this technology is available. Additionally, the capacity installed of electrolyzers is over 2.5 times higher than that of H 2 power units.INDEX TERMS batteries, hydrogen turbines, electrolyzers, hydrogen tanks, pumped storage hydropower, renewable generation, stochastic programming I. NOTATION

show abstract

Section: Introductionmentioning

confidence: 99%

Generation Capacity Expansion Considering Hydrogen Power Plants and Energy Storage Systems

et al. 2023

View full text Add to dashboard Cite

show abstract

“…The implementation of microgrids has made it possible to make full use of electrical energy and to diversify the use of electrical energy. The large-scale construction of microgrids is now a key development project in all regions [1]. Based on the increasing depletion of energy on Earth, hierarchical and zoning planning for microgrid energy storage and the construction of high-quality microgrids have become a hot research topic in practicing the concept of sustainable development.…”

Section: Introductionmentioning

confidence: 99%

Optimal planning algorithm for hierarchical zoning of microgrids under cooperative dispatch of multiple energy storage devices

Zhang,

Zhou,

Han

et al. 2023

Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023)

View full text Add to dashboard Cite

The synergy with energy storage devices in the current microgrid hierarchical zoning optimization planning is low, resulting in poor quality optimization planning results. To this end, a microgrid hierarchical zoning optimisation planning algorithm with collaborative scheduling of multiple energy storage devices is proposed. Analysis of weak levels and regions. Distributed arrangement of energy storage devices in the microgrid. Dynamic control of energy storage device parameters and hierarchical partitioning of multiple energy storage devices for collaborative scheduling. Generation of a microgrid hierarchical partitioned optimal planning algorithm. The experiments show that the average index entropy value of the algorithm is 0.4857, which can effectively improve the quality of the microgrid hierarchical zoning optimization planning results and has high practical value.

show abstract

“…In the realm of power system planning, significant attention has been directed toward the transition to decarbonized systems and the optimization of integrated system coupling. The authors of [20] introduced the concept of optimizing emission reduction per unit cost, effectively balancing the tradeoff between cost and emission reduction in the planning process. Meanwhile, the authors of [21] proposed a method for collaborative planning of the electricity system and electric vehicle transportation network, aiming to enhance system flexibility.…”

Section: Introductionmentioning

confidence: 99%

Interpretable Hybrid Experiment Learning-Based Simulation Analysis of Power System Planning under the Spot Market Environment

et al. 2023

Self Cite

View full text Add to dashboard Cite

The electricity spot market plays a significant role in promoting the self-improvement of the overall resource utilization efficiency of the power system and advancing energy conservation and emission reduction. This paper analyzes and compares the potential impacts of spot market operations on system planning, considering the differences between planning methods in traditional and spot market environments through theoretical analysis and model comparison. Furthermore, we conduct research and analysis on grid planning methods under the spot market environment with the goal of maximizing social benefits. Unlike the pricing approach based on historical price data in traditional market simulation processes, a data-driven approach that combines experimental economics and machine learning is proposed, specifically using mixed empirical learning to simulate unit bidding strategies in market transactions. A simulation model for electricity spot market trading is constructed to analyze the performance of the planning results in the spot market environment. The case study results indicate that the proposed planning methods can enable the grid to operate well in the spot market environment, maintain relatively stable nodal prices, and ensure the integration of a high proportion of clean energy.

show abstract

Integrated grid, coal-fired power generation retirement and GESS planning towards a low-carbon economy

Cited by 26 publications

References 27 publications

Generation Capacity Expansion Considering Hydrogen Power Plants and Energy Storage Systems

Generation Capacity Expansion Considering Hydrogen Power Plants and Energy Storage Systems

Optimal planning algorithm for hierarchical zoning of microgrids under cooperative dispatch of multiple energy storage devices

Interpretable Hybrid Experiment Learning-Based Simulation Analysis of Power System Planning under the Spot Market Environment

Contact Info

Product

Resources

About