Stochastic planning of a multi-microgrid considering integration of renewable energy resources and real-time electricity market

Hakimi, Seyed Mehdi; Hasankhani, Arezoo; Shafie‐khah, Miadreza; Catalão, João P.S.

doi:10.1016/j.apenergy.2021.117215

Cited by 83 publications

(19 citation statements)

References 61 publications

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“…Meanwhile, for the stable and economic operation of MMG, a multi-microgrid energy management system is required to manage and coordinate dispatchable distributed generators, controllable loads, and energy trading among networked MGs. The operation objectives of MMG can be summarized as follows: 1) to minimize the overall operation cost of MMG in the grid-connected mode [17] and islanded mode [18]; 2) to maximize the distributed renewable energy penetration with the influence of uncertainties from various DREs, loads and electricity price [19][20][21]; 3) to minimize energy transmission loss from energy exchanges with the main-grid and among networked MGs [22]; 4) to maximize the economic goals of different subjects by designing multimicrogrids cluster architecture and its energy transaction mechanism [23]; 5) to minimize the communication delay between MMGs and improve the security and reliability of communication system [24].…”

Section: Figure1 the Global Microgrid Market Size (2021-2027)mentioning

confidence: 99%

“…With more and more power electronic devices (including distributed energy resources and loads) connected to multimicrogrid systems, the development of communication technology, the design and implementation of complex power control modules, the maturity of energy transaction market and the emergence of emerging technologies, The smart power grid industry will face new challenges. These challenges will not only affect the realization of multimicrogrid energy management, but will also have different characteristics in MMG research fields, such as, 1) massive distributed energy resources will provide a new possibilities for MMG planning and distributed operation control [20], [59]; 2) different energy characteristics and differences in time and space scales in the integrated energy system will significantly improve the MMG energy efficiency [138], [165][166]; 3) the development of information technology such as blockchain technology will make energy transactions more inclusive and convenient [167][168], etc. In summary, these technologies will bring some new development opportunities to different research fields such as the planning, operation, control, and energy transaction of MMG.…”

Section: Challenges and Future Directionsmentioning

confidence: 99%

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A Review on Optimal Energy Management of Multimicrogrid System Considering Uncertainties

Zhang

2022

IEEE Access

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Microgrid (MG) is one of the most effective solution to integrate distributed renewable energy into power system. However, modern MG has several technical challenges such as migration to multi vector energy system, increasing renewable energy penetration, and the uncertainties that arise from the large-scale incorporation of renewable energy. Recent development of multi-microgrid (MMG) could potentially mitigate these challenges. MMG has obvious advantages in improving the system stability, reliability, economy, and energy efficiency of power grid operation through autonomous management and coordinated control among networked MGs. In the meantime, uncertainties from many elements and operators in the MMG system also pose huge challenges in modeling. This paper will present and review typical architecture of MMG, including physical layer, information layer and application layer. Moreover, this paper will critically review and analyze challenges in uncertainty modelling and solution in MMGs. Finally, the paper will also discuss future research areas and development trends of MMG.

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Section: Figure1 the Global Microgrid Market Size (2021-2027)mentioning

confidence: 99%

Section: Challenges and Future Directionsmentioning

confidence: 99%

A Review on Optimal Energy Management of Multimicrogrid System Considering Uncertainties

Zhang

2022

IEEE Access

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“…Technical specifications and statistical parameters for the wind speed are used to generate the state matrix of the WT [73,74]. Different probability distributions have been reported for the statistical modelling of wind speed and WTs [75,76]. The Weibull distribution is one of the most popular ones.…”

Section: Headermentioning

confidence: 99%

Analytical reliability evaluation method of smart micro‐grids considering the cyber failures and information transmission system faults

Aslani

Hashemi‐Dezaki

Ketabi

2022

IET Renewable Power Gen

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The reliability of smart micro‐grids (SMGs), as a cyber‐physical system (CPS), might be influenced by cyber failures and information transmission faults. Several Monte Carlo simulation (MCS)‐based approaches have been reported to assess the reliability of SMGs and smart grids. On the other hand, analytical reliability assessment methods have been presented in some research works, while the cyber system has not been concerned. However, the literature shows a research gap in developing an accurate and fast reliability evaluation method for SMGs based on the unavailability of cyber elements and information transmission faults. This article tries to fill the discussed gap by adding the analytical modelling of cyber‐physical interdependencies and information transmission faults to available analytical methods, focusing on physical uncertainties. Comparing the proposed model with existing MCS‐based and analytical reliability evaluation methods illustrates the advantages of this research. Test results show that less than 5.7% expected energy not supplied (EENS) error occurs by the proposed method, which would be much faster than MCS‐based ones. Moreover, the sensitivity analyses highlight the impacts of the cyber network topologies on the cyber‐physical interdependencies.

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“…search agents in the feasible space, and the particles' position represents valid solutions to the problem. Particles move to new positions to discover better positions by tracking optimal ones [42]. In the beginning, particles are scattered randomly in the feasible region.…”

Section: Arc Voltage Arc Currentmentioning

confidence: 99%

Optimal Electric Arc Furnace Model’s Characteristics Using Genetic Algorithm and Particle Swarm Optimization and Comparison of Various Optimal Characteristics in DIgSILENT and EMTP-RV

Nooshabadi

Sadeghi

Hashemi‐Dezaki

2022

International Transactions on Electrical Energy Systems

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The stochastic and nonlinear characteristics of electric arc furnaces (EAFs) lead to power quality challenges in the power system. In studying EAF behaviors, having optimized characteristics/models, selecting a suitable and optimum model that adapts to the actual characteristics of EAFs, and investigating simulation software’s capability for implementing EAF models are essential. However, the literature shows a research gap in investigating EAF simulations in various software products based on different models. This paper studies several time-domain models, such as piece-wise linear, modified piece-wise linear, hyperbolic, exponential, and exponential-hyperbolic models, for EAF modeling and simulation. The optimal estimation of parameters for the introduced models is necessary to adapt actual EAF characteristics. Thus, one of the studies taken in this paper is optimizing the EAF model’s characteristics. The proposed optimization problem is solved using the genetic algorithm (GA) and particle swarm optimization (PSO). Moreover, the optimized models are simulated in DIgSILENT and EMTP-RV to investigate different EAF models from the viewpoint of accuracy and efficiency. The optimization of different EAF models’ characteristics and comparison of EMTP-RV and DIgSILENT in simulating EAF behavior are the contributions of this paper. The proposed method is validated based on the actual data of a realistic EAF-based steel company in Iran. The obtained results show that the modified piece-wise linear model has the most accuracy in identifying the EAF behavior. The test results based on DIgSILENT and EMTP-RV simulations imply that the EAF could be simulated with high accuracy using modified piece-wise linear and piece-wise linear models. In general, EMTP-RV has expressed more accuracy in simulating different EAF models, and the simulation execution speed of EMTP-RV is around 2.5 times faster than DIgSILENT. In contrast, DIgSILENT is more suitable to facilitate the power system studies of EAF according to its extensive study tools and library.

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Stochastic planning of a multi-microgrid considering integration of renewable energy resources and real-time electricity market

Cited by 83 publications

References 61 publications

A Review on Optimal Energy Management of Multimicrogrid System Considering Uncertainties

A Review on Optimal Energy Management of Multimicrogrid System Considering Uncertainties

Analytical reliability evaluation method of smart micro‐grids considering the cyber failures and information transmission system faults

Optimal Electric Arc Furnace Model’s Characteristics Using Genetic Algorithm and Particle Swarm Optimization and Comparison of Various Optimal Characteristics in DIgSILENT and EMTP-RV

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