Optimal scheduling of a renewable based microgrid considering photovoltaic system and battery energy storage under uncertainty

Luo, Liang; Abdulkareem, Sarkew S.; Rezvani, Alireza; Miveh, Mohammad Reza; Samad, Sarminah; Aljojo, Nahla; Pazhoohesh, Mehdi

doi:10.1016/j.est.2020.101306

Cited by 229 publications

(80 citation statements)

References 30 publications

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“…This work differs from other related surveys in the literature, such as, [22][23][24][25][26][27][28][29][30][31][32][33][34] in being the first meta-analytic review on efficient SG energy management. From the existing literature, it is also conclude that mostly meta-heuristic techniques are used for optimization because of their ability to deal with large and complex scenarios with less execution time.…”

Section: Motivation For the Research Workmentioning

confidence: 91%

A hybrid RFCRO approach for the energy management of the grid connected microgrid system

Roy

Mandal

2020

Int Trans Electr Energ Syst

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Energy management of the grid connected microgrid (MG) systems with low cost using a novel hybrid algorithm is implemented in this paper. The novel proposed hybrid technique is the combined performance of both the Random Forest (RF) and Coral Reefs Optimization (CRO) algorithm and in this way it is named as RFCRO. Optimum operation of micro-sources for decreasing the electricity production cost by hourly day-ahead and real-time scheduling is the main objective of the paper. The proposed hybrid technique is to manage the power flows between the energy sources and the grid. To achieve this point, demand response and minimum cost of energy are determined. This technique is involved with the mathematical optimization problems that necessitate more than one fitness function to be optimized simultaneously. By using the inputs of MG-like wind turbine, photovoltaic array, battery, and fuel cell with corresponding cost functions, the RF is employed to predict the load demand. CRO clarifies the squirrel in optimizing the configuration of MG based on the load demand. The proposed hybrid technique is implemented in MATLAB/ Simulink working platform and compared with other solution techniques like

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Section: Motivation For the Research Workmentioning

confidence: 91%

A hybrid RFCRO approach for the energy management of the grid connected microgrid system

Roy

Mandal

2020

Int Trans Electr Energ Syst

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“…where M is a sufficiently large positive number. The transformed single-layer optimization model is still non-linear, mainly due to the product of energy price and power in (19). In the lower layer, the user optimization model is a linear model.…”

Section: Linear Transformation Of the Master-slave Game Modelmentioning

confidence: 99%

“…In Reference 18, a double‐layer energy management system for the microgrid group was built, the impact due to the uncertainty of renewable energy was reduced by the joint scheduling of the internal microgrids. In Reference 19, the nonsequential Monte Carlo method was used to simulate the output of renewable energy, on this basis, the power system failure caused by the uncertainty of renewable energy output was studied. In Reference 20, the paper combines stochastic programming with traditional robust optimization, and proposes a two‐stage distributed robust optimization model to reduce the impact of wind power uncertainty on the optimal dispatch of integrated electricity and gas energy.…”

Section: Introductionmentioning

confidence: 99%

Master‐slave game optimization method of smart energy systems considering the uncertainty of renewable energy

2020

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As the uncertainty of renewable energy output brings more and more risks to the day-ahead dispatch of the power grid, an optimization scheduling strategy of a smart energy system based on improved master-slave game model is proposed. Risk factors related to the uncertainties of renewable energy are introduced into the master-slave game model. Taking the smart energy system as the leader and the end users as the follower, an optimized operation model of the smart energy system based on the improved master-slave game model is established, which is transformed into a single-layer linear programming model according to the Karush-Kuhn-Tucher conditions and the duality theorem. The benefits of the system and electric vehicle users in four application scenarios are obtained by the YALMIP algorithm and the sensitivity affecting the economics of the smart energy system is analyzed. The validity of the model is verified by a simulation analysis of actual operation data from the smart energy system in China. The simulation results show that the method proposed in this paper can increase the revenue of the smart energy system by 7%, reduce the risk cost and charging cost of electric vehicle users by 63.92% and 48.34%.

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“…Among the various existing ESS, battery ESSs have been widely employed with RESs in wide range of electrical power installations. However, the short operating lifetime and increased replacement costs represent the main critical issues for battery ESSs [11], [12]. Another alternative is through converting the excess electrical power from the RES into hydrogen via employing electrolyzers.…”

Section: Introductionmentioning

confidence: 99%

A Differential Evolution-Based Optimized Fuzzy Logic MPPT Method for Enhancing the Maximum Power Extraction of Proton Exchange Membrane Fuel Cells

Aly

Rezk

2020

IEEE Access

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Recently, fuel cells (FCs) have found vast employment in several applications. However, unique maximum power point tracking (MPPT) exists for each set of operating condition for the efficient operation of FCs. Therefore, this paper presents a differential evolution optimization algorithm (DEOA)based optimized fuzzy-logic (OFLC) MPPT method for enhancing the maximum power extraction of FCs. The various settings for the membership functions (MFs) of the input and output variables are optimized in the proposed method. Thence, more degree-of-freedom can be employed for accurate and fast tracking of the optimal power point of the proton exchange membrane FCs (PEMFCs). Whereas, existing MPPT methods in the literature for FC applications suffer from decreased degree-of-freedom for optimizing their performance, and lack of adaptivity, which obstructs their suitability for the wide operating range of FCs. The superiority and performance effectiveness of the proposed OFLC MPPT method have been validated and compared with the most prevalent techniques in the literature. Moreover, the robustness and sensitivity of the proposed OFLC MPPT method have been tested at various step changes in the water content of membrane and various temperature changes. Moreover, the proposed design of the suggested OFLC MPPT is general and it can be implemented on low-cost microcontrollers. The results verify the superior performance of the proposed OFLC MPPT method from the accurate and fast MPPT extraction, smooth output power with low ripple, and simplicity of the design point of views. INDEX TERMS Differential Evolution Optimization Algorithm (DEOA), fuel cell (FC), fuzzy logic control (FLC), maximum power point tracking.

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Optimal scheduling of a renewable based microgrid considering photovoltaic system and battery energy storage under uncertainty

Cited by 229 publications

References 30 publications

A hybrid RFCRO approach for the energy management of the grid connected microgrid system

A hybrid RFCRO approach for the energy management of the grid connected microgrid system

Master‐slave game optimization method of smart energy systems considering the uncertainty of renewable energy

A Differential Evolution-Based Optimized Fuzzy Logic MPPT Method for Enhancing the Maximum Power Extraction of Proton Exchange Membrane Fuel Cells

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