Economic Integration of Renewable Energy Sources for Optimal Operation of Smart Grid

Electrical grid is no longer featured in a conventional way nowadays. Today, the growing of new technologies, primarily the distributed renewable energy sources and electric vehicles, has been integrated with the distribution networks causing several technical issues. As a result, the penetration of the renewable energy sources can be limited by the utility companies. Smart grid has been emerged as one of the solutions to the technical issues, hence allowing the usage of renewable and improving the energy efficiency of the electrical grid. The challenge is to develop an intelligent management system to maintain the balance between the generation and demand. This task can be performed by using energy storage system. As part of the smart grid, the deployment of energy storage system plays a critical role in stabilizing the voltage and frequency of the networks with renewable energy sources and electric vehicles. This book chapter illustrates the revolution and the roles of energy storage for improving the network performance.

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Integrated Optimization Design of Combined Cooling, Heating, and Power System Coupled with Solar and Biomass Energy

Energies ◽

10.3390/en12040687 ◽

2019 ◽

Vol 12 (4) ◽

pp. 687 ◽

Cited By ~ 8

Author(s):

Lizhi Zhang ◽

Fan Li ◽

Bo Sun ◽

Chenghui Zhang

Keyword(s):

Renewable Energy ◽

Solar Energy ◽

Optimization Design ◽

Design Method ◽

Renewable Energy Sources ◽

Optimal Operation ◽

Biomass Energy ◽

System Structure ◽

Energy Sources ◽

Combined Cooling

The combined cooling, heating, and power (CCHP) systems coupled with solar energy and biomass energy can meet the needs of island or rural decentralized and small-scale integrated energy use, which have become increasingly popular in recent years. This study presents a renewable energy sources integrated combined cooling, heating, and power (RES-CCHP) system, driven by a biogas fueled internal combustion engine (ICE) and photovoltaic (PV) panels, which is different from the traditional natural gas CCHP system. Owing to the solar energy volatility and the constraint of biomass gas production, the traditional optimization design method is no longer applicable. To improve the energetic, economic and environmental performances of the system, an integrated design method with renewable energy capacity, power equipment capacity and key operating parameters as optimization variables is proposed. In addition, a case study of a small farm in Jinan, China, is conducted to verify the feasibility of the proposed RES–CCHP system structure and the corresponding optimal operation strategy. The results illustrate that the implementation of the optimal design is energy-efficient, economical and environmentally-friendly. The values of primary energy saving ratio, annual total cost saving rate and carbon emission reduction ratio are 20.94%, 11.73% and 40.79%, respectively. Finally, the influence of the volatility of renewable energy sources on the optimization method is analyzed, which shows that the RES–CCHP system and the method proposed are robust.

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Optimum utilization of grid connected hybrid renewable energy sources using hybrid algorithm

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331220913740 ◽

2020 ◽

pp. 014233122091374

Author(s):

M. Suresh ◽

R. Meenakumari

Keyword(s):

Renewable Energy ◽

Tabu Search ◽

Smart Grid ◽

Optimization Algorithm ◽

Renewable Energy Sources ◽

Whale Optimization Algorithm ◽

Computational Time ◽

Energy Sources ◽

Whale Optimization ◽

Hybrid Renewable Energy

An optimal utilization of smart grid connected hybrid renewable energy sources is proposed in this paper. The hybrid technique is the combination of recurrent neural network and adaptive whale optimization algorithm plus tabu search, called AWOTS. The main objective is the RES optimum operation for decreasing the electricity production cost by hourly day-ahead and real time scheduling. Here, the load demands are predicted using AWOTS to develop the correct control signals based on power difference between source and load side. Adaptive whale optimization algorithm searching behaviour is adjusted by tabu search. The proposed technique is executed in the MATLAB/Simulink working platform. To test the performance of the proposed method, the load demand for the 24-hour time period is demonstrated. By then the power generated in the sources, such as photovoltaic, wind turbine, micro turbine and battery by the proposed technique, is analyzed and compared with existing techniques, such as genetic algorithm, particle swarm optimization and whale optimization algorithm. Furthermore, the state of charge of the battery for the 24-hour period is compared with existing techniques. Likewise, the cost of the system is compared and error in the sources also compared. The comparison results affirm that the proposed technique has less computational time (35.001703) than the existing techniques. Moreover, the proposed method is cost-effective power production of smart grid and effective utilization of renewable energy sources without wasting the available energy.

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