scholarly journals A Multi-objective Scheduling Optimization Model for Hybrid Energy System Connected with Wind-Photovoltaic-Conventional Gas Turbines, CHP Considering Heating Storage Mechanism

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 425 ◽  
Author(s):  
Yao Wang ◽  
Yan Lu ◽  
Liwei Ju ◽  
Ting Wang ◽  
Qingkun Tan ◽  
...  
Keyword(s):  
Demand Response ◽  
Gas Turbines ◽  
Energy System ◽  
Objective Functions ◽  
Distributed Energy ◽  
Operating Income ◽  
Hybrid Energy ◽  
Multi Objective ◽  
Load Demand ◽  
Load Fluctuation

In order to meet the user’s electricity demand and make full use of distributed energy, a hybrid energy system (HES) was proposed and designed, including wind turbines (WTs), photovoltaic (PV) power generation, conventional gas turbines (CGTs), incentive-based demand response (IBDR), combined heat and power (CHP) and regenerative electric (RE) boilers. Then, the collaborative operation problem of HES is discussed. First, the paper describes the HES’ basic structure and presents the output model of power sources and heating sources. Next, the maximum operating income and minimum load fluctuation are taken as the objective function, and a multi-objective model of HES scheduling is proposed. Then an algorithm for solving the model is proposed that comprises two steps: processing the objective functions and constraints into linear equations and determining the optimal weight of the objective functions. The selected simulation system is a microgrid located on an eastern island of China to comparatively analyze the influence of RE-heating storage (RE-HS) and price-based demand response (PBDR) on HES operation in relation to four cases. By analyzing the results, the following three conclusions are drawn: (1) HES can comprehensively utilize a variety of distributed energy sources to meet load demand. In particular, RE technology can convert the abandoned energy of WT and PV into heat during the valley load time, to meet the load demand combined with CHP; (2) The proposed multi-objective scheduling model of HES operation not only considers the maximum operating income but also considers the minimum load fluctuation, thus achieving the optimal balancing operation; (3) RE-HS and PBDR have a synergistic optimization effect, and when RE-HS and PBDR are both applied, an HES can achieve optimal operation results. Overall, the proposed decision method is highly effective and applicable, and decision makers could utilize this method to design an optimal HES operation strategy according to their own actual conditions.

scholarly journals USING PARTICLE SWARM OPTIMAZATION TO FIND OPTIMAL SIZING OF PV-BS AND DIESEL GENERATOR

2021 ◽  
Vol 25 (3) ◽  
pp. 51-59
Author(s):  
Abbas Q. Mohammed ◽  
◽  
Kassim A. Al-Anbarri ◽  
Rafid M. Hannun ◽  
◽  
...  
Keyword(s):  
Particle Swarm ◽  
Energy System ◽  
Total System ◽  
Diesel Generator ◽  
Optimal Sizing ◽  
Hybrid Energy ◽  
Multi Objective ◽  
Load Demand ◽  
Cost Of Energy ◽  
Southern Iraq

This paper explores the sizing optimization of stand -alone hybrid energy system (HES) in southern Iraq (Thi Qar province) for supply stand-alone households by the electricity. HES consist of three components (solar cell (PV), diesel generator (DG) and battery storage (BS)). Particle swarm optimization (PSO) used in this study for find optimal sizing of the HES to minimizing multi-objective, first objective is to minimizing the total system cost (TSC) that lead to minimizing cost of energy (COE). Second objective is to minimizing total emission CO2 (TECO2). The constraint of the optimization is the reliability (100 %) mean continuous provide the load demand by the electricity. The results of the optimization show the ability the algorithm to minimizing the multi-objective with continuous supply the load by the electricity through life cycle of the project (25) years.

scholarly journals Optimal Sizing of an Island Hybrid Microgrid Based on Improved Multi-Objective Grey Wolf Optimizer

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1581
Author(s):  
Wenqiang Zhu ◽  
Jiang Guo ◽  
Guo Zhao ◽  
Bing Zeng
Keyword(s):  
Power Supply ◽  
Tidal Current ◽  
System Optimization ◽  
Energy System ◽  
Energy Sources ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Hybrid Energy System ◽  
Hybrid Energy ◽  
Multi Objective

The hybrid renewable energy system is a promising and significant technology for clean and sustainable island power supply. Among the abundant ocean energy sources, tidal current energy appears to be very valuable due to its excellent predictability and stability, particularly compared with the intermittent wind and solar energy. In this paper, an island hybrid energy microgrid composed of photovoltaic, wind, tidal current, battery and diesel is constructed according to the actual energy sources. A sizing optimization method based on improved multi-objective grey wolf optimizer (IMOGWO) is presented to optimize the hybrid energy system. The proposed method is applied to determine the optimal system size, which is a multi-objective problem including the minimization of annualized cost of system (CACS) and deficiency of power supply probability (DPSP). MATLAB software is utilized to program and simulate the hybrid energy system. Optimization results confirm that IMOGWO is feasible to optimally size the system, and the energy management strategy effectively matches the requirements of system operation. Furthermore, comparison of hybrid systems with and without tidal current turbines is undertaken to confirm that the utilization of tidal current turbines can contribute to enhancing system reliability and reducing system investment, especially in areas with abundant tidal energy sources.

scholarly journals A Novel Demand Response Strategy for Sizing of Hybrid Energy System With Smart Grid Concepts

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 20277-20294
Author(s):  
Ali M. Eltamaly ◽  
Majed A. Alotaibi ◽  
Abdulrahman I. Alolah ◽  
Mohamed A. Ahmed
Keyword(s):  
Smart Grid ◽  
Demand Response ◽  
Energy System ◽  
Response Strategy ◽  
Hybrid Energy System ◽  
Hybrid Energy

scholarly journals A Multiobjective Scheduling Optimization Model for Multienergy Complementary System Integrated by Wind-Photovoltaic-Convention Gas Turbines considering Demand Response

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Zhang Lihui ◽  
Xin He ◽  
Ju Liwei
Keyword(s):  
Demand Response ◽  
Optimization Model ◽  
Gas Turbines ◽  
Risk Level ◽  
Objective Functions ◽  
Entropy Weight ◽  
Scheduling Optimization ◽  
Power Sources ◽  
Complementary System ◽  
Scheduling Model

To utilize the complementary feature of different power sources, wind power plant (WPP), and solar photovoltaic power (PV), convention gas turbines (CGT) and incentive-based demand response (IBDR) are integrated into a multienergy complementary system (MECS) with the implementation of price-based demand response (PBDR). Firstly, the power output model of WPP, PV, and CGT is constructed and the mathematical model of DR is presented. Then, a multiobjective scheduling model is proposed for MECS operation under the objective functions of the maximum economic benefit, the minimum abandoned energy, and the minimum risk level. Thirdly, the payoff table of objective functions is put forward for converting the multiobjective model into a single objective model by using entropy weight method to calculate weighting coefficients of different objective functions. Finally, the improved IEEE 30 bus system is taken as the simulation system with four simulation scenarios for comparatively analyzing the influence of PBDR and IBDR on MECS operation. The simulation results show the following: (1) The MECS fully utilized the complementarity of different power sources; CGT and IBDR can provide peaking service for WPP and PV to optimize overall system operation. (2) The proposed algorithm can solve the MECS multiobjective scheduling optimization model, and the system scheduling results in the comprehensive optimal mode can take into account different appeal. And the total revenue, abandoned energy capacity, and load fluctuation are, respectively, 108009.30¥, 11.62 MW h, and 9.74 MW. (3) PBDR and IBDR have significant synergistic optimization effects, which can promote the grid connection of WPP and PV. When they are both introduced, the peak-to-valley ratio of the load curve is 1.19, and the abandoned energy is 5.85 MW h. Therefore, the proposed MECS scheduling model and solution algorithm could provide the decision basis for decision makers based on their actual situation.

scholarly journals Modeling, Control and Power Management Strategy of a Grid connected Hybrid Energy System

2018 ◽  
Vol 8 (3) ◽  
pp. 1345 ◽  
Author(s):  
Sujit Kumar Bhuyan ◽  
Prakash Kumar Hota ◽  
Bhagabat Panda
Keyword(s):  
Fuel Cell ◽  
Power Management ◽  
Storage Tank ◽  
Power Flow ◽  
Management Strategies ◽  
Energy System ◽  
Pv System ◽  
Hybrid Energy System ◽  
Hybrid Energy ◽  
Load Demand

This paper presents the detailed modeling of various components of a grid connected hybrid energy system (HES) consisting of a photovoltaic (PV) system, a solid oxide fuel cell (SOFC), an electrolyzer and a hydrogen storage tank with a power flow controller. Also, a valve controlled by the proposed controller decides how much amount of fuel is consumed by fuel cell according to the load demand. In this paper fuel cell is used instead of battery bank because fuel cell is free from pollution. The control and power management strategies are also developed. When the PV power is sufficient then it can fulfill the load demand as well as feeds the extra power to the electrolyzer. By using the electrolyzer, the hydrogen is generated from the water and stored in storage tank and this hydrogen act as a fuel to SOFC. If the availability of the power from the PV system cannot fulfill the load demand, then the fuel cell fulfills the required load demand. The SOFC takes required amount of hydrogen as fuel, which is controlled by the PID controller through a valve. Effectiveness of this technology is verified by the help of computer simulations in MATLAB/SIMULINK environment under various loading conditions and promising results are obtained.

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