Intelligent energy management in hybrid microgrids considering tidal, wind, solar and battery

Esapour, Khodakhast; Abbasian, Mohammadali; Saghafi, Hadi

doi:10.1016/j.ijepes.2020.106615

Cited by 27 publications

(6 citation statements)

References 19 publications

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“…Ocean energy was presented more in detail in the previous works to provide energy for different zones as in [53][54][55][56][57]. Almost all of these studies have introduced modeling and multi-objective optimization for hybrid energy systems under various constraints, using diverse optimization approaches to solve the intended issues.…”

Section: Ocean Energymentioning

confidence: 99%

Overview: Using Hybrid Energy System for Electricity Production Based on the Optimization Methods

Saib,

Bayındır,

Vadi

2024

Gazi University Journal of Science

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Renewable energy systems are mostly used in the world due to their inexhaustible and non-polluting production. As a result of a large utilization of these energy sources in different areas, the electricity production rate is increasing every day. Previous studies clarified uses, modeling, configuration, energy management operation, and optimization objectives based on different energy sources. For this reason, this paper focuses on an overview of multi energy systems as renewable and conventional power sources with the integration of an energy storage system coupled to the on-off electrical network. Furthermore, a survey is done regarding global energy production, configuration energy systems, energy storage systems, power management strategies, and optimization methods based on different hybrid energy systems. Multiple optimization approaches have been implemented to reach the global best solution for the hybrid power systems. To ensure the best optimization result, it is preferable to take hybrid optimization methods into consideration. These methods have been invented recently and have proved their efficacy and performance mainly in power systems.

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Section: Ocean Energymentioning

confidence: 99%

Overview: Using Hybrid Energy System for Electricity Production Based on the Optimization Methods

Saib,

Bayındır,

Vadi

2024

Gazi University Journal of Science

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“…An energy management model based on mixed-integer linear programming (MILP) is developed in [41] to optimize the operation of smart buildings for peak shaving. In [42], a novel optimization method known as bat algorithm to tackle the energy management problem of a microgrid in islanded mode. The paper [43] implements a multi-objective cuckoo search algorithm to evaluate the effects of utilizing BES on optimal performance of power system.…”

Section: Energy Optimization Microgrid Centric Techniques For Islande...mentioning

confidence: 99%

Real-Time Scheduling for Optimal Energy Optimization in Smart Grid Integrated With Renewable Energy Sources

et al. 2022

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Load scheduling, battery energy storage control, and improving user comfort are critical energy optimization problems in smart grid. However, system inputs like renewable energy generation process, conventional grid generation process, battery charging/discharging process, dynamic price signals, and load arrival process comprise controller performance to accurately optimize real-time battery energy storage scheduling, load scheduling, energy generation, and user comfort. Thus, in this work, the virtual queue stability based Lyapunov optimization technique (LOT) is adopted to investigate real-time energy optimization in a grid-connected sustainable smart home with a heating, ventilation, and air conditioning (HVAC) load considering unknown system inputs dynamics. The main goal is to minimize overall time average energy cost and thermal discomfort cost in a long time horizon for sustainable smart home accounting for changes in home occupancy state, the most comfortable temperature setting, electrical consumption, renewable generation output, outdoor temperature, and the electricity costs. The employed algorithm creates and regulates four queues for indoor temperature, electric vehicle (EV) charging, and energy storage system (ESS). Extensive simulations are conducted to validate the employed algorithm. Simulation results illustrate that the proposed algorithm performs real-time energy optimization and reduces the time average energy cost of 20.15% while meeting the user's energy and comfort requirement. INDEX TERMSReal-time, optimization, convex optimization, dynamic pricing, renewable energy generation, scheduling, energy storage, user comfort. NOMENCLATURE Abbreviations Explanation AI Artificial intelligence. ACO Ant colony optimization. ABC Artificial bee colony. AEP Annual energy production. BES Battery energy storage. DR Demand response.

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“…They consider four different scenarios for sizing and feasibility study of the system. Esapour et al 29 hybrid model is developed by integrating a solar energy system, a wind energy system, tidal energy, and a battery bank. They considered the entire installation cost and used a genetic algorithm to minimize the entire energy cost.…”

Section: Literature Reviewmentioning

confidence: 99%

Planning and optimization of standalone microgrid with renewable resources and energy storage

2022

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Renewable energy has shown to be a feasible and cost‐effective approach to electrifying rural villages while also meeting the region's long‐term development goals. Due to the intermittent and unpredictable nature of renewable energy supply and the need to satisfy variable demand across time, capacity planning for a sustainable energy system is problematic. Because the energy planning problem is non‐linear and non‐convex, an efficient technique must be used to build a cost‐effective energy system that supplies reliable electricity to the area. In the present work, a rural microgrid is suggested for the isolated community of the Indian hilly region. The integrated model combines existing energy resources in the area. The microgrid consists of the solar photovoltaic system, micro‐hydropower, wind energy biomass, and storage foreconomical and reliable electrification. The modeling of microgrids is based on the availability of renewable resources. Using the Differential Evolution optimization algorithm, the recommended hybrid energy model examined the per‐unit cost of energy and the overall operating cost. Based on the simulation for a year, it has been found that the optimal system has 35 kWof biomass, 30 kW of biogas, 40 kW of MHP, 144 kW of SPV, and 42 kW of the wind energy system to satisfy the energy demand of the area entirely. The per‐unit cost of energy is 0.12$/kWh, and the total operating cost is $ $2 120 700, respectively. Further, the sensitivity analysis is performed to know the impact of change in parameters on energy cost. The suggested microgrid provides a cost‐effective solution to the community.

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Intelligent energy management in hybrid microgrids considering tidal, wind, solar and battery

Cited by 27 publications

References 19 publications

Overview: Using Hybrid Energy System for Electricity Production Based on the Optimization Methods

Overview: Using Hybrid Energy System for Electricity Production Based on the Optimization Methods

Real-Time Scheduling for Optimal Energy Optimization in Smart Grid Integrated With Renewable Energy Sources

Planning and optimization of standalone microgrid with renewable resources and energy storage

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