Energy management system for hybrid PV-wind-battery microgrid using convex programming, model predictive and rolling horizon predictive control with experimental validation

Elkazaz, Mahmoud; Sumner, Mark; Thomas, David William

doi:10.1016/j.ijepes.2019.105483

Cited by 129 publications

(42 citation statements)

References 49 publications

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“…The daily household energy costs "C Home " (2) that need to be minimized are comprised of payments ( 3) (e.g., for electricity purchased from the supply utility), and incomes (4) (e.g., for the energy exported to the supply utility) [31]. The constraints are divided into: (a) the equality constraint function (5), and (b) the inequality constraint functions ( 9)-( 11).…”

Section: Formulation Of the Optimization Problem And Constraintsmentioning

confidence: 99%

Performance Assessment of an Energy Management System for a Home Microgrid with PV Generation

et al. 2020

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Home energy management systems (HEMS) are a key technology for managing future electricity distribution systems as they can shift household electricity usage away from peak consumption times and can reduce the amount of local generation penetrating into the wider distribution system. In doing this they can also provide significant cost savings to domestic electricity users. This paper studies a HEMS which minimizes the daily energy costs, reduces energy lost to the utility, and improves photovoltaic (PV) self-consumption by controlling a home battery storage system (HBSS). The study assesses factors such as the overnight charging level, forecasting uncertainty, control sample time and tariff policy. Two management strategies have been used to control the HBSS; (1) a HEMS based on a real-time controller (RTC) and (2) a HEMS based on a model predictive controller (MPC). Several methods have been developed for home demand energy forecasting and PV generation forecasting and their impact on the HEMS is assessed. The influence of changing the battery’s capacity and the PV system size on the energy costs and the lost energy are also evaluated. A significant reduction in energy costs and energy lost to the utility can be achieved by combining a suitable overnight charging level, an appropriate sample time, and an accurate forecasting tool. The HEMS has been implemented on an experimental house emulation system to demonstrate it can operate in real-time.

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Section: Formulation Of the Optimization Problem And Constraintsmentioning

confidence: 99%

Performance Assessment of an Energy Management System for a Home Microgrid with PV Generation

et al. 2020

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“…The BESS was planned to balance the demand for loads during times of unavailability of renewable energy sources. In this paper, in addition to the demand based on the following formula, battery capacity is planned in accordance with the desired autonomy date [23]. The desired autonomy day parameter means the number of days a battery bank would be able to satisfy the energy demand of PV systems that are presented mathematically as follows,…”

Section: Modelling Of Bessmentioning

confidence: 99%

An Emperor Penguin Optimization and Particle Swarm Optimization Control algorithm for PV with ZSI in Grid Connected System

Vidhya

R²

2021

Preprint

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In the paper, a distributed controller for the analysis of SEPIC and Z-Source Inverter (ZSI) based grid-connected Photovoltaic (PV) system. The PV systems are modeled, designed and implemented to given maximum power output with the help of proposed controller. In the paper, a distributed controller is designed to provide maximum output power and to working by changing irradiance and providing various range of active power. An enhanced controller is specified as the Fractional Order PID (FOPID) controller with aid of hybrid approach. The hybrid approach is consisting of Emperor Penguin Optimization (EPO) and Particle Swarm Optimization (PSO). FOPID controller is the advanced PID controller and it gives a better output and robustness than the traditional PID controller. To enhance the performance of the FOPID, the gain parameters are optimized with the utilization of hybrid approach. For achieving the optimal power management and maximum power tracking, the objective function is defined and specified their constraints also. Here, two various methods have been deliberated to changing the inverter operation with constant irradiance and varied irradiance. The proposed method is tested by using MATLAB/Simulink and it is contrasted with the previously developed methods like base model, Ant Colony Optimization (ACO) and PSO algorithm.

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“…The main purpose of using the ESS system is to store the excess energy from RERs and other resources and thus compensate for the energy shortage during periods of lack of supplying power to the load. The ESS is modeled as (10) [32], [33]:…”

Section: ) Ess Modelmentioning

confidence: 99%

Scheduling of Diesel Generators Operation with Restricted PCC in Microgrid

Aklo¹,

Rashid²

2021

IJEEE

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Smart Microgrid (MG) effectively contributes to supporting the electrical power systems as a whole and reducing the burden on the utility grid by the use of unconventional energy generation resources, in addition to backup Diesel Generators (DGs) for reliability increasing. In this paper, potential had been done on day-ahead scheduling of diesel generators and reducing the energy cost reached to the consumers side to side with renewable energy resources, where economical energy and cost-effective MG has been used based on optimization agent called Energy Management System (EMS). Improved Particle Swarm Optimization (IPSO) technique has been used as an optimization method to reduce fuel consumption and obtain the lowest energy cost as well as achieving the best performance to the energy system. Three scenarios are adopted to prove the efficiency of the proposed method. The first scenario uses a 24 hour time horizon to investigate the performance of the model, the second scenario uses two DGs and the third scenario depends on a 48-hour time horizon to validating the performance. The superiority of the proposed method is illustrated by comparing it with PSO and simulation results show using the proposed method can reducing the fuel demand and the energy cost by satisfying the user’s preference.

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Energy management system for hybrid PV-wind-battery microgrid using convex programming, model predictive and rolling horizon predictive control with experimental validation

Cited by 129 publications

References 49 publications

Performance Assessment of an Energy Management System for a Home Microgrid with PV Generation

Performance Assessment of an Energy Management System for a Home Microgrid with PV Generation

An Emperor Penguin Optimization and Particle Swarm Optimization Control algorithm for PV with ZSI in Grid Connected System

Scheduling of Diesel Generators Operation with Restricted PCC in Microgrid

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