Predictive Active Power Control of Two Interconnected Microgrids

Tungadio, Diambomba H.; Bansal, Ramesh C.; Siti, Mukwanga W.; Mbungu, Nsilulu T.

doi:10.1007/s40866-018-0040-2

Cited by 26 publications

(25 citation statements)

References 37 publications

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“…Table provides a comparative analysis of other approaches applied to EMS. Tungadio et al presented a study on the MPC approach for controlling power flow in AC‐tie line and frequency deviations in a system composed of two microgrids. The simulation results were compared with those obtained using the open control loop; it was found that that closed‐loop base MPC is much faster and accurate as compared with open‐loop control for a complex dynamical system.…”

Section: Solution Approaches For Emsmentioning

confidence: 99%

Energy management system for smart grid: An overview and key issues

2020

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Summary Energy crisis and the global impetus to “go green” have encouraged the integration of renewable energy resources, plug‐in electric vehicles, and energy storage systems to the grid. The presence of more than one energy source in the grid necessitates the need for an efficient energy management system to guide the flow of energy. Moreover, the variability and volatile nature of renewable energy sources, uncertainties associated with plug‐in electric vehicles, the electricity price, and the time‐varying load bring new challenges to the power engineers to achieve demand‐supply balance for stable operation of the power system. The energy management system can effectively coordinate the energy sharing/trading among all available energy resources, and supply loads economically in all the conditions for the reliable, secure, and efficient operation of the power system. This paper reviews the framework, objectives, architecture, benefits, and challenges of the energy management system with a comprehensive analysis of different stakeholders and participants involved in it. The review paper gives a critical analysis of the distributed energy resources behavior and different programs such as demand response, demand‐side management, and power quality management implemented in the energy management system. Different uncertainty quantification methods are also summarized. This review paper also presents a comparative and critical analysis of the main optimization techniques used to achieve different energy management system objectives while satisfying multiple constraints. Thus, the review offers numerous recommendations for research and development of the cutting‐edge optimized energy management system applicable for homes, buildings, industries, electric vehicles, and the whole community.

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Section: Solution Approaches For Emsmentioning

confidence: 99%

Energy management system for smart grid: An overview and key issues

2020

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“…Energy efficiency on a smart grid system reduces the overall cost of power and secures the power flow coordination between the energy supply and demand. Several strategies have recently been implemented to effectively manage the energy flow on the different types of the electrical system; from residential usage to industrial consumption [8][9][10][11][12][13][14][15][16].…”

Section: Literature Surveymentioning

confidence: 99%

Smart energy coordination of autonomous residential home

2019

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The smart grid technology permits the revolution of the electrical system from a conventional power grid to an intelligent power network which has led the improvements in electrical system in terms of energy efficiency and sustainable energy integration. This study presents the energy management/coordination scheme for domestic demand using the key strategy of smart grid energy efficiency modelling. The structure consists of combining renewable energy resources, photovoltaic (PV) and wind power generation connected to the utility grid with energy storage system (ESS) in an optimal control manner to coordinate the power flow of a residential home. Based on the demand response schemes in the framework of real-time electricity pricing, this work designs a closed-loop optimal control strategy that is created by the dynamic model of the ESS to compute the system performance index, which is formulated by the cost of the energy flows. A dynamic distributed energy storage strategy (DDESS) is implemented to optimally coordinate the energy system, which reduces the total energy consumption from the main grid of more than 100% of the load demand. The designed model introduces a payback scheme while robustly optimising the energy flows and minimising the utility grid's energy consumption cost.

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“…An active power control approach is implemented under smart grid framework using model predictive control (MPC) to coordinate the energy flow of two interconnected microgrids [162]. This system aims to actively control the RERs and the storage ability so that the deviation of active power and frequency in the tie-line of the electrical system as a whole can be minimized.…”

Section: B Smart Microgridmentioning

confidence: 99%

Overview of the Optimal Smart Energy Coordination for Microgrid Applications

Mbungu¹,

Naidoo²,

Bansal³

et al. 2019

IEEE Access

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This paper describes an overview of the optimal energy coordination/management approaches for microgrids. The article presents the smart grid environment in conjunction with their technologies into the applications of a microgrid when the energy coordination aims to create power flow stability between the generation and consumption of the electricity. This energy equilibrium is made regardless of a power grid complexity that can contain diverse load demands and distributed energy resources (DERs), including renewable energy system (RES), energy storage system (ESS), electric vehicle (EV), etc. A microgrid often contains an energy mix system that requires three control levels, namely primary, secondary and tertiary, to optimize the energy cost and behavior of the system operation and exploitation. Based on several DERs, a microgrid can operate in island mode or be connected to the main grid. The energy coordination for both features is to deal with the energy resources uncertainty, the climate impact, to reduce atmospheric pollution deriving from the conventional power grid, and the energy demand growth. Through the smart grid technology, the optimization approaches of this coordination have brought several improvements into the electrical system. Thus, an overview of an intelligent energy management system for microgrid applications is intensively detailed to structure the implementation strategies which aim to coordinate the energy flow of an electrical system optimally.

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Predictive Active Power Control of Two Interconnected Microgrids

Cited by 26 publications

References 37 publications

Energy management system for smart grid: An overview and key issues

Energy management system for smart grid: An overview and key issues

Smart energy coordination of autonomous residential home

Overview of the Optimal Smart Energy Coordination for Microgrid Applications

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