A Multiagent Fuzzy-Logic-Based Energy Management of Hybrid Systems

Lagorse, Jeremy; Simões, Marcelo Godoy; Miraoui, Abdellatif

doi:10.1109/tia.2009.2031786

Cited by 156 publications

(89 citation statements)

References 6 publications

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“…For instance, a lithium-ion battery and fuel cell are used in [30] to prevent the power failure of a DC microgrid consisting of PVS and wind energy, in which a fuzzy logic controller (FLC) was designed to improve the battery's life by maintaining its desired SOC. In [31], a similar HES was deployed and the operation of ESS was controlled using a multi-agent FLC by referring to the SOC of both the DC bus and ESS. Another energy management scheme used to minimize the grid power fluctuations or consumption of a residential grid-connected microgrid while keeping the SOC of ESS within secure limits was reported in [32][33][34].…”

Section: Review Of Existing Literaturementioning

confidence: 99%

“…A central controller was designed in [39] to compensate for the power fluctuation caused by the renewable generation in the microgrid by coordinating the operation of heat pumps and ESS modeled as a two-tank energy storage device. Most existing works [30][31][32][33][34][35][36] related to the life cycle of ESS with its SOC assumed that no significant maintenance costs were incurred by ESS as long as ESS was not overcharged or over-discharged beyond the limits of SOC. Meanwhile, some limited studies [37][38][39] that considered the ESS models with more comprehensive degradation effects during optimization tend to employ a nonlinear mathematical formulation, which is generally not feasible for real-time applications.…”

Section: Review Of Existing Literaturementioning

confidence: 99%

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Optimal Charging and Discharging Scheduling for Electric Vehicles in a Parking Station with Photovoltaic System and Energy Storage System

2017

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Abstract:The economic and environmental benefits brought by electric vehicles (EVs) cannot be fully delivered unless these vehicles are fully or partially charged by renewable energy sources (RES) such as photovoltaic system (PVS). Nevertheless, the EV charging management problem of a parking station integrated with RES is challenging due to the uncertain nature of local RES generation. This paper aims to address these difficulties by deploying an energy storage system (ESS) in parking stations and exploiting the charging and discharging scheduling of EVs to achieve better utilization of intermittent PVS for EV charging. A real-time charging optimization scheme is also formulated, using mixed-integer linear programming (MILP) to coordinate the charging or discharging power of EVs along with the power dispatches of power grid and ESS based on the vehicles' charging or discharging priorities and electricity price preferences. Extensive simulations show that the proposed approach not only maximizes the satisfaction of EV owners in terms of fulfilling all charging and discharging requests, but also minimizes the overall operational cost of the parking station by prioritizing the utilization of energy from PVS, ESS, and scheduling of every EV's charging and discharging.

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Section: Review Of Existing Literaturementioning

confidence: 99%

Section: Review Of Existing Literaturementioning

confidence: 99%

Optimal Charging and Discharging Scheduling for Electric Vehicles in a Parking Station with Photovoltaic System and Energy Storage System

2017

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“…In a fully-distributed control scheme, measurement signals of each MG energy source are sent to corresponding local controllers, as shown in Figure 2 [71][72][73]. These controllers communicate with one another for the purpose of collaborating.…”

Section: Distributed Control Schemementioning

confidence: 99%

A Survey on Smart Agent-Based Microgrids for Resilient/Self-Healing Grids

2017

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This paper presents an overview of our body of work on the application of smart control techniques for the control and management of microgrids (MGs). The main focus here is on the application of distributed multi-agent system (MAS) theory in multi-objective (MO) power management of MGs to find the Pareto-front of the MO power management problem. In addition, the paper presents the application of Nash bargaining solution (NBS) and the MAS theory to directly obtain the NBS on the Pareto-front. The paper also discusses the progress reported on the above issues from the literature. We also present a MG-based power system architecture for enhancing the resilience and self-healing of the system.

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“…In [29], various sectors in designing and implementation of HRES were comprehensively reviewed, including configurations, criteria selection, sizing methodologies and control & energy management. For stand-alone and grid-connected applications, many control systems have been designed into three main categories, i.e., centralized [16,30], distributed [31], and hybrid control paradigms [32]. Due to scope of this paper, energy management methods (planning, scheduling and control) are introduced in this section.…”

Section: Literature Reviewmentioning

confidence: 99%

Demand side management of photovoltaic-battery hybrid system

2015

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In the electricity market, customers have many choices to reduce electricity cost if they can economically schedule their power consumption. Renewable hybrid system, which can explore solar or wind sources at low cost, is a popular choice for this purpose nowadays. In this paper optimal energy management for a grid-connected photovoltaic-battery hybrid system is proposed to sufficiently explore solar energy and to benefit customers at demand side. The management of power flow aims to minimize electricity cost subject to a number of constraints, such as power balance, solar output and battery capacity. With respect to demand side management, an optimal control method (open loop) is developed to schedule the power flow of hybrid system over 24 hours, and model predictive control is used as a closed-loop method to dispatch the power flow in real-time when uncertain disturbances occur. In these two kinds of applications, optimal energy management solutions can be obtained with great cost savings and robust control performance.

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A Multiagent Fuzzy-Logic-Based Energy Management of Hybrid Systems

Cited by 156 publications

References 6 publications

Optimal Charging and Discharging Scheduling for Electric Vehicles in a Parking Station with Photovoltaic System and Energy Storage System

Optimal Charging and Discharging Scheduling for Electric Vehicles in a Parking Station with Photovoltaic System and Energy Storage System

A Survey on Smart Agent-Based Microgrids for Resilient/Self-Healing Grids

Demand side management of photovoltaic-battery hybrid system

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