A simple PV constrained production control strategy

Wang, Baochao; Houssamo, Issam; Sechilariu, Manuela; Locment, Fabrice

doi:10.1109/isie.2012.6237220

Cited by 19 publications

(11 citation statements)

References 7 publications

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“…Therefore, for this third case, the difference between PVA power and PEVs power, Δp, is not the same as that presented in Figure 10b. During the mentioned time slots, a PVA power shedding algorithm is applied for the PVA control as developed in [35]. The PVA power limitation is operated according to PEVs power demand and the public grid power limitation.…”

Section: Microgrid Simulation Based On Storage Current Limitation mentioning

confidence: 99%

Modeling and Simulation of DC Microgrids for Electric Vehicle Charging Stations

Locment

Sechilariu

2015

Energies

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This paper focuses on the evaluation of theoretical and numerical aspects related to an original DC microgrid power architecture for efficient charging of plug-in electric vehicles (PEVs). The proposed DC microgrid is based on photovoltaic array (PVA) generation, electrochemical storage, and grid connection; it is assumed that PEVs have a direct access to their DC charger input. As opposed to conventional power architecture designs, the PVA is coupled directly on the DC link without a static converter, which implies no DC voltage stabilization, increasing energy efficiency, and reducing control complexity. Based on a real-time rule-based algorithm, the proposed power management allows self-consumption according to PVA power production and storage constraints, and the public grid is seen only as back-up. The first phase of modeling aims to evaluate the main energy flows within the proposed DC microgrid architecture and to identify the control structure and the power management strategies. For this, an original model is obtained by applying the Energetic Macroscopic Representation formalism, which allows deducing the control design using Maximum Control Structure. The second phase of simulation is based on the numerical characterization of the DC microgrid components and the energy management strategies, which consider the power source requirements, charging times of different PEVs, electrochemical storage ageing, and grid power limitations for injection mode. The simulation results show the validity of the model and the feasibility of the proposed DC microgrid power architecture which presents good performance in terms of total efficiency and simplified control. OPEN ACCESSEnergies 2015, 8 4336

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Section: Microgrid Simulation Based On Storage Current Limitation mentioning

confidence: 99%

Modeling and Simulation of DC Microgrids for Electric Vehicle Charging Stations

Locment

Sechilariu

2015

Energies

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“…PV sources are mostly controlled by a maximum power point tracking (MPPT) algorithm [27], but could be controlled to output a limited power [28], if required. The storage system is an electrochemical system that is technically and economically well adapted for a building-integrated microgrid system.…”

Section: Microgrid Control Strategymentioning

confidence: 99%

“…Nevertheless, to protect storage from overcharging, the PV production may be partially shed by the limited PV production algorithm described in [28]. The PV sources power PV p is given by Equation (5): .…”

Section: Isolated DC Microgrid Controlmentioning

confidence: 99%

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Photovoltaic Electricity for Sustainable Building. Efficiency and Energy Cost Reduction for Isolated DC Microgrid

2015

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Abstract:In the context of sustainable buildings, this paper investigates power flow management for an isolated DC microgrid and focuses on efficiency and energy cost reduction by optimal scheduling. Aiming at high efficiency, the local produced power has to be used where, when, and how it is generated. Thus, based on photovoltaic sources, storage, and a biofuel generator, the proposed DC microgrid is coupled with the DC distribution network of the building. The DC bus distribution maximizes the efficiency of the overall production-consumption system by avoiding some energy conversion losses and absence of reactive power. The isolated DC microgrid aims to minimize the total energy cost and thus, based on forecasting data, a cost function is formulated. Using a mixed integer linear programming optimization, the optimal power flow scheduling is obtained which leads to an optimization-based strategy for real-time power balancing. Three experimental tests, operated under different meteorological conditions, validate the feasibility of the proposed control and demonstrate the problem formulation of minimizing total energy cost.

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“…When the battery is full or is charging at the maximum rate R, photovoltaic production must be limited. Various algorithms are proposed in the literature to switch from the usual maximum power point tracking (MPPT) to a limited-power regime (e.g., [34]). Conversely, to counteract the effects of unpredicted energy deficits, we assume the presence of an emergency recovery mechanism that automatically switches the operational mode to grid-connected if either the storage bank charge level drops below a safety threshold or it is discharging at a rate above a safety threshold.…”

Section: Objective Functionsmentioning

confidence: 99%

An Energy Management Service for the Smart Office

et al. 2015

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The evolution of the electricity grid towards the smart grid paradigm is fostering the integration of distributed renewable energy sources in smart buildings: a combination of local power generation, battery storage and controllable loads can greatly increase the energetic self-sufficiency of a smart building, enabling it to maximize the self-consumption of photovoltaic electricity and to participate in the energy market, thus taking advantage of time-variable tariffs to achieve economic savings. This paper proposes an energy management infrastructure specifically tailored for a smart office building, which relies on measured data and on forecasting algorithms to predict the future patterns of both local energy generation and power loads. The performance is compared to the optimal energy usage scheduling, which would be obtained assuming the exact knowledge of the future energy production and consumption trends, showing gaps below 10% with respect to the optimum.

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A simple PV constrained production control strategy

Cited by 19 publications

References 7 publications

Modeling and Simulation of DC Microgrids for Electric Vehicle Charging Stations

Modeling and Simulation of DC Microgrids for Electric Vehicle Charging Stations

Photovoltaic Electricity for Sustainable Building. Efficiency and Energy Cost Reduction for Isolated DC Microgrid

An Energy Management Service for the Smart Office

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