Optimizing the energy storage schedule of a battery in a PV grid-connected nZEB using linear programming

Georgiou, Giorgos S.; Christodoulides, Paul; Kalogirou, Soteris A.

doi:10.1016/j.energy.2020.118177

Cited by 61 publications

(14 citation statements)

References 13 publications

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“…Most of the research used the battery storage technologies in the modeling of the GCPV systems [37]. The extensive use of the battery storage technologies in PV systems is due to the advantages such as the easy availability and integration [38].…”

Section: A Gcpv Systems With Battery Storagementioning

confidence: 99%

Multi-Criteria Storage Selection Model for Grid-Connected Photovoltaics Systems

et al. 2021

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The grid-connected photovoltaics (GCPV) systems are a sustainable alternative to the conventional non-renewable electricity systems. However, GCPV systems create the many issues such as grid overloading, demand and supply variations, and power quality issues. A key way to address such issues is the integration of the effective energy storage technologies in GCPV systems. There are many storage technologies which can be connected with GCPV systems. The integration of a proper storage technology into the GCPV systems may provide a best alternative. This paper evaluates the different storage technologies for GCPV systems using the analytic hierarchy process (AHP) approach. The goal of the AHP model was the selection of the best storage alternative for GCPV systems based on the multiple criteria. The criteria included the storage parameters as well as the parameters related to the compatibility with GCPV systems. The results exhibited that the pumped hydro storage is the best alternative if all the storage and compatibility parameters are equally desirable. However, if AHP model gives the highest preference to the criteria ''integration simplicity regarding renewable energy'' and ''geographic limitations'', the several other storage technologies achieve the higher rankings. Hence, the AHP model provides a greater flexibility to evaluate the different storage technologies for GCPV systems under different circumstances.INDEX TERMS Analytic hierarchy process (AHP), electrical power grid, environmental sustainability, power flow balancing, power system planning, power system reliability, renewable energy, solar energy, PV.

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Section: A Gcpv Systems With Battery Storagementioning

confidence: 99%

Multi-Criteria Storage Selection Model for Grid-Connected Photovoltaics Systems

et al. 2021

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“…The objective function is a weighted sum of five "separate optimization" functions (terms). A detailed derivation of this can be found in [30], where the LP optimization method was applied and validated for a building case study. The optimization problem reads as follows.…”

Section: Proposed Linear Programming Modelmentioning

confidence: 99%

“…The purpose of the current study was the nearly zeroing of the net grid electrical energy in buildings, in real time, in an optimal manner. This is a problem that, to the best of our knowledge, has only been dealt with on two occasions (References [26,30]), but not in the holistic manner of the current paper, which utilized and integrated convex optimization, heuristic optimization, load and PV forecasting, and realistic battery dispatch software to nearly zero the building's daily net-grid energy. This target was achieved by using LP to optimally dispatch the battery operation in an adaptive manner, assisted by equally powerful methods such as artificial neural networks (ANN) used to forecast both the next 24 hours' PV generation and load demand, and GA to drive LP to optimal solutions based on daily forecasts relating to PV generation and demand.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Optimization Approach for Autonomy Enhancement of Nearly-Zero-Energy Buildings Based on Battery Performance and Artificial Neural Networks

et al. 2020

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Reducing the primary energy consumption in buildings and simultaneously increasing self-consumption from renewable energy sources in nearly-zero-energy buildings, as per the 2010/31/EU directive, is crucial nowadays. This work solved the problem of nearly zeroing the net grid electrical energy in buildings in real time. This target was achieved using linear programming (LP)—a convex optimization technique leading to global solutions—to optimally decide the daily charging or discharging (dispatch) of the energy storage in an adaptive manner, in real time, and hence control and minimize both the import and export grid energies. LP was assisted by equally powerful methods, such as artificial neural networks (ANN) for forecasting the building’s load demand and photovoltaic (PV) on a 24 hour basis, and genetic algorithm (GA)—a heuristic optimization technique—for driving the optimum dispatch. Moreover, to address the non-linear nature of the battery and model the energy dispatch in a more realistic manner, the proven freeware system advisor model (SAM) of National Renewable Energy Laboratory (NREL) was integrated with the proposed approach to give the final dispatch. Assessing the case of a building, the results showed that the annual hourly profile of the import and export energies was smoothed and flattened, as compared to the cases without storage and/or using a conventional controller. With the proposed approach, the annual aggregated grid usage was reduced by 53% and the building’s annual energy needs were covered by the renewable energy system at a rate of 60%. It was therefore concluded that the proposed hybrid methodology can provide a tool to maximize the autonomy of nearly-zero-energy buildings and bring them a step closer to implementation.

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“…The optimal strategy found for the summer season is based on the enthalpy control. Georgiou et al [13] have introduced a novel approach able to adapt to a given PV generation and load demand and individually control the battery and the net grid energy. Aranguren et al [14], by means of a numerical model, have proposed the adoption of a thermoelectric cooler-heat pump.…”

Section: Introduction and Literature State Of The Artmentioning

confidence: 99%

Evaluation and optimization of the performance of the heating system in a nZEB educational building by monitoring and simulation

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et al. 2021

Energy and Buildings

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The optimal control of the HVAC system in the nearly zero energy buildings (nZEBs) can be considered as a challenge.Indeed, the lack of data given by monitored data does not allow understanding what are the implications of different strategies on thermal comfort and energy consumptions. This paper determines an approach for the evaluation of the management of the heating system in an existing educational nZEB. The aim is to understand how the energy efficiency of the heating system is sensitive to controls strategies and the important role played by the control systems. The test lecture rooms on KU Leuven Ghent Technology Campus (Belgium) have been chosen as case study.A deep analysis, starting from an in-field monitoring, was carried out during the winter period of 2019, in order to assess the actual operation and the energy use of building systems under real conditions. Then, a building energy simulation (BES) model of the building and its systems was developed and calibrated against the real monitoring data. Control strategies of the heating system are simulated and compared to the current configuration. The simulation results show that strategies based on a definition of a heating curve for the boiler can reduce the comfortable time (-23%). Controlling the temperature inside the storage tank as a function of the outdoor temperature together with the control on the activation of the air handling unit result in an energy savings from 32% to 46%, with a correspondent increase of comfort time in the period from 0.6% to 3.4% compared to the baseline scenario, depending to the relationship between the external temperature and water temperature inside the water storage tank.

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Optimizing the energy storage schedule of a battery in a PV grid-connected nZEB using linear programming

Cited by 61 publications

References 13 publications

Multi-Criteria Storage Selection Model for Grid-Connected Photovoltaics Systems

Multi-Criteria Storage Selection Model for Grid-Connected Photovoltaics Systems

A Hybrid Optimization Approach for Autonomy Enhancement of Nearly-Zero-Energy Buildings Based on Battery Performance and Artificial Neural Networks

Evaluation and optimization of the performance of the heating system in a nZEB educational building by monitoring and simulation

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