Battery sizing and rule-based operation of grid-connected photovoltaic-battery system: A case study in Sweden

Zhang, Yang; Lundblad, Anders; Campana, Pietro Elia; Benavente-Araoz, Fabian; Yan, Jinyue

doi:10.1016/j.enconman.2016.11.060

Cited by 171 publications

(56 citation statements)

References 48 publications

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“…While much literature exists on the use of grid-connected domestic PV-battery systems for increasing energy self-sufficiency and reducing electricity bills [6][7][8][9][10][11][12][13], literature that examines environmental impacts shows that such systems cannot always be assumed to be 'green'. Kabakian et al (2015) [14] showed that a 1.8 kW PV system with lead-acid batteries in Lebanon had slightly more embodied lifetime greenhouse gas (GHG) emissions than the 1.8 kW PV alone, 92 g of CO 2 -equivalent per kWh delivered compared to 89 g/kWh.…”

Section: Introductionmentioning

confidence: 99%

“…As such, environmental impacts were negative when those operating strategies were applied to Portugal and Poland [18]. The literature is abundant with algorithms for peak reduction, cost minimization and self-sufficiency maximization [6][7][8][9][10][11][12][13]. There is good reason for this: All these objectives are quantifiable and desired by consumers, distribution network operators, or other relevant stakeholders.…”

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confidence: 99%

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An Emissions Arbitrage Algorithm to Improve the Environmental Performance of Domestic PV-Battery Systems

Sun

Crossland²,

Chipperfield

et al. 2019

Energies

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Domestic PV-battery systems are rarely operated in a way which specifically maximizes environmental benefit. Consequently the studies that seriously examine such systems often find that the greenhouse gas and pollutant emissions savings of rooftop PV, though still positive, are lessened by adding a domestic battery. This study shows thatby simulating a PV-battery system with a range of sizes that this need not be inevitable. A novel algorithm was designed specifically to perform 'emissions arbitrage': to charge the battery when the grid emissions intensity is low and to discharge when it is high. It was found that the CO 2 saved relative to the same system with PV only can more than pay back the CO 2 debt of manufacturing the battery. This is true as long as the UK moves away from the present-day situation where natural gas-fired generators are nearly always the marginal generator. This work underlines the importance of both the operating strategy and the interactions between the system and the entire grid, in order to maximize the environmental benefit achievable with domestic PV-battery systems.In contrast, Faria et al. (2014) [18] showed that a second-life electric vehicle battery could reduce global warming, abiotic depletion, acidification and eutrophication factors by 2% when used in a peak-shaving application in France, and 4-5% in a load-shifting application (both without PV). This is because the French grid emissions intensities change throughout the day in such a way that electricity is imported from the grid when emissions are low and exported to the grid when they are high. This 'emissions arbitrage' effect was not accounted for in the other papers mentioned, which assumed a constant grid emissions intensity.A flaw in the work of Faria et al. (2014) [18] is that they used average rather than marginal emissions intensities. If some grid-generated electricity is displaced by the injection of PV power, or indeed any other intervention, not all the generator types (nuclear, coal, biomass, etc.) would have their output reduced in the same proportion as their total generation. The reduction would occur mostly for the generator type with the highest running cost. This gives rise to the concept of marginal emissions factor (MEF, as opposed to average emissions factor, AEF). Studies have shown that using AEF rather than MEF can cause errors of up to 25% [19][20][21][22].It should also be noted that the battery operating strategies studied by Faria et al. (2014) were not designed to achieve emissions arbitrage. As such, environmental impacts were negative when those operating strategies were applied to Portugal and Poland [18]. The literature is abundant with algorithms for peak reduction, cost minimization and self-sufficiency maximization [6][7][8][9][10][11][12][13]. There is good reason for this: All these objectives are quantifiable and desired by consumers, distribution network operators, or other relevant stakeholders. However, environmental benefit is also desirable, as evidenced by survey data on opini...

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

An Emissions Arbitrage Algorithm to Improve the Environmental Performance of Domestic PV-Battery Systems

Sun

Crossland²,

Chipperfield

et al. 2019

Energies

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“…A possible solution to compensate for the intermittency is to incorporate energy storage unit (ESU) into the PV grid‐connected charging system (simply known as a PV‐ESU grid system) . In this case, the optimum sizes of the alternative sources (PV array and ESU) must be determined to avoid the economic losses to the system while providing the required charging services …”

Section: Introductionmentioning

confidence: 99%

“…[16][17][18] In this case, the optimum sizes of the alternative sources (PV array and ESU) must be determined to avoid the economic losses to the system while providing the required charging services. 19,20 Since the PV-ESU grid charging concept is relatively new, there are limited literature that discuss the component (PV and ESU) sizing and its effects on the utility grid and EV users. 21 Majority of the present and past works deal with the grid charging only.…”

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confidence: 99%

Optimized sizing of photovoltaic grid‐connected electric vehicle charging system using particle swarm optimization

et al. 2018

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Summary In this paper, the particle swarm optimization (PSO) is used to find optimum size of the photovoltaic (PV) array and energy storage unit (ESU) for PV grid‐connected charging system (in office workplace) for electric vehicles (EV). It is designed in such a way that the EVs are charged at a fixed price (rather than time‐of‐use price) without incurring economic losses to the station owner. The simulation is modeled using the single diode model (for PV) and the state of charge of Li‐ion battery (for ESU and EV). The objective function of the PSO is formulated based on a financial model that comprises of the grid tariff, EV demand, and the purchasing as well as selling prices of the energy from PV and ESU. By integrating the financial model with energy management algorithm (EMA), the PSO computes the minimum number of PV modules (Npv) and ESU batteries (Nbat) for a various number of vehicles and office holidays. The resiliency of the proposed system is validated under different weather conditions, EV fleet, parity levels, energy prices, and operating period. Furthermore, the performance of the proposed system is compared with the standard grid charging system. The results suggest that with the computed Npv and Nbat, the charging price is decreased by approximately 16%, while the EV charging burden on the grid is reduced by 94% to 99%. It is envisaged that this work provides the guidance for the installers to precisely determine the optimum size of the components prior to the physical construction of the charging station.

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“…Ru et al [9] and Khalilpour et al [10] addressed the sizing problem with consideration of the operation strategies. Zhang et al summarized the existing methods and proposed an approach, which simultaneously obtained the storage capacity and rulebased operation strategies [11].…”

Section: Introductionmentioning

confidence: 99%

Comparative study of hydrogen storage and battery storage in grid connected photovoltaic system: Storage sizing and rule-based operation

et al. 2017

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The paper studies grid connected photovoltaic(PV)-hydrogen/battery systems. The storage component capacities and the rule-based operation strategy parameters are simultaneously optimized by the Genetic Algorithm. Three operation strategies for the hydrogen storage, namely conventional operation strategy, peak shaving strategy and hybrid operation strategy, are compared under two scenarios based on the pessimistic and optimistic costs. The results indicate that the hybrid operation strategy, which combines the conventional operation strategy and the peak shaving strategy, is advantageous in achieving higher Net Present Value (NPV) and Self Sufficiency Ratio (SSR). Hydrogen storage is further compared with battery storage. Under the pessimistic cost scenario, hydrogen storage results in poorer performance in both SSR and NPV. While under the optimistic cost scenario, hydrogen storage achieves higher NPV. Moreover, when taking into account the grid power fluctuation, hydrogen storage achieves better performance in all three optimization objectives, which are NPV, SSR and GI (Grid Indicator).

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Battery sizing and rule-based operation of grid-connected photovoltaic-battery system: A case study in Sweden

Cited by 171 publications

References 48 publications

An Emissions Arbitrage Algorithm to Improve the Environmental Performance of Domestic PV-Battery Systems

An Emissions Arbitrage Algorithm to Improve the Environmental Performance of Domestic PV-Battery Systems

Optimized sizing of photovoltaic grid‐connected electric vehicle charging system using particle swarm optimization

Comparative study of hydrogen storage and battery storage in grid connected photovoltaic system: Storage sizing and rule-based operation

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