On the influence of electricity demand patterns, battery storage and PV system design on PV self-consumption and grid interaction

Litjens, G.B.M.A.; Sark, W.G.J.H.M. van; Worrell, Ernst

doi:10.1109/pvsc.2016.7749983

Cited by 14 publications

(5 citation statements)

References 7 publications

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“…One of the limitation for injecting the RES production into the grid is that the selling price of local renewable energy production is very less than the price of energy that is bought from the grid. In addition, considering the grid stability issues involved with high injection of renewable energy into the distribution grid, the new policies [2] in many countries support the increase in the self-consumption of solar-PV [3].…”

Section: Introductionmentioning

confidence: 99%

Maximizing the self-consumption of Solar-PV using Battery Energy Storage System in Samsø-Marina

Ponnaganti

Bak‐Jensen

Pillai

2019

2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

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Samsøø is a medium sized Danish island located in the sea of Kattegat. Almost 90% of the island's production comes from renewable energy sources (RES) including wind and solarphotovoltaics. The fluctuating nature of these resources leads to its reduced utilization. Installing battery energy storage systems (BESS) at local communities or residences in the island not only improves the utilization efficiency but also increases the revenue to the utility/RES owners. This paper proposes a method for maximizing the self-consumption of RES using BESS installation at the Ballen-Marina site in the Samsøø island. The reported simulation studies are carried out for summer months i.e., mid-July to mid-September based on real data from the Marina site.

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Section: Introductionmentioning

confidence: 99%

Maximizing the self-consumption of Solar-PV using Battery Energy Storage System in Samsø-Marina

Ponnaganti

Bak‐Jensen

Pillai

2019

2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

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“…In [8], an investigation into the installed PV sizes in public buildings illustrated that the PV energy production and consumption match over time, so the given solution suggested no need for BESS. In [9], the impact of residential and commercial consumption on the SCC rates and curtailed energy was investigated. Different PV and BESS system sizes were used as the control parameters of the influence problem of 400 residential and 26 commercial communities in the Netherlands.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization Framework for Integration of Distributed Energy Resources in Smart Communities

Ahmadi

Pappu

Hoogsteen

et al. 2022

2022 57th International Universities Power Engineering Conference (UPEC)

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This paper studies a multi-objective optimization problem on the allocation problem of photovoltaic (PV) and battery energy storage systems (BESSs) in a community, whereby the aim is to find Pareto optimal solutions according to two different set of objective functions. These objective functions are minimizing the dependency of the whole community or each household on the national grid and minimizing the investment, operation, and maintenance costs of PV and BESS units. A Parallel Multi-Objective Multi-Verse Optimization (PMOMVO) algorithm is developed to obtain the Pareto optimal solutions for the problems. The optimization framework is used to determine all Pareto front solutions in a real community and the results are compared to the base case scenario of the community. The Pareto solutions show that by small investment in the BESS units, community can be less dependent on the national grid even with less PV panels installed in the community.

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“…The most crucial aspect of self-consumption/management is the reduction of the exchanged energy with the grid, which of course, necessitates an efficient control of the ESSs [7], [8]. Several ESS control schemes are already proposed for residential Energy Management System (EMS), where computational intelligence methods are commonly employed in both off-line and real-time operations.…”

Section: Introductionmentioning

confidence: 99%

Forecast-Based Energy Management for Domestic PV-Battery Systems: A U.K. Case Study

et al. 2021

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This paper presents a predictive Energy Management System (EMS), aimed to improve the performance of a domestic PV-battery system and maximize self-consumption by minimizing energy exchange with the utility grid. The proposed algorithm facilitates a self-consumption approach, which reduces electricity bills, transmission losses, and the required central generation/storage systems. The proposed EMS uses a combination of Fuzzy Logic (FL) and a rule based-algorithm to optimally control the PV-battery system while considering the day-ahead energy forecast including forecast error and the battery State of Health (SOH). The FL maximizes the lifetime of the battery by using SOH and State of Charge (SOC) in decision making algorithm to charge/discharge the battery. The proposed Battery Management System (BMS) has been tested using Active Office Building (AOB) located in Swansea University, UK. Furthermore, it is compared with three recently published methods and with the current BMS utilized in the AOB to show the effectiveness of the proposed technique. The results show that the proposed BMS achieves a saving of 18% in the total energy cost over six months compared to a similar day-ahead forecast-based work. It also achieves a saving up to 95% compared to other methods (with a similar structure) but without a day-ahead forecast-based management. The proposed BMS enhances the battery's lifetime by reducing the average SOC up to 47% compared to the previous methods through avoiding unnecessary charge and discharge cycles. The impact of the PV system size and the battery capacity on the net exchanged energy with the utility grid is also investigated in this study.INDEX TERMS Battery management system, energy management system, fuzzy logic, state of charge, state of health.

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On the influence of electricity demand patterns, battery storage and PV system design on PV self-consumption and grid interaction

Cited by 14 publications

References 7 publications

Maximizing the self-consumption of Solar-PV using Battery Energy Storage System in Samsø-Marina

Maximizing the self-consumption of Solar-PV using Battery Energy Storage System in Samsø-Marina

Multi-Objective Optimization Framework for Integration of Distributed Energy Resources in Smart Communities

Forecast-Based Energy Management for Domestic PV-Battery Systems: A U.K. Case Study

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