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Smart and optimization-based operation scheduling strategies for maximizing battery profitability and longevity in grid-connected application

Shabani, Masoume (författare)
Mälardalens universitet,Framtidens energi
Wallin, Fredrik, 1973- (författare)
Mälardalens universitet,Framtidens energi
Dahlquist, Erik, 1951- (författare)
Mälardalens universitet,Framtidens energi
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Yan, Jinyue, 1959- (författare)
Mälardalens universitet,Framtidens energi,Department of Building Environment and Energy Engineering, Hong Kong Polytechnic University, Hong Kong
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 (creator_code:org_t)
Elsevier, 2024
2024
Engelska.
Ingår i: Energy Conversion and Management. - : Elsevier. - 2590-1745. ; 21
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Lithium-ion battery storage has emerged as a promising solution for various energy systems. However, complex degradation behavior, relatively short lifetime, high capital, and operational costs, and electricity market volatility are critical factors that challenge its practical viability. Thus, to ensure sustained profitability of Lithium-ion batteries in real-life applications, a smart and optimal management strategy considering key influencing factors is imperative for achieving efficient battery utilization. This study proposes two day-ahead battery-behavior-aware operation scheduling strategies to maximize profitability and longevity in residential grid-connected applications with dynamic electricity pricing. Each scenario employs unique approaches to make optimal decisions for optimal battery utilization. The first scenario optimizes short-term profitability by prioritizing revenue gains under three charge/discharge rates (high, moderate, low), considering daily charge and discharge timings as decision variables. Conversely, the second scenario proposes a smart strategy capable of making intelligent decisions on a wide range of variables to simultaneously maximize revenue and minimize degradation costs, ensuring short-term and long-term profitability. Decision variables include the cycle frequency for each specific day, timings as well as durations for charging and discharging per cycle. To ensure effective long-term assessment, both scenarios accurately estimate battery performance, calendric and cyclic capacity degradations, remaining-useful-lifetime, and internal states under real operational conditions until battery reaches its end-of-life criteria. The scenarios are assessed economically using various indicators. Furthermore, the impact of battery price and size on optimization outcomes are examined. The key findings indicate that, among the first set of scenarios, the strategy with low charge/discharge rate extends the battery lifetime most efficiently, estimated at 14.8 years. However, it proved to be the least profitable, resulting in negative profit of −3€/kWh/yr. On the other hand, strategies with high and moderate charge/discharge rates resulted in positive profit of 8.3 €/kWh/year and 9.2 €/kWh/year, despite having shorter battery lifetimes, estimated at 10.1 years and 13.6 years, respectively. Furthermore, from a payback perspective, the strategy with fast charge/discharge capability led to 1.5 years shorter payback period than that of the moderate rate strategy. The findings highlight that the first set of scenarios limits the strategy's flexibility in achieving both sustainability and profitability. In contrast, the second scenario achieves impressive profit (18 €/kWh/yr), shortest payback period (7.5 year), a commendable lifespan (12.5 years), contrasting revenue-focused scenarios, emphasizing the importance of striking optimal balance between revenue gain and degradation costs for charging/discharging actions, ensuring sustained profitability. The findings offer valuable insights for decision-makers, enabling informed strategic choices and effective solutions.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Energiteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Energy Engineering (hsv//eng)

Nyckelord

Day-ahead optimization-based battery operation scheduling
Degradation cost minimization
Price arbitrage within real-time electricity price tariff
Residential-grid connected battery application
Revenue maximization
Sustained profitability optimization
Battery management systems
Charging (batteries)
Costs
Decision making
Housing
Investments
Lithium-ion batteries
Power markets
Battery applications
Battery operation
Cost minimization
Day-ahead
Electricity prices
Grid-connected
Operations scheduling
Optimisations
Real- time
Profitability

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