Data-Driven Distributionally Robust Economic Dispatch of Offshore Engineering Microgrids: Multi-Functional Battery Coordination, Life-Cycle Cost Awareness, and Dual Time-Scale Optimization

Offshore engineering microgrids integrate renewable generation, energy storage, and large marine test loads. Frequent start-stop transients of test loads, strong wind/PV fluctuations, and saline–humid conditions accelerate equipment aging and threaten power quality, while conventional dispatch neglects battery degradation, converter stress, and test-load energy recovery. This paper develops a data-driven distributionally robust economic dispatch method combining: (i) a priority-based dynamically weighted multi-functional battery coordination model unifying test-load surge suppression, renewable smoothing, and price arbitrage, with its coordinated reference embedded as a tracking constraint with an explicit two-level reserved margin; (ii) a two-stage Wasserstein distributionally robust optimization with adaptive ambiguity radii on standardized forecast errors and an improved column-and-constraint generation algorithm covering the full vertex set of the standardized uncertainty box; and (iii) a life-cycle-cost-aware objective with linearized battery degradation and converter power-variation stress under a dual time-scale (1 h day-ahead/15 min intraday) framework. Case studies on grid-connected and islanded offshore engineering microgrids show that multi-functional coordination lowers the post-storage maximum load ramp rate from 23.57 to 19.31 kW/min (−18.1%) and its standard deviation from 6.25 to 5.79 kW/min (−7.3%) at an operating-cost increase of 126.4 CNY/day, while reducing downstream renewable power fluctuation by 41.0% and recovering 102.0 kWh/day of test-load regenerative energy. The distributionally robust schedule attains a first-stage cost of 9492.5 CNY and, over 1000 independent realizations, reduces the out-of-sample mean cost from 9656.1 CNY (deterministic) to 9397.3 CNY and the 95% conditional value at risk (CVaR95) from 9940.5 to 9552.1 CNY, versus 10,698.3 CNY for a box-robust schedule with equivalent 95% coverage. The life-cycle-cost-aware dispatch reduces equivalent battery capacity fade by 37.1% and converter power-variation stress by 32.5% at +1.76% operating cost, while maintaining energy-based supply reliability at 99.79–100%. When the four mechanisms operate simultaneously, the maximum post-storage ramp is 19.31 kW/min against 23.57 kW/min for the unintegrated baseline (−18.1%), and removing the distributionally robust layer from the integrated schedule raises the out-of-sample CVaR95 of the recourse cost from 68.8 to 609.2 CNY/day. All optimization results are reproduced by two independent MILP solvers, with objectives agreeing within 2 × 10−9.

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Publication Details

Journal
Energies
Published
2026-10-27
DOI
https://doi.org/10.3390/en19215113
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Data-Driven Distributionally Robust Economic Dispatch of Offshore Engineering Microgrids: Multi-Functional Battery Coordination, Life-Cycle Cost Awareness, and Dual Time-Scale Optimization

Xiang Gu, Nan Hu, Xiuyong Yu, Lei Zhang
2 links
Energies
Microgrid Control and Optimization
article

Data-Driven Distributionally Robust Economic Dispatch of Offshore Engineering Microgrids: Multi-Functional Battery Coordination, Life-Cycle Cost Awareness, and Dual Time-Scale Optimization

Xiang Gu, Nan Hu, Xiuyong Yu, Lei Zhang
article en

Abstract

Offshore engineering microgrids integrate renewable generation, energy storage, and large marine test loads. Frequent start-stop transients of test loads, strong wind/PV fluctuations, and saline–humid conditions accelerate equipment aging and threaten power quality, while conventional dispatch neglects battery degradation, converter stress, and test-load energy recovery. This paper develops a data-driven distributionally robust economic dispatch method combining: (i) a priority-based dynamically weighted multi-functional battery coordination model unifying test-load surge suppression, renewable smoothing, and price arbitrage, with its coordinated reference embedded as a tracking constraint with an explicit two-level reserved margin; (ii) a two-stage Wasserstein distributionally robust optimization with adaptive ambiguity radii on standardized forecast errors and an improved column-and-constraint generation algorithm covering the full vertex set of the standardized uncertainty box; and (iii) a life-cycle-cost-aware objective with linearized battery degradation and converter power-variation stress under a dual time-scale (1 h day-ahead/15 min intraday) framework. Case studies on grid-connected and islanded offshore engineering microgrids show that multi-functional coordination lowers the post-storage maximum load ramp rate from 23.57 to 19.31 kW/min (−18.1%) and its standard deviation from 6.25 to 5.79 kW/min (−7.3%) at an operating-cost increase of 126.4 CNY/day, while reducing downstream renewable power fluctuation by 41.0% and recovering 102.0 kWh/day of test-load regenerative energy. The distributionally robust schedule attains a first-stage cost of 9492.5 CNY and, over 1000 independent realizations, reduces the out-of-sample mean cost from 9656.1 CNY (deterministic) to 9397.3 CNY and the 95% conditional value at risk (CVaR95) from 9940.5 to 9552.1 CNY, versus 10,698.3 CNY for a box-robust schedule with equivalent 95% coverage. The life-cycle-cost-aware dispatch reduces equivalent battery capacity fade by 37.1% and converter power-variation stress by 32.5% at +1.76% operating cost, while maintaining energy-based supply reliability at 99.79–100%. When the four mechanisms operate simultaneously, the maximum post-storage ramp is 19.31 kW/min against 23.57 kW/min for the unintegrated baseline (−18.1%), and removing the distributionally robust layer from the integrated schedule raises the out-of-sample CVaR95 of the recourse cost from 68.8 to 609.2 CNY/day. All optimization results are reproduced by two independent MILP solvers, with objectives agreeing within 2 × 10−9.

EnergiesVol. 19(21)
Nanjing Normal University (CN)
Affordable and clean energy, Industry, innovation and infrastructure, Climate action
Openalex Percentile: Top 17%
Microgrid Control and Optimization
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