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Efficient battery siting in distribution networks using SBM-DEA
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چکیده: (12 مشاهده) |
| Battery energy storage planning in distribution networks is inherently multi-criteria. The alternative that produces the largest peak reduction may be excessively costly; the minimum-loss alternative may deliver insufficient peak support; and a charging schedule that is beneficial at one bus may aggravate local voltage drop at another. This paper develops an integrated framework for evaluating 63 battery siting and sizing alternatives on the IEEE 33-bus distribution system. In the first stage, hourly AC load flow is performed for every alternative to calculate investment cost, peak reduction, discharged energy, daily energy losses, and voltage deviation. In the second stage, the alternatives are treated as homogeneous decision-making units and evaluated using a non-radial undesirable-output slacks-based measure data envelopment analysis model. Investment cost is the input; peak reduction and discharged energy are desirable outputs; and energy losses and voltage deviation are undesirable outputs. SBM is selected for three substantive reasons: technical and economic criteria contain independent slacks, criterion changes are non-proportional, and undesirable outputs must be modeled directly without reciprocal or translation transformations. Super-SBM is then used to discriminate among efficient alternatives. Under the defined 63-alternative set and the stated deterministic assumptions, a 750-kW, four-hour battery at bus 14 obtains the highest super-efficiency score; this result identifies the most efficient observed alternative within the study design and should not be interpreted as a universally optimal network-planning solution. Nevertheless, the minimum-loss alternative ranks only 35th, demonstrating that superior single-criterion performance is not equivalent to efficient capital use. Sensitivity analyses on battery cost structure, PV penetration, loading level, and returns to scale show that the ranking pattern is broadly stable, although the best location changes with operating conditions. The framework is therefore suitable for technical-economic screening before detailed stochastic or robust investment optimization. |
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متن کامل [PDF 648 kb]
(8 دریافت)
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نوع مطالعه: پژوهشي |
موضوع مقاله:
عمومى
دریافت: 1405/4/31 | پذیرش: 1405/6/19 | انتشار: 1405/7/3
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