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Trade-off both in the clearing market and ancillary services markets for agriculture park operator: A strategic bilevel multi-objective programming

Future agriculture is poised to shift towards smarter, more sustainable production modes. This innovation are performed as the integration of greenhouse with photovoltaic energy storage systems (PESS). Agricultural park operators (APOs) may efficiently leverage solar energy to enhance both crop growth and overall energy management. Thus, APOs transform into prosumers via the deployment and management of PESS. Beyond benefits known to all, this transition presents a trade-off for APOs: 1) Using energy storage to save more solar energy, thereby extending growth time per day for crops utilize stored power. 2) Lease the energy storage to utilities for additional revenue or offset part of the electricity bill. In response to this future practical and meaningful challenge, this paper develops a bi-level optimization model of strategic decision-making and designs energy management for operators. The upper level highlighted maximizing profits of efficient and daily management for agricultural park. The upper level comprises two parts: (i) Maximizing profits in the ancillary services market and (ii) Minimizing the cost of electricity procurement. The bi-level model is reformulated as a mathematical program with equilibrium constraints (MPEC) problem via the Karush-Kuhn-Tucker (KKT) method. Simulations indicate that deploying photovoltaic and battery systems may reduce costs of electricity procurement and crop growth cycles, increase net profit up to 33 %. Additionally, crop prices and ancillary service prices significantly influence strategy options.
Distributed control, Boosting mode, Bilevel model, Agriculture park microgrid, MPEC model, Energy management system, Market clearing
Distributed control, Boosting mode, Bilevel model, Agriculture park microgrid, MPEC model, Energy management system, Market clearing
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