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This study presents a scenario-based model predictive control (MPC) approach to minimize the cotton farm microgrid operational cost under uncertainties. Uncertainties in cotton farms may come from renewable energy generation, water demand, precipitation, and evaporation, so the cotton field pumping system operation can be formulated as a stochastic MPC problem to accommodate uncertain climate conditions and real-time changes in irrigation demand. Scenario generation and reduction techniques can obtain typical scenarios and their probabilities. The typical scenarios can be used in the MPC iterative step to facilitate modelling the proposed stochastic optimization problem. This study discusses static and dynamic uncertainty modelling techniques used for MPC, and each technique is analysed separately in grid-connected and islanded microgrids through case studies. In the grid-connected dynamic scenario-based MPC, the operational cost is AU$ 18,797 over the entire irrigation period, which is AU$ 8759 lower than that of the standard MPC. Furthermore, for the islanded dynamic scenario-based MPC, the operational cost is AU$ 24,443 over the entire irrigation period, which is AU$ 6721 lower than the standard MPC.

This study presents a scenario-based model predictive control (MPC) approach to minimize the cotton farm microgrid operational cost under uncertainties. Uncertainties in cotton farms may come from renewable energy generation, water demand, precipitation, and evaporation, so the cotton field pumping system operation can be formulated as a stochastic MPC problem to accommodate uncertain climate conditions and real-time changes in irrigation demand. Scenario generation and reduction techniques can obtain typical scenarios and their probabilities. The typical scenarios can be used in the MPC iterative step to facilitate modelling the proposed stochastic optimization problem. This study discusses static and dynamic uncertainty modelling techniques used for MPC, and each technique is analysed separately in grid-connected and islanded microgrids through case studies. In the grid-connected dynamic scenario-based MPC, the operational cost is AU$ 18,797 over the entire irrigation period, which is AU$ 8759 lower than that of the standard MPC. Furthermore, for the islanded dynamic scenario-based MPC, the operational cost is AU$ 24,443 over the entire irrigation period, which is AU$ 6721 lower than the standard MPC. • A model predictive control under uncertainties is proposed for a microgrid. • The static and dynamic scenario-based approach is used to model the uncertainties. • Case studies using a cotton farm microgrid are analysed to validate the method. [ABSTRACT FROM AUTHOR]

This paper aims to address the issue of income distribution among farm households growing cotton under the irrigated conditions of the Harran Plain located in the Sanliurfa Province. Comparing the results from ex-ante and ex-post distributional analyses, it is possible to determine the socio-economic impacts of the South Eastern Anatolia (GAP) Project on the well-being of these local cotton farmers. Results show that although in absolute terms the provision of Harran Plain irrigation projects has increased income of local cotton farmers, Gini ratio of 0.49 indicates that there has been uneven income distribution in the Harran Plain’s cotton sector. The most important factor affecting income distribution is determined to be how well or poor land under cotton is distributed among these local farmers.

This paper aims to address the issue of income distribution among farm households growing cotton under the irrigated conditions of the Harran Plain located in the Sanliurfa Province. Comparing the results from ex-ante and ex-post distributional analyses, it is possible to determine the socio-economic impacts of the South Eastern Anatolia (GAP) Project on the well-being of these local cotton farmers. Results show that although in absolute terms the provision of Harran Plain irrigation projects has increased income of local cotton farmers, Gini ratio of 0.49 indicates that there has been uneven income distribution in the Harran Plain's cotton sector. The most important factor affecting income distribution is determined to be how well or poor land under cotton is distributed among these local farmers. [ABSTRACT FROM AUTHOR]