Multi Reservoir Water Price and Allocation Model
Rispiningtati1, Rudy Soenoko2
1Rispiningtati*, Water Resources Engineering Department, Engineering Faculty, Brawijaya University, Malang, Indonesia.
2Rudy Soenoko, Mechanical Engineering Department, Engineering Faculty, Brawijaya University, Malang, Indonesia.
Manuscript received on October 18, 2019. | Revised Manuscript received on 27 October, 2019. | Manuscript published on November 10, 2019. | PP: 2220-2227 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4789119119/2019©BEIESP | DOI: 10.35940/ijitee.A4789.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Many water planning, researches have been done but water pricing has not been considered as the prime factor. Cost allocation is required whenever a project deals with multi-purpose groups. An optimization model which is accommodating the water allocation and water price must be developed in Indonesia. The new linear optimization model is developed to present a method for the determination of equitable impact fees and optimal water allocation for single reservoir. The proposed method is demonstrated on a river system with 4 major reservoirs. Each reservoir system serves 5 uses (irrigation, hydroelectric and flood control, industrial and domestic need). Using optimization with the cost of the reservoir and its facilities as targets and the objective function is maximization of total net benefit of user income, water allocation as x variable and water price as the y variable will produce the optimal result. The result is the optimal water allocation with a minimal water price which is present on 3 simulation analysis. The result of the model is in a graphic and table presentation, which can be used easily to determine the water allocation and water price per m3 in all reservoir systems.
Keywords: Allocation, Model, Optimization, Water Price.
Scope of the Article: Discrete Optimization