In this paper, we have investigated minimization of total cost to pump a given flow rate from any number (n) of wells up to a water tank, under steady-state flow conditions. Regarding groundwater flow, we have considered infinite or semi-infinite aquifers, to which the method of images applies. Additional regional groundwater flow can be taken into account, too. The pipe network connecting the wells to the tank can include junctions at the locations of the wells only. Moreover, all pumps have equal efficiency. We have derived a new analytical formula, which holds at the critical points of the total cost function. Based on this formula, we derived a system of n equations and n unknowns, to calculate the well flow rate combinations which correspond to the critical points of the total cost function. The n-1 equations are 2nd degree polynomials, while the remaining one is linear, expressing the constraint that the sum of well flow rates must be equal the required total flow rate. The solution of the system can be achieved using commercial solvers. Moreover, we have concluded that there is one feasible solution that minimizes the total cost. Finally, we present a tabulation process to facilitate the use of solvers and we provide and discuss two illustrative examples.

This paper deals with water pumping cost minimization, in a confined infinite aquifer, proposing an alternate pulsed pumping schedule. The transient flow analysis is conducted for two wells with equal pumping rates. Specifically, two pumping schedules are analytically compared. In the first case, well users pump simultaneously, and in the second one they cooperate so that they pump alternately. This paper proves that the proposed alternate pumping schedule works as a stabilizer, reducing the high hydraulic drawdowns values, regardless of the aquifer characteristics. Moreover, pumping alternately is better in terms of pumping cost, compared to simultaneous pumping, though benefit become negligible as distance between wells becomes large. Two simplified equations are proposed, one to find the difference of the hydraulic drawdowns between the two pumping schedules and the other one to find the economic benefit of each well from cooperation. The equations are finally applied to a number of cases and their results are compared to the results obtained from an algorithm created to calculate the hydraulic drawdowns and the pumping cost, using the Theis equation. The results can be very useful in irrigation scheduling, as they can be applied to systems of well users/farmers, to reduce pumping cost.

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Minimization of groundwater exploitation cost is examined, considering: (a) Pumping from a system of wells up to a central water tank, including friction losses along the connecting pipe network and (b) amortization of network construction. Assuming that the wells are located symmetrically around the tank and directly connected to it, we derived analytically the distance between tank and wells, which minimizes the total cost. Then we compared the minimum cost of this well layout, with that of placing one well at the location of the tank and the rest symmetrically around it. Finally, we dropped any assumption on well layout, we considered that wells are connected to the tank using a minimum spanning tree and we optimized well locations and flow rates using genetic algorithms. For up to 8 wells, the resulting minimum cost is comparable to that of the symmetrical cases, even when the optimal well layout is quite different. Moreover, the analytical solution, derived for the symmetrical case, can serve to evaluate solutions achieved by sophisticated optimization techniques.

In this paper, an integrated methodology is developed to determine optimum areas for Photovoltaic (PV) installations that minimize the relevant visual disturbance and satisfy spatial constraints associated with land use, as well as environmental and techno-economic siting factors. The visual disturbance due to PV installations is quantified by introducing and calculating the “Social Disturbance” (SDIS) indicator, whereas optimum locations are determined for predefined values of two siting preferences (maximum allowable PV locations—grid station distance and minimum allowable total coverage area of PV installations). Thematic maps of appropriate selected exclusion criteria are produced, followed by a cumulative weighted viewshed analysis, where the SDIS indicator is calculated. Optimum solutions are then determined by developing and employing a Genetic Algorithms (GAs) optimization process. The methodology is applied for the municipality of La Palma Del Condado in Spain for 100 different combinations of the two siting preferences. The optimization results are also employed to create a flexible and easy-to-use web-GIS application, facilitating policy-makers to choose the set of solutions that better fulfils their preferences. The GAs algorithm offers the ability to determine distinguishable, but compact, regions of optimum locations in the region, whereas the results indicate the strong dependence of the optimum areas upon the two siting preferences.