Search Results (2)

This paper proposes an optimal solution for the design of a hybrid power system that will supply a remote fishpond in eastern Serbia. In terms of structure, this off-grid system should be a hydro-photovoltaic-diesel-converter-battery setup. The optimization objectives are to minimize total net present cost (NPC) and greenhouse gas (GHG) emissions and to maximize total annual electricity generation based on the modification of hydro-turbine performance. This study considers the following three cases of a hydro-turbine with fixed propeller blades: having fixed guide vanes, for the annual average flow rate-Case 1; having adjustable guide vanes, for smaller flow rates-Case 2 and having adjustable guide vanes, for higher flow rates-Case 3. The optimization is performed using HOMER Pro v. 3.16.2 software. The results show that the total NPC, levelized cost of energy (COE) and GHG emissions in Case 3 are 16.6%, 16.8% and 13.1% lower than in Case 1, and 8.1%, 8% and 11.7% lower than in Case 2, respectively. It is also found that the total annual electricity generation and power output from the entire system in Case 3 are 33.3% and 1.2% higher than in Case 1, and 11.9% higher and not different than in Case 2, respectively. Full article

Micro Hydro Power Plants (MHPP) constitute an effective, environmentally-friendly solution to deal with energy poverty in rural isolated areas, being the most extended renewable technology in this field. Nevertheless, the context of poverty and lack of qualified manpower usually lead to a poor usage of the resources, due to the use of thumb rules and user experience to design the layout of the plants, which conditions the performance. For this reason, the development of robust and efficient optimization strategies are particularly relevant in this field. This paper proposes a Genetic Algorithm (GA) to address the problem of finding the optimal layout for an MHPP based on real scenario data, obtained by means of a set of experimental topographic measurements. With this end in view, a model of the plant is first developed, in terms of which the optimization problem is formulated with the constraints of minimal generated power and maximum use of flow, together with the practical feasibility of the layout to the measured terrain. The problem is formulated in both single-objective (minimization of the cost) and multi-objective (minimization of the cost and maximization of the generated power) modes, the Pareto dominance being studied in this last case. The algorithm is first applied to an example scenario to illustrate its performance and compared with a reference Branch and Bound Algorithm (BBA) linear approach, reaching reductions of more than 70% in the cost of the MHPP. Finally, it is also applied to a real set of geographical data to validate its robustness against irregular, poorly sampled domains. Full article