Optimal Site Selection of Wind-Solar Complementary Power Generation Project for a Large-Scale Plug-In Charging Station

Abstract

Abstract:The wind-solar hybrid power generation project combined with electric vehicle charging stations can effectively reduce the impact on the power system caused by the random charging of electric cars, contribute to the in-situ wind-solar complementary system and reduce the harm arising from its output volatility. In this paper, the site selection index system of a landscape complementary power generation project is established by using the statistical methods and statistical analysis in the literature. Subsequently, using the Analytic Network Process to calculate the index weight, a cloud model was used in combination with preference ranking organization method for enrichment evaluations to transform and sort uncertain language information. Finally, using the results of the decision-making for the location of the Shanghai wind-solar complementary project and by carrying out contrast analysis and sensitivity analysis, the superiority and stability of the decision model constructed in this study was demonstrated.

A Hybrid Multiple Criteria Decision Making Model for Selecting the Location of Women’s Fitness Centers

“…Aksoy and Yetkin Ozbuk [16] employed the preference selection index (PSI) to rank hotels by location. Chen et al [17] used the preference ranking organization method for enrichment evaluations (PROMETHEE) based on the cloud model and AHP to select location for a large charging power station. Komchornrit [18] used the confirmatory factor analysis (CFA), the measuring attractiveness by a categorical based evaluation technique (MAC-BETH), and PROMETHEE to select a dry port location.…”

Integración del recurso eólico marino en los sectores del transporte y climatización: estudio de transición energética en la costa Este de EEUU

“…El promedio ponderado global del LCOE para la energía eólica marina en el 2018 fue de 0.126 USD/kWh, comparado con el 2010 resulta un decremento del 20 %. Factor Referencias % Velocidad del viento (F 1,1 ) [199,226,50,139,223,167,231,104,102,207,251,211,49,227,239,152,186,112,208,209,70,206,235,53,145,161,84,51,240,79,220,41] 94 [187,237,45,67,244,69,91,248,148,149,74,232,196,250,103,172,230,…”

“…Referencias % Precio de venta de energía (F 5,1 ) [199,104,211,70] 12 [248,196,212,37,171,113,216,210]…”

“…Generación de energía (F 5,2 ) [199,226,167,104,211,251,49,70,240] 26 [67,69,91,248,148,196,212,113,217,216,210] 27 CAPEX (F 5,3 ) [199,104,211,251,70,161,203,220] 24 [67,69,91,248,148,196,250,172,175,176,193…”

“…Interés de prestamos (F 5,7 ) [104,251] 6 [67,244,69,196,250,172,175,176,169,147,193 Medidas políticas (F 6,3 ) [251,70,220] 9 [91] 2…”