Solar Deployment System (SolarDS) Model: Documentation and Sample Results

Denholm, P. ; Drury, E. ; Margolis, R.

关键词: CAPACITY;    CAPITALIZED COST;    CARBON;    COMPETITION;    DOCUMENTATION;    ELECTRICITY;    FINANCING;    MARKET;    PERFORMANCE;    PRICES SOLARDS;    PHOTOVOLTAICS;    PV;    PV CAPACITY;    PV SYSTEMS;    SOLAR DEPLOYMENT SYSTEM;    MODEL RESULTS;    MARKET MODEL;    MARKET PENETRATION;    MARKET COMPETITIVENESS;    REGIONAL SOLAR RESOURCES;    SOLAR CAPITAL COSTS;    ELECTRICITY PRICES;    UTILITY RATE STRUCTURES;    FEDERAL INCENTIVES;    LOCAL INCENTIVES;    ANNUAL REVENUE;    FINANCIAL PERFORMANCE CALCULATOR;    Energy Analysis;   

DOI  :  10.2172/967192
RP-ID  :  NREL/TP-6A2-45832
PID  :  OSTI ID: 967192
Others  :  TRN: US200923%%513

学科分类：再生能源与代替技术

美国|英语

来源: SciTech Connect

【 摘 要 】

The Solar Deployment System (SolarDS) model is a bottom-up, market penetration model that simulates the potential adoption of photovoltaics (PV) on residential and commercial rooftops in the continental United States through 2030. NREL developed SolarDS to examine the market competitiveness of PV based on regional solar resources, capital costs, electricity prices, utility rate structures, and federal and local incentives. The model uses the projected financial performance of PV systems to simulate PV adoption for building types and regions then aggregates adoption to state and national levels. The main components of SolarDS include a PV performance simulator, a PV annual revenue calculator, a PV financial performance calculator, a PV market share calculator, and a regional aggregator. The model simulates a variety of installed PV capacity for a range of user-specified input parameters. PV market penetration levels from 15 to 193 GW by 2030 were simulated in preliminary model runs. SolarDS results are primarily driven by three model assumptions: (1) future PV cost reductions, (2) the maximum PV market share assumed for systems with given financial performance, and (3) PV financing parameters and policy-driven assumptions, such as the possible future cost of carbon emissions.