Showing papers on "Grid parity published in 1983"
TL;DR: In this article, a simple but powerful numerical generation planning model has been constructed for grids containing wind farms and three classes of thermal power station, but no storage, and the breakeven costs of wind energy in a model British CEGB grid, containing coal, nuclear, oil and wind driven power plant, are evaluated under various conditions.
21 citations
TL;DR: In this article, the status of flat-plate photovoltaic (PV) system technology, performance and cost for applications in developing countries were discussed and a comparison of key electrical service performance factors is made between PV and conventional generating systems.
7 citations
01 Jan 1983
TL;DR: In this article, the authors present two quantitative scenarios for balancing global energy supply with demand for the period 1980-2030, showing that during these 50 years there will be a persistent demand worldwide for liquid fuels, a continuing reliance on ever more expensive and dirty fossil fuels, and a limited penetration rate of nuclear generated electricity into the energy market.
Abstract: The results of two quantitative scenarios balancing global energy supply with demand for the period 1980–2030 are reviewed briefly. The results suggest that during these 50 years there will be a persistent demand worldwide for liquid fuels, a continuing reliance on ever more expensive and “dirty” fossil fuels, and a limited penetration rate of nuclear generated electricity into the energy market. The paper therefore addresses a possible “second” grid driven by nuclear heat — a grid based not on electricity but on “clean” liquid fuels manufactured from gaseous and solid fossil fuels using nuclear power. Such a second grid would be an important complement to the electricity grid if the world is to progress towards a truly sustainable energy system after 2030.
4 citations
Book•
02 Mar 1983
1 citations
TL;DR: In this article, the authors report on a study to simulate a typical solar installation and determine the probability that back-up power will be needed at the time the utility experiences its peak load.