Is Green Healthy for Competition? Renewable Technologies, Optimal Generation Mix and Price Volatility in Competitive Electricity Markets

Professor Asher Tishler, Faculty of Management, Tel Aviv University

This paper presents a two-stage decision model with endogenous capacity and operations to assess the effect of renewable technologies on generation capacity and mix, on the optimal electricity price and on price volatility. This model is timely since the recent deterioration of the environment will certainly be one of the most important policy issues of the next decade, enhancing the development and use of renewable technologies.

We consider two types of generating technologies: (1) ‘regular’, fossil-using, technologies such as combined cycle gas turbines and, (2) weather-dependent renewable technologies (photovoltaic cells, say). In the first stage of the model (game), when only the probability distribution functions of future daily electricity demands and weather conditions are known, profit-seeking producers maximize their expected profits by determining the capacity to be constructed from each technology. In the second stage, once daily demands and weather conditions become known, each producer selects the daily production levels of each technology subject to its capacity availability (available capacity of the renewable technology depends on capacity construction in the first stage of the game, and on the weather).

We show that the endogenously determined optimal generation capacity is higher and price spikes are substantially higher and more frequent in the presence of renewable technologies than in their absence (when only fossil-fired technologies are employed). We also show that the average electricity price is likely to increase when construction costs of PV capacity decline (due, say, to technology improvements), that market structure has large effects on capacity mix and price volatility, that the increase in PV capacity is fairly limited in the near future and that CO2 tax will likely have only a minor effect on PV capacity. We demonstrate these results by applying the model to real world data.

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