optimally, under which power plant’s optimal strategy of investing is to purchase USE about 4.5 times much more than SSE.Keywords: electricity supply with uncertainty; electricity investment; electricity pricing; wholesale market; retail market; Stackelberg game Renewable energy, such as wind and solar energy, may vary significantly over time and locations depending on the weather and the climate conditions. This leads to the supply uncertainty in the electricity (power) market with renewable energy integrated to power grid. In this paper, electricity in the market is classified into two types: stable-supply electricity (SSE) and unstable-supply electricity (USE). We investigate the investment and pricing strategies under the electricity supply uncertainty in wholesale and retail electricity market. In particular, our model combines the wholesale and retail market and capture the dominant players, i.e., consumers, power plant (power operator), and electricity supplier. To derive the market behaviors of these players, we formulate the market decision problems as a multistage Stackelberg game. By solving the game model, we obtain the optimal, with closed-form, wholesale investment and retail pricing strategy for the operator. We also obtain the energy supplier’s best price mechanism numerically under certain assumption. We find the price of SSE being about 1.4 times higher than that of USE will benefit energy supplier https://arudhrainnovations.com/
consumers can freely negotiate the purchase and sale of electricity and the electricity prices are purely determined by supply and demand . On the other hand, renewable energy re-sources (RER), such as wind and solar, are very promising to release the dependence on fossil fuels and reduce greenhouse gas emis-sions. For more comprehensive analysis of the changes, we recommend  and ly low fixed costs but high variable costs for burning fossil fuel. Besides, CO2 allowances is also a component of electricity prices . Consequently, nuclear power and hydro ener-gy are usually used to cover the base demand, while thermo energy is used to cover peak de-mand.The operation of electric power systems involves a complicated process of forecasting the demand for electricity, and scheduling and operating a large number of power plants to meet that varying demand. In the last decade, it has become apparent that the wholesale electricity prices fluctuate hour by hour, but the retail prices have been almost fixed and adjusted only very a few times per year. It is supposed to be economically inefficient when retail prices do not reflect wholesale acqui-sition costs. This gives impetus to dynamic retail pricing method considering demand-side participation to reflect the marginal cost of electricity, such as time-of-use (TOU) pric-ing, real-time pricing (RTP). In TOU pricing, both prices and time periods are known ex ante and are fixed for some duration. In RTP, prices change on an hour basis and are fixed and known only on a day-ahead or hour-ahead basis.  presents an overview and analysis of possible approaches to dynamic pricing.  shows enhancing the ability of the demand for electricity to respond to price signals could benefit not only the consumers, but also help market operate more efficiently and satisfacto-rily.  gives a computable equilibrium model to estimate ex ante TOU prices for a retail electricity market. In , it demonstrates that in the long-run the magnitude of efficiency gains from RTP is significant and much higher than TOU pricing.Since the liberalization of electricity mar-ket, the power industry worldwide has expe-rienced big changes. On the one hand, it has been widely recognized that the creation of mechanisms for wholesale and retail electric-ity market to supply consumer energy need is at the core of the changes. For example, since 1990, a large number of electricity exchanges have opened in Europe.
In this paper, the electricity market with sup-ply uncertainty is studied theoretically in a general view. In our market model we assume three players: one electricity supplier, one electricity operator, a collection of consumers. Then we model both the wholesale market and retail market as a two-level Stackelberg game to find the market dynamic behaviors. By backward induction, we fi nd a closed-form solutions for the operator. Our conclusion is that the supply uncertainty in the market are reflected via a lower electricity price to the operator charged for USE. Furthermore, under some additional assumption on the wholesale price of USE, we find an optimal numerical solution for supplier, where the price of SSEbeing about 1.4 times higher than that of USE will benefit energy supplier optimally, and power plant’s optimal strategy of investing is to purchase USE about 4.5 times much more than SSE.