
doi: 10.1049/rpg2.12186
Abstract In co‐expansion planning of generation and storage systems, the investor aims to determine the time, location, and capacity of the generation energy storage units. The main challenge is to install these systems in a way that the investor's profit is maximized. In addition, market‐clearing must take place in order to optimize social welfare. This paper studies a co‐expansion planning problem as a bi‐level model that involves the expansion of generation and energy storage units. Generating units include wind and gas turbines and the energy storage system (ESS) is compressed air. This paper addresses the upper‐level problem of increasing investor profits and the lower‐level problem of increasing social welfare. Simulation results show that an investor can achieve the highest possible profit by simultaneously investing in the wind and gas turbine as well as the storage systems using strategic behaviour (price offer/bid close to market price) and participating in the spot market and guaranteed purchase contract. In addition, improving the load growth rate and guaranteed purchase contracts increase the investment in the generation‐storage units. The simulation results of this study are compared with other studies for validation purposes.
Gas‐turbine power stations and plants, Power system planning and layout, Wind power plants, Optimisation techniques, TJ807-830, Power system management, operation and economics, Other energy storage, Renewable energy sources
Gas‐turbine power stations and plants, Power system planning and layout, Wind power plants, Optimisation techniques, TJ807-830, Power system management, operation and economics, Other energy storage, Renewable energy sources
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
