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Decentralized electricity markets are often dominated by a small set ofgenerator companies who control the majority of the capacity. In this paper, weexplore the effect of the total controlled electricity capacity by a single, orgroup, of generator companies can have on the average electricity price. Wedemonstrate this through the use of ElecSim, a simulation of a country-wideenergy market. We develop a strategic agent, representing a generation company,which uses a deep deterministic policy gradient reinforcement learningalgorithm to bid in a uniform pricing electricity market. A uniform pricingmarket is one where all players are paid the highest accepted price. ElecSim isparameterized to the United Kingdom for the year 2018. This work can helpinform policy on how to best regulate a market to ensure that the price ofelectricity remains competitive.  We find that capacity has an impact on the average electricity price in asingle year. If any single generator company, or a collaborating group ofgenerator companies, control more than ${\sim}$11$\%$ of generation capacityand bid strategically, prices begin to increase by ${\sim}$25$\%$. The value of${\sim}$25\% and ${\sim}$11\% may vary between market structures and countries.For instance, different load profiles may favour a particular type of generatoror a different distribution of generation capacity. Once the capacitycontrolled by a generator company, which bids strategically, is higher than${\sim}$35\%, prices increase exponentially. We observe that the use of amarket cap of approximately double the average market price has the effect ofsignificantly decreasing this effect and maintaining a competitive market. Afair and competitive electricity market provides value to consumers and enablesa more competitive economy through the utilisation of electricity by bothindustry and consumers.

Exploring market power using deep reinforcement learning for intelligent bidding strategies