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Energy storage can provide a range of revenue streams for investors in electricity markets. However, as their deployments continue to rise, storage will no longer be a player on the sidelines and remain a price-taker, rather, these assets will start to impact prices. In this study, accounting for energy storage as a price-maker and using data from CAISO, we investigate strategic market behavior among competing investors using a non-cooperative game. We establish a centralized optimization problem to compute the market equilibrium. In the game, each investor initially decides on how much to invest and then how to operate their asset over a time horizon. Investors are allowed to deploy different energy storage technologies. Analytically, we show that an increasing number of investors will increase the market competition thereby reducing profits while increasing the total capacity of storage deployed. Numerically, our key findings include: (a) the difference in optimal investments under price-taker and price-maker assumptions, (b) as wind and solar assets expand under different resource-mix scenarios, there is a corresponding non-monotonic variation in arbitrage potential for energy storage, (c) when competition is intense and investors are allowed to invest in different technologies, a slight increase in storage technology performance can significantly improve an investor's profit share, (d) when the arbitrage opportunity increases with renewables, longer duration storage technologies may gain an advantage, (e) Li-ion batteries dominate the market under low-moderate renewable energy penetration or with steep energy-capacity cost reductions in the future. • We develop a game-theoretical framework for strategic investments in energy storage. • The framework derives a centralized optimization problem to compute the Nash equilibrium. • The impact of energy storage on market price is characterized using CAISO data. • We present insights on arbitrage potential and market competition for energy storage investors. • We quantify the effects of the number of investors, renewable energy levels, and technology heterogeneity. [ABSTRACT FROM AUTHOR]

• A peer-to-peer energy trading market mechanism with shared energy storage units is proposed. • A non-cooperative game among peer-to-peer market participants is presented. • The generalized Nash equilibrium problem among shared energy storage users is depicted. • A game equilibrium solution based on KKT condition is proposed. • Proposed mechanism improves the efficiency and ensures fairness. The high penetration of distributed energy resources with local renewable energy consumption facilitates the emergence of peer-to-peer (P2P) energy trading, where a peer can share excessive energy with local peers. P2P energy trading is expected to be a promising business model in the future transactive energy market. Influenced by the sharing economy principle, shared energy storage(SES) is investigated to reduce the costly initial investment and improve the utilization rate of storage devices. Given the context, this paper proposes an equilibrium model of a P2P energy trading market, considering the deployment of shared energy storage in the residential consumer-side. The market equilibrium problem consists of two interwoven games. Considering the benefit conflicts between energy sellers and buyers in P2P energy trading, the P2P transaction between peers can be described as a non-cooperative game. Considering the limited SES capacity resources, the competition among SES users can be viewed as a generalized Nash equilibrium problem. These two games in the P2P market interact with each other and can be summarized as a holistic equilibrium problem, in which the P2P transaction price is endogenously determined and storage capacity is allocated. The market equilibrium problem can be solved based on Karush-Kuhn-Tucker (KKT) optimality conditions and linearization techniques, finally cast as a mixed-integer linear program. Numerical simulation demonstrates that P2P energy trading benefits all participants and the introduction of shared energy storage can further reduce energy costs. [ABSTRACT FROM AUTHOR]

• Decentralized investments in conventional and renewable capacities are coordinated. • Regulatory targets for adequacy and environmental conditions are promised concurrently. • Cost of designed incentives is reduced considerably compared to models in the literature. • The proposed incentive design model is recast as a mixed-integer linear programming. Environmental concerns and energy security issues have led to the rapid growth of renewable capacities in the power sector. With the increase in the penetration of renewables, conventional generations such as thermal technologies have faced the decreased market prices, reduced volume of sold energies and thus diminished revenues. The decrease in the interests for investment in conventional capacities resulting from revenue deficiency from one side and high penetration of non-dispatchable renewables such as wind and solar generations from the other side may hinder the generation adequacy. So, the investment in conventional and renewable capacities should be done in a coordinated manner to meet both adequacy and environmental goals. Thus, the present study is conducted to present a regulatory tool for coordinated incentive design of investment in conventional and renewable generation capacities considering market equilibria. To this aim, a bi-level model is proposed where in the first level, regulator determines capacity-based and energy-based incentives paid for conventional and renewable generations, respectively, considering targets for adequacy and environmental issues. In the second level, the investment behavior of generation companies in response to investment incentives is anticipated using a game-theoretic model. Our results show that regulatory targets for adequacy and environmental issues are simultaneously realized by the proposed coordinated incentive design. Besides, cost of the designed incentives considerably reduces compared to the recent works. [ABSTRACT FROM AUTHOR]