The global energy transition toward a carbon-neutral future relies on the large-scale integration of renewables and electrification in transportation, civil infrastructure, and industrial manufacturing sectors. This dissertation addresses three challenges in power systems and electricity markets mechanism designs for the energy transition: (i) the integration of storage resources with distinct cost structures (e.g., battery lifetime degradation cost and opportunity cost); (ii) pricing real-time operation with high penetration of stochastic renewables; (iii) the aggregation of small but vast distributed energy resources (e.g., rooftop solar and electric vehicles) to participate in the wholesale electricity market. First, for the utility-scale storage integrated into power systems, we consider the problem of co-optimized energy-reserve market clearing with state-of-charge (SoC) dependent bids from battery storage participants. While SoC-dependent bidding accurately captures storage’s degradation and opportunity costs, such bids result in a non-convex optimization in the electricity market clearing process. More challenging is the regulation reserve capacity clearing, where the SoC-dependent cost is uncertain as it depends on the unknown regulation trajectories ex-post of the market clearing. Addressing the nonconvexity and uncertainty in a multi-interval co-optimized real-time energy-reserve market, we introduce a simple restriction on the SoC-dependent bids along with a robust optimization formulation, transforming the non-convex market clearing under uncertainty into a standard convex piece-wise linear program and making it possible for large-scale storage integration. Under reasonable assumptions, we show that SoC-dependent bids yield higher profits for storage participants than SoC-independent bids. Numerical simulations demonstrate a 28%-150% profit increase of the proposed SoC-dependent bids compared with the SoC-independent counterpart. Second, we focus on the pricing mechanism in the real-time electricity market under demand and generation stochasticities. A scenario-based stochastic rolling-window dispatch model is formulated for the real-time market, consisting of conventional generators, utility-scale storage, and distributed energy resource aggregators. We show that uniform pricing mechanisms require discriminative out-of-the-market uplifts, making settlements under locational marginal pricing (LMP) discriminative. It is also shown that the temporal locational marginal pricing (TLMP) that adds nonuniform shadow prices of ramping and SoC to LMP removes the need for out-of-the-market uplifts. Truthful bidding incentives are also established for price-taking participants under TLMP. Revenue adequacy and uplifts are evaluated in numerical simulations. Third, for the large-scale distributed energy resources (DERs) integration, we consider a profit-seeking DER aggregator (DERA) participating directly in the wholesale electricity market. DERAs must acquire distribution network access from the distribution utility in order to participate in the wholesale electricity markets. We propose a forward auction that a distribution system operator (DSO) can utilize to allocate distribution network access limits to DERAs. As long as the DERAs operate within their acquired limits, these limits define operating envelopes that guarantee distribution network security, thus defining a mechanism without real-time interventions from the DSOs for DERAs to participate in the wholesale market. Finally, we propose a competitive DER aggregation mechanism that maximizes the DERA’s profit subject to that each customer of the DERA gains no less surplus and pays no higher energy cost than those under the regulated retail tariff. The DERA participates in the wholesale electricity market as virtual storage with optimized generation offers and consumption bids derived from the DERA’s competitive aggregation. Also derived are DERA’s bid curves for the distribution network access. We show that, with sufficiently high network access, the proposed DERA’s wholesale market participation achieves the same welfare-maximizing outcome as when its customers participate directly in the wholesale electricity market.