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Distributed transmission-scale energy storage is becoming economically feasible due to the growing share of renewable generation and cost reduction of specific storage technologies, primarily batteries. Under these circumstances, independent merchants may start investing in storage facilities. On the other hand, system operators, besides investing in transmission lines, may, under certain conditions, invest in storage units as well. This paper formulates a trilevel model where the upper-level problem optimizes the system operator's transmission line and energy storage investments, the middle-level problem determines merchant energy storage investment decisions, while the lower level problem simulates market clearing process for representative days. After replacing the lower level problem with its primal dual equivalent conditions, the middle- and lower level problems are merged into a mixed-integer problem with equilibrium constraints. The resulting bilevel structure is iteratively solved using a cutting plane algorithm. The proposed formulation is first applied to a six-bus system to present the mechanics of the model and then to the IEEE RTS-96 test system. The results show that even at the low cost of energy storage, the system operator (SO) still prefers line investments, while merchant investments are driven by the volatility of LMPs. Both the SO and merchant investments increase the social welfare, although this increase is mostly driven by the SO investments. [ABSTRACT FROM AUTHOR]

Massive integration of renewable energy resources calls for new operating and planning paradigms, which address reduced controllability and increased uncertainty on the generation side. On the other hand, emerging energy storage technologies can provide additional flexibility. Therefore, generation and storage expansion models need to be coordinated to ensure sufficiency of system-wide response capabilities within different regulation intervals. This paper proposes a coordinated generation and storage expansion formulation considering primary frequency response constraints. This is a stochastic mixed-integer linear program solved using an off-the-shelf solver. The proposed formulation is compared to the case when primary frequency response is neglected. The case study performed for an eight-zone ISO New England test system quantifies the value of energy storage simultaneously providing primary frequency response and spatio-temporal arbitrage. [ABSTRACT FROM AUTHOR]

Preventive security-constrained optimal power flow (PSCOPF) dispatches controllable generators at minimum cost while ensuring that the system adheres to all operating constraints. All the transmission and generation limits are respected during both the pre- and post-contingency states without relying on post-contingency redispatch. Therefore, all credible generation contingencies should be modeled in PSCOPF and the system-wide automatic primary response should be allocated accordingly among synchronized generators by adjusting their droop coefficients. This paper proposes a new PSCOPF model that optimizes the droop coefficients of the synchronized generators. The cost savings attained with the proposed approach and its computational performance are evaluated. Different wind penetration levels and reserve policies are tested using annual simulations on the one- and three-area IEEE Reliability Test System. [ABSTRACT FROM PUBLISHER]

Suitably located energy storage systems are able to collect significant revenue through spatiotemporal arbitrage in congested transmission networks. However, transmission capacity expansion can significantly reduce or eliminate this source of revenue. Investment decisions by merchant storage operators must, therefore, account for the consequences of potential investments in transmission capacity by central planners. This paper presents a tri-level model to co-optimize merchant electrochemical storage siting and sizing with centralized transmission expansion planning. The upper level takes the merchant storage owner's perspective and aims to maximize the lifetime profits of the storage, while ensuring a given rate of return on investments. The middle level optimizes centralized decisions about transmission expansion. The lower level simulates market clearing. The proposed model is recast as a bi-level equivalent, which is solved using the column-and-constraint generation technique. A case study based on a 240-bus, 448-line testbed of the Western Electricity Coordinating Council interconnection demonstrates the usefulness of the proposed tri-level model. [ABSTRACT FROM PUBLISHER]

Energy storage (ES) is a pivotal technology for dealing with the challenges caused by the integration of renewable energy sources. It is expected that a decrease in the capital cost of storage will eventually spur the deployment of large amounts of ES. These devices will provide transmission services, such as spatiotemporal energy arbitrage, i.e., storing surplus energy from intermittent renewable sources for later use by loads while reducing the congestion in the transmission network. This paper proposes a bilevel program that determines the optimal location and size of storage devices to perform this spatiotemporal energy arbitrage. This method aims to simultaneously reduce the system-wide operating cost and the cost of investments in ES while ensuring that merchant storage devices collect sufficient profits to fully recover their investment cost. The usefulness of the proposed method is illustrated using a representative case study of the ISO New England system with a prospective wind generation portfolio. [ABSTRACT FROM AUTHOR]

This paper considers the yearly maintenance scheduling of generating units within a market environment. Each producer schedules its units' maintenance periods to maximize its revenue using a bilevel approach. The upper-level problem of this bilevel model seeks maximum revenue and contains unit scheduling constraints, while the lower-level problems represent the market clearing process under different operating conditions. This single producer maintenance problem can be recast as a mathematical program with equilibrium constraints (MPEC). Since the MPECs of all producers have to be considered simultaneously and the market clearing process is common to all of them, the proposed formulation for maintenance scheduling is an equilibrium problem with equilibrium constraints (EPEC) corresponding to a multiple-leader-common-follower game. The solution of this EPEC is a set of equilibria, in which none of the producers is able to increase its revenue unilaterally by changing the maintenance periods of its generating units. [ABSTRACT FROM PUBLISHER]

Within a yearly horizon, a transmission system operator needs to schedule the maintenance outages of the set of transmission lines due for maintenance. Facing this task, two conflicting objectives arise: on one hand, the transmission system adequacy should be preserved as much as possible, and, on the other hand, market operation should be altered in the least possible manner. To address this scheduling problem, a bilevel model is proposed whose upper-level problem schedules line maintenance outages pursuing maximum transmission capacity margin. This upper-level problem is constrained by a set of lower-level problems that represent the clearing of the market for all the time periods considered within the yearly planning horizon. This bilevel model is conveniently converted into a nonlinear mathematical program with equilibrium constraints (MPEC) that can be recast as a mixed-integer linear programming problem solvable with currently available branch-and-cut techniques. [ABSTRACT FROM PUBLISHER]