15,869 research outputs found
Storage Sizing and Placement through Operational and Uncertainty-Aware Simulations
As the penetration level of transmission-scale time-intermittent renewable
generation resources increases, control of flexible resources will become
important to mitigating the fluctuations due to these new renewable resources.
Flexible resources may include new or existing synchronous generators as well
as new energy storage devices. Optimal placement and sizing of energy storage
to minimize costs of integrating renewable resources is a difficult
optimization problem. Further,optimal planning procedures typically do not
consider the effect of the time dependence of operations and may lead to
unsatisfactory results. Here, we use an optimal energy storage control
algorithm to develop a heuristic procedure for energy storage placement and
sizing. We perform operational simulation under various time profiles of
intermittent generation, loads and interchanges (artificially generated or from
historical data) and accumulate statistics of the usage of storage at each node
under the optimal dispatch. We develop a greedy heuristic based on the
accumulated statistics to obtain a minimal set of nodes for storage placement.
The quality of the heuristic is explored by comparing our results to the
obvious heuristic of placing storage at the renewables for IEEE benchmarks and
real-world network topologies.Comment: To Appear in proceedings of Hawaii International Conference on System
Sciences (HICSS-2014
Robust Optimal Power Flow with Wind Integration Using Conditional Value-at-Risk
Integrating renewable energy into the power grid requires intelligent
risk-aware dispatch accounting for the stochastic availability of renewables.
Toward achieving this goal, a robust DC optimal flow problem is developed in
the present paper for power systems with a high penetration of wind energy. The
optimal dispatch is obtained as the solution to a convex program with a
suitable regularizer, which is able to mitigate the potentially high risk of
inadequate wind power. The regularizer is constructed based on the energy
transaction cost using conditional value-at-risk (CVaR). Bypassing the
prohibitive high-dimensional integral, the distribution-free sample average
approximation method is efficiently utilized for solving the resulting
optimization problem. Case studies are reported to corroborate the efficacy of
the novel model and approach tested on the IEEE 30-bus benchmark system with
real operation data from seven wind farms.Comment: To Appear in Proc. of the 4th Intl. Conf. on Smart Grid
Communication
Optimization of the operation of smart rural grids through a novel rnergy management system
The paper proposes an innovative Energy Management System (EMS) that optimizes the grid operation based on economic and technical criteria. The EMS inputs the demand and renewable generation forecasts, electricity prices and the status of the distributed storages through the network, and solves with an optimal quarter-hourly dispatch for controllable resources. The performance of the EMS is quantified through diverse proposed metrics. The analyses were based on a real rural grid from the European FP7 project Smart Rural Grid. The performance of the EMS has been evaluated through some scenarios varying the penetration of distributed generation. The obtained results demonstrate that the inclusion of the EMS from both a technical point of view and an economic perspective for the adopted grid is justified. At the technical level, the inclusion of the EMS permits us to significantly increase the power quality in weak and radial networks. At the economic level and from a certain threshold value in renewables’ penetration, the EMS reduces the energy costs for the grid participants, minimizing imports from the external grid and compensating the toll to be paid in the form of the losses incurred by including additional equipment in the network (i.e., distributed storage).Postprint (published version
Risk-Aware Management of Distributed Energy Resources
High wind energy penetration critically challenges the economic dispatch of
current and future power systems. Supply and demand must be balanced at every
bus of the grid, while respecting transmission line ratings and accounting for
the stochastic nature of renewable energy sources. Aligned to that goal, a
network-constrained economic dispatch is developed in this paper. To account
for the uncertainty of renewable energy forecasts, wind farm schedules are
determined so that they can be delivered over the transmission network with a
prescribed probability. Given that the distribution of wind power forecasts is
rarely known, and/or uncertainties may yield non-convex feasible sets for the
power schedules, a scenario approximation technique using Monte Carlo sampling
is pursued. Upon utilizing the structure of the DC optimal power flow (OPF), a
distribution-free convex problem formulation is derived whose complexity scales
well with the wind forecast sample size. The efficacy of this novel approach is
evaluated over the IEEE 30-bus power grid benchmark after including real
operation data from seven wind farms.Comment: To appear in Proc. of 18th Intl. Conf. on DSP, Santorini Island,
Greece, July 1-3, 201
Economic Sizing of Distributed Energy Resources for Reliable Community Microgrids
Community microgrids offer many advantages for power distribution systems.
When there is an extreme event happening, distribution systems can be
seamlessly partitioned into several community microgrids for uninterrupted
supply to the end-users. In order to guarantee the system reliability,
distributed energy resources (DERs) should be sized for ensuring generation
adequacy to cover unexpected events. This paper presents a comprehensive
methodology for DERs selection in community microgrids, and an economic
approach to meet the system reliability requirements. Algorithms of discrete
time Fourier transform (DTFT) and particle swarm optimization (PSO) are
employed to find the optimal solution. Uncertainties of load demand and
renewable generation are taken into consideration. As part of the case study, a
sensitivity analysis is carried out to show the renewable generation impact on
DERs' capacity planning.Comment: 5 pages, 6 figures, 1 table, 2017 IEEE Power & Energy Society General
Meeting. arXiv admin note: substantial text overlap with arXiv:1708.0102
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