TY - GEN
T1 - Storage sizing and placement through operational and uncertainty-aware simulations
AU - Dvijotham, Krishnamurthy
AU - Chertkov, Misha
AU - Backhaus, Scott
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Energy storage
KW - Power system control
KW - Power system planning
UR - http://www.scopus.com/inward/record.url?scp=84902290889&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84902290889&partnerID=8YFLogxK
U2 - 10.1109/HICSS.2014.302
DO - 10.1109/HICSS.2014.302
M3 - Conference contribution
AN - SCOPUS:84902290889
SN - 9781479925049
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 2408
EP - 2416
BT - Proceedings of the 47th Annual Hawaii International Conference on System Sciences, HICSS 2014
PB - IEEE Computer Society
T2 - 47th Hawaii International Conference on System Sciences, HICSS 2014
Y2 - 6 January 2014 through 9 January 2014
ER -