Estimating the Active and Reactive Power Flexibility Area at the TSO-DSO Interface

The penetration of distributed renewable energy sources in the distribution grid is increasing considerably in the last years. This is one of the main causes that contributed to the growth of technical problems in both transmission and distribution systems. An effective solution to improve system security is to exploit the flexibility that can be provided by distributed energy resources (DER), which are mostly located at the distribution grids. Their location combined with the lack of power flow coordination at the system operators interface creates difficulties in taking advantage of these flexible resources. This paper presents a methodology based on the solution of a set of optimization problems that estimate the flexibility ranges at the distribution and transmission system operators (TSO-DSO) boundary nodes. The estimation is performed while considering the grid technical constraints and a maximum cost that the user is willing to pay. The novelty behind this approach comes from the development of flexibility cost maps, which allow the visualization of the impact of DER flexibility on the operating point at the TSO-DSO interface. The results are compared with a sampling method and suggest that a higher accuracy in the TSO-DSO information exchange process can be achieved through this approach.

[1]  Jinye Zhao,et al.  A Unified Framework for Defining and Measuring Flexibility in Power System , 2016, IEEE Transactions on Power Systems.

[2]  D. Ernst,et al.  Agent-based analysis of dynamic access ranges to the distribution network , 2016, 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe).

[3]  S. Granville Optimal reactive dispatch through interior point methods , 1994 .

[4]  A. P. Sakis Meliopoulos,et al.  Aggregate modeling of distribution systems for multi-period OPF , 2016, 2016 Power Systems Computation Conference (PSCC).

[5]  Yongjun Zhang,et al.  Optimal reactive power dispatch considering costs of adjusting the control devices , 2005 .

[6]  Victor H. Quintana,et al.  Interior-point methods and their applications to power systems: a classification of publications and software codes , 2000 .

[7]  Yi Ding,et al.  Development of a dso-market on flexibility services , 2013 .

[8]  Thomas E. Carroll,et al.  Generalized aggregation and coordination of residential loads in a smart community , 2015, 2015 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[9]  Paul Cuffe,et al.  evolvDSO Deliverable D3.3 - Advanced Methodologies and Tools for Operation and Maintenance of Distribution Grids with DRES , 2015 .

[10]  Wei Zhang,et al.  A Geometric Approach to Aggregate Flexibility Modeling of Thermostatically Controlled Loads , 2016, IEEE Transactions on Power Systems.

[11]  Dirk Kuiken,et al.  Basic schemes for TSO-DSO coordination and ancillary services provision , 2016 .

[12]  N. Megiddo Progress in Mathematical Programming: Interior-Point and Related Methods , 2011 .

[13]  M. El-Hawary,et al.  Hybrid Particle Swarm Optimization Approach for Solving the Discrete OPF Problem Considering the Valve Loading Effects , 2007, IEEE Transactions on Power Systems.

[14]  Steven H. Low,et al.  Convex Relaxation of Optimal Power Flow—Part I: Formulations and Equivalence , 2014, IEEE Transactions on Control of Network Systems.

[15]  Goran Andersson,et al.  On quantification of flexibility in power systems , 2015, 2015 IEEE Eindhoven PowerTech.

[16]  R. J. Bessa,et al.  Estimation of the flexibility range in the transmission-distribution boundary , 2015, 2015 IEEE Eindhoven PowerTech.

[17]  V. H. Quintana,et al.  On a Nonlinear Multiple-Centralitycorrections Interior-Point Method for Optimal Power Flow , 2001, IEEE Power Engineering Review.

[18]  Danny Pudjianto,et al.  Virtual power plant and system integration of distributed energy resources , 2007 .

[19]  Francois Bouffard,et al.  Flexibility Envelopes for Power System Operational Planning , 2014, IEEE Transactions on Sustainable Energy.

[20]  Tobias Kornrumpf,et al.  Economic dispatch of flexibility options for Grid services on distribution level , 2016, 2016 Power Systems Computation Conference (PSCC).