Real-time Cosimulations for Hydropower Research and Development

Transcription

1 Real-time Cosimulations for Hydropower Research and Development Manish Mohanpurkar, Ph.D. Yusheng Luo, Ph.D. Rob Hovsapian, Ph.D. Power and Energy Department Idaho National Laboratory

2 Introduction Hydropower is the largest producer of renewable energy in the U.S. with over 60% penetration Multiple configurations exist for hydropower generation: Conventional hydro - fixed speed Advanced hydro - adjustable speed Conventional hydropower is based on synchronous generators operating at fixed speed Participate in primary energy market Advanced hydro is typically based on induction machines with speed control through power electronics Additional potential to participate in the ancillary service markets Challenges lack of framework to determine and compensate for stability due to rotating inertia and participation in wider avenues

3 Status of Hydropower & Renewables Brazil Hydropower generation U.S. China Other Renewables 50 Canada Russia India Venezuala Percentage of hydro power generation to the total electricity generation for leading hydro producers of the world Electricity generation by hydro and renewable energy sources in the U.S. (Y-axis: electricity generated in million MWh)

4 Motivation - I Rapid increase in non-deterministic and variable generation resources at transmission and distribution network Results in reduced inertia in grids Hydropower is versatile, emission free, and deterministic source of energy Till recent years was utilized as load following and peaking units Pumped Storage Hydro (PSH) is the only proven grid level storage technique that is economically feasible Advances in power electronics allow the adjustable speed operation Ideal storage characteristics of PSH and AS-PSH Quick response (~15 MW/s) Large capacity (several 100 MWs) No emissions during operation Transmission infrastructure available for interconnections

5 Motivation - II Developing physics based vendor neutral, dynamic models capable of capturing events at a sub-second level for hydro systems Mechanical and hydro systems have response times ranging from few seconds to few minutes A typical ramping rate of an advanced hydropower plant is 5 to 15 MW/seconds Change of state of gate from sensing to controls to execution is few minutes Electrical system dynamic events and faults occur in sub-second to a few seconds A typical 1L-G fault exists for a few cycles and protection systems are activated Technical Gap: A multi domain, true co-simulation environment with models to analyze and provide a stability quantification framework

6 Objectives of AS-PSH modeling Creating physics based, vendor neutral model that can provide a dynamic and transient response in real time Capability of simulating several different modes of operation of AS- PSH with reasonable practicality Capability to co-simulate the hydro-dynamics with other domains i.e., electrical, mechanical, and thermal as needed Demonstrate participation in both real time energy and ancillary service market Capability of providing an environment for Controller-Hardware-In-the- Loop (CHIL), Hardware-In-the-Loop (HIL), and Power-Hardware-In-the- Loop (PHIL) to serve as a verification and validation platform Similarity in control architecture of a Type-3 wind turbines

7 Pumped Storage Hydropower (PSH) Transient Simulation Modeling Develop transient EMT models in small time steps (5-50 s) to better understand the dynamic interactions between electromagnetics and hydrodynamics Study the hydrodynamic behaviors such as water hammering and flywheel effects due to sudden load and fault conditions Conduct System level testing and analysis on the Real Time Digital Simulator Provide a greater understanding of variable renewable interactions and the value of energy storage DFIG Co-simulation of the electromagnetic & hydrodynamic transients

8 Adjustable Speed Pumped Storage Hydro Two primary subsystems within a typical AS-PSH Hydraulic subsystem Electric subsystem Several modes of operation normal generation, normal pumping, idle, down fringe generation, up fringe generation, down fringe generation, etc.

9 Physics Based Modeling Models developed capable of capturing sub-cycle events in both domains Coupled partial differential equations used for the development of models Basic water flow dynamics and solution by Integral Transform : H t U t 2 a U g x H g x fu U 2D H(x,t) is pressure head, U(x,t) is the fluid velocity, a is the pressure wave velocity, g is gravitational acceleration, D is internal diameter of the pipe, and f is a friction factor

10 Unit Step Load Change Large step load is simulated along with the controller signal and output

11 Real Time AS-PSH model Physics based model of the AS-PSH hydro circuit, power electronic converter, converter controls, and a test power system Multiple test scenarios in real time are simulated Balanced faults Unbalanced faults Unit step load changes

12 Real-time Co-simulation of Hydro and Electrical Events Response of the AS-PSH to electrical faults Unbalanced fault: 1 Line to ground fault Balanced fault: 3 Line to ground fault

13 Motivation - III Large hydropower plants may not be possible due to numerous constraints such as regulatory, environmental, and limited resources Immense potential of small sized (< 100 MW) Run-Of-the-River (ROR) hydropower plants is identified 65,500 MW untapped hydro-resources in the U.S. Innovation Emulate the response of a large hydropower plant by coordinating a group of smaller ROR plants ROR hydropower plant operation is typically determined by irrigation schedules and hence non-dispatchable Constant speed operation is the most suited mode for such applications Communications and controls in industry accepted and vendor neutral approach adopted to demonstrate effectiveness

14 Proposed Solution A cohesive operation of multiple ROR hydropower plants and an optimal Energy Storage System (ESS) ESS comprises of supercapacitors, flywheels, and batteries ESS is capable of short to long term support based on ROR power output and response requests Coordination and controls between the components is based on Siemens Smart Energy Box (SEB) SEB is an open platform developed by Siemens and is readily available ROR does not have the inherent storage flexibility therefore it can only participate in the primary energy market ROR plus ESS coordinated operation via SEB will be connected to test and actual power systems to register response to dynamic conditions

15 ROR Hydropower plus ESS Operation Market description Reserve type Timescale of response Timescale of discharge Application Proposed Primary Secondary Tertiary Power electronically interfaced Smaller (µs ms) Spinning Spinning Non-spinning Medium (ms s) Longer (s minutes) µs minutes several minutes 30 minutes 2 hours Transient stability, power quality corrections Operating reserve for regulation, fault recovery, power quality Operating reserve for slow dynamics, voltage support, contingency Longer (minutes hours) several hours Load leveling, energy arbitrage, firming, contingency Example technologies Supercapacitors, flywheels Synchronous generators, batteries Synchronous generators, batteries Pumped hydro, gas turbines

16 Front End Controller Development Develop physics based ESS models and vendor neutral topologies in real time environment Develop Front-End-Controller (FEC) to receive grid management signals and respond as needed FECs will be developed for each ESS component Verification and validation via Controller-Hardware-In-the-Loop (CHIL) of FEC in real time environment Assess the economic and financial value streams of ROR HPPs HIL testing based on RTDS links between INL and NREL with the controllable grid interface Dynamic grid and market conditions to be simulated RTDS link between the two labs is an outcome of an existing LDRD effort at INL

17 Accomplishments and Progress Control Architecture for integrating ROR HPP with ESS and power grid

18 Proposed Framework Storage Devices Hardware in the Loop Devices Super capacitor Battery (80kW) I/O Real Time Environment Power electronics interface Siemens Smart Energy Box Inverter controller ROR models developed collaboratively Front End Controller Interface Power Market Interface Primary Energy Market Front End Controller Permanent Magnet based Hydro Power Plant Induction Machine based Hydro Power Plant Simulated Devices Flywheel model Battery model I/O Electric Grid model Hydro model Spot Market Ancillary Service Market Front End Controller Induction Machine based Hydro Power Plant INL Data for economic analysis generated to be used with PLEXOS and FESTIV type tools ANL Front End Controller NREL

19 HIL based testing with NREL A controllable grid interface at NREL will be used remotely via RTDS links to perform hardware performance validation of the developed framework Data generated from dynamic grid and market conditions will be analyzed by Argonne National Laboratory and Energy Exemplar Economic feasibility and revenue data will be generated for business case

20 Concluding Remarks Real Time Power and Energy Group, INL is actively involved in multiple hydropower related projects Brief review of two current projects at INL by Wind and Water Program Technologies Office is discussed Dynamic modeling of Adjustable-Speed Pumped Storage Hydropower Plant Co-simulation of hydro and electrical events in real time at sub-second regime Integrated Hydropower and Storage Systems Operation for Enhanced Grid Services Cohesive response of multiple ROR hydropower plants and storage to provide ancillary services A physics based, vendor neutral modeling approach is adopted in real time environment with sub-second resolution True real time co-simulations performed to analyze systems Multiple DOE labs, industry, and utilities with complimentary skills to form teams

21 Thank you & Questions