Use of Residual Load Duration Curves to study the high penetration of renewables in TIMES-Greece G. Giannakidis K. Tigas J. Mantzaris Centre for Renewable Energy Sources and Saving (CRES), Athens, Greece
Introduction Questions from the Policy makers: • Achievement of RES targets, optimal mix of RES • Analysis on possible CO2 reduction levels scenarios • Feasibility of new power plants • Impact of RES in the electricity system • Storage requirements and reserve capacity requirements
Introduction A number of issues arise in long term energy planning under environmental constraints and large scale RES utilization requirements: • strong stochastic nature of RES and the limitations in their dispatching need to be taken into account, given the curtailment that might be necessary when load is low and RES generation high. • addressing this through the construction of storage plants and fast reserve capacity to balance the load variation.
Approach Multi-Regional TIMES model PSS/E In-house tool grid impact studies Probabilistic simulation WASP for electricity (PropSim)
Approach Application: A multi-regional TIMES model (14 regions) 16 timeslices Seasons hours (R S F W) (D N P L) Electricity grid modelling 1) Standard TIMES trading processes between regions 2) Include a simplified electricity grid with 73 nodes and 99 corridors (to be used in the DC load flow).
Approach The TIMES solution should incorporate: • costs related to transmission grid expansions necessary for penetration of geographical areas with a high potential of renewables and • costs related to balancing units required due to variations of renewable generation (storage plants and fast response power plants (gas turbines)).
Approach To handle the stochastic aspects introduced by the large scale penetration of RES, the TIMES model was combined (soft linked) with a model for Probabilistic Production Simulation (ProPSim): • Calculate Residual Load Duration Curves (RLDC) from hourly values of customer load and hourly values of non-dispatchable generation (wind, PV, small hydro and CHP) which are provided as input. • For a given time interval (hourly simulation) ProPSim then simulates the operation of the generation system and it calculates the peak load capacity required, the balancing units capacity required to cover the residual load hourly variations and the storage capacity required to restrict energy curtailment. • These ancillary services parameters together with corrected utilization factors of Renewables are then fed back to the TIMES model (include the cost which entails balancing units costs, storage costs, grid expansion and connection costs together with utilization factors of RES in specific areas).
Approach
Methodology The methodology to derive RLDCs is based on the determination of the load (residual load) that remains to be covered by dispatchable units (thermal, reservoir hydro). 1) Results from TIMES for the electricity demand and electricity production per RES technology for the future years. 2) Time series are developed based on historical data for RES generation combined with concurrent customer load which are extrapolated into the future to forecast the variables of production from RES units (with one hour time resolution). 3) The probability density function (PDF) and the cumulative distribution function (CDF) of the different forms of non-dispatchable generation as well as the customer load are formulated and are input into ProPSim to calculate a Residual Load Duration Curve on a monthly basis through the convolution of the customer load with the non- dispatchable energy generation (hourly zones are used to assure small correlation between load and RES energy).
Methodology The derived residual load duration curve used in PropSim is obtained from the convolution of the customer load with the generation from non dispatchable sources j which is expressed by the following equation PDF of generation from source j PDF of Load where L res = I L−j x is the CDF (cumulative distribution function) of residual load (Residual Load Duration Curve), L is the customer load, C j is the generating capacity from non-dispatchable source j and F L−j x is the CDF (cumulative distribution function) of the convolution of the customer load with the non dispatchable generation source j .
Methodology Based on the formulation of the Residual Load Curve Residual Load Curve Residual Load Curve Residual Load Duration Curve it is possible to define an optimum 10000 10000 10000 Demand 9000 9000 combination of thermal plants and 9000 Demand Demand x (-PV) Demand Demand x (-PV) 8000 8000 8000 Demand x (-PV-wind) Tech minimum reservoir-type hydro plants to cover Tech minimum 7000 7000 7000 Tech minimum the load that remains to be covered 6000 Power (MW) 6000 Power (MW) 6000 Power (MW) 5000 5000 by dispatchable plants. 5000 4000 4000 4000 At the same time, the level of 3000 3000 3000 2000 2000 penetration of non-dispatchable 2000 1000 1000 1000 energy is considered in the light of the 0 0 0 0 0 100 100 200 200 300 300 400 400 500 500 600 600 700 700 required level of additional costs 0 100 200 300 400 500 600 700 Hours Hours Hours related to non-dispatchable electricity curtailment or balancing units required. Monthly RLDC
Methodology Non dispatchable energy curtailment is related to the technical minimum of thermal power plants of the generation system and can be reduced either by selecting generation technologies with decreased technical Storage reserve minimum, or by using sufficient capacity of required R st storage plants. The storage capacity normally does not balance 100% of the potential curtailment. The probability for curtailment is restricted by a parameter ε (which normally is taken at the level of 1 % or 87 hours annually)
Detailed Methodology Need to calculate the reserve capacity necessary for maintaining a constant index of reliability under variations of the residual load. In the present approach a load shedding incident can happen in case that the variation of the residual load on an hourly basis (which can be a consequence of load variation, of variation of the production of non-dispatchable units and of the possibility of one or two generator trips) exceeds the spinning reserve.
Some results Pumped Storage Capacity (MW) 6000 5000 CP: Current Policies Scenario. 4000 Capacity (MW) CP EMCM-60%: Environmental 3000 EMCM-60% RESM-60% measures 60% emissions 2000 reduction in 2050 wrt 2005. 1000 0 RESM-60%: RES-E maximization 2020 2025 2030 2035 2040 2045 2050 scenario with 60% emissions reduction in 2050 wrt 2005. Reserve Capacity for Hourly Load Variations (MW) 3000 2500 2000 Capacity (MW) CP 1500 EMCM-60% RESM-60% 1000 500 0 2020 2030 2040 2050
Incorporation of the methodology into TIMES Residual Load Curve features have been included into the last version of TIMES and could be used for evaluating the impacts of the integration of large amounts of variable renewable generation on the electricity system. Due to its nature as a long-term energy system modeling framework, TIMES is not very well suitable for stochastic generation expansion planning, but one can try to simulate the impacts of stochasticity on the system by using deterministic variation parameters that are statistically calibrated outside the model.
Implementation in TIMES The specific residual load modelling features in TIMES include the following components: • Calculation of residual load curves by region and time period; • Constraints ensuring that the technically imposed minimum levels of thermal generation are satisfied; • Constraints for ensuring sufficient storage and peak capacity, taking into account the expected variations in the load and non-dispatchable generation.
Implementation in TIMES Non - dispatchable power curtailment is related to the technical minimum of thermal power generation in the system. In TIMES constraints are imposed on the thermal power generation that reflect these technical limits: for each thermal power technology i and each timeslice j with a duration of dj Options for declaring this:
Implementation in TIMES Two capacity constraints are imposed to cope with the variation in the residual load. 1) Define the minimum required storage capacity in each timeslice: Residual Load Curve th min (P ,t ) Demand x (-PV-wind) res Demanded storage at L Tech minimum every residual load level Power (MW) (each timeslice) is defined by the difference of its value from technical res (L ,t ) res L minimum of dispatchable plants in the system Hours (thermal minimum) stg stg th min res Storage AF CAP P L i,j i j j i
Variation component • At every level of 1 residual load ( L res ), 0.8 there is a res res (850, 0.99) VAR L corresponding Probability 0.6 probability function describing the possible 0.4 res res VAR L variations of residual (-800, 0.01) 0.2 load • An additional 0 -1000 -500 0 500 1000 component is added in Load Variation (MW) the equation for storage requirement stg stg th min res res res Storage AF CAP P L VAR L i,j i j j j j i
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