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Oferta tecnológica

openTEPES: Open Generation and Transmission Operation and Expansion Planning Model with RES and ESS

Dr. Andrés Ramos Galán

Introduction

The Open Generation and Transmission Operation and Expansion Planning Model with RES and ESS (openTEPES) determines the investment plans of new facilities (generators, ESS and lines) for supplying the forecasted demand at minimum cost. Tactical planning is concerned with time horizons of 10-20 years. Its objective is to evaluate the future generation, storage and network needs. The main results are the guidelines for the future structure of the generation and transmission systems.

The openTEPES model presents a decision support system for defining the generation and transmission expansion plan of a large-scale electric system at a tactical level, defined as a set of generation and network investment decisions for future years. The candidate generators, ESS and lines are pre-defined by the user, so the model determines the optimal decisions among those specified by the user.

It determines automatically optimal expansion plans that satisfy simultaneously several attributes. Its main characteristics are:

  • Static: the scope of the model corresponds to a single year at a long-term horizon, 2030 or 2040 for example.

    It represents hierarchically the different time scopes to take decisions in an electric system:

    - Period: one year

    - Load level: h0001 to h8760 or 01/01/2030 00:00 to 30/12/2030 23:00

    This time division allows a flexible representation of the periods for evaluating the system operation. For example, by a set of non-chronological isolated snapshots or by 2920 periods of three hours or by the 8760 hours of the year.

  • Stochastic: several stochastic parameters that can influence the optimal generation and transmission expansion decisions are considered. The model considers stochastic short-term yearly uncertainties (scenarios) related to the system operation. The operation scenarios are associated with renewable energy sources and electricity demand.

Multicriteria: the objective function incorporates some of the main quantifiable objectives: generation and transmission investment cost (CAPEX) and expected variable operation costs (including generation emission cost) (system OPEX).

The model formulates an optimization problem including generation and network binary investment decisions and operation decisions.

The operation model is a network constrained unit commitment (NCUC) based on a tight and compact network unit commitment (UC) model including operating reserves with a DC power flow (DCPF). Network ohmic losses are considered proportional to the line flow. It considers different energy storage systems (ESS), e.g., pumped-storage hydro, battery, etc. It allows analyzing the trade-off between the investment in generation/transmission and the use of storage capacity.

The main results of the model can be structured in these topics:

  • Investment: investment decisions and cost.
  • Operation: the output of different units and technologies (thermal, storage hydro, pumped-storage hydro, RES), RES curtailment, line flows, line ohmic losses, node voltage angles.
  • Emissions: CO2.
  • Marginal: Short-Run Marginal Costs (SRMC).

A careful implementation has been done to avoid numerical problems by scaling parameters, variables and equations of the optimization problem alowing the model to be used for large-scale cases.

Research projects

This model is currently being used in the European research project:

The Open ENergy TRansition ANalyses for a low-carbon Economy (openENTRANCE), developed for the European Union, aims at developing, using and disseminating an open, transparent and integrated modelling platform for assessing low-carbon transition pathways in Europe.

L. Olmos, S. Lumbreras, A. Ramos, E. Alvarez, M. Rivier

OpenEntrance

Contact Us

Andrés Ramos

andres.ramos@comillas.edu

More information here

Some TEP-related publications:

[1] S.Lumbreras, F. Banez-Chicharro, A. Ramos "Optimal Transmission Network Expansion Planning in Real-Sized Power Systems with High Renewable Penetration", Electric Power Systems Research 49, 76-88, Aug 2017. DOI: 10.1016/j.epsr.2017.04.020

[2] S.Lumbreras, A. Ramos "The new challenges to transmission expansion planning. Survey of recent practice and literature review", Electric Power Systems Research 134: 19-29, May 2016. DOI: 10.1016/j.epsr.2015.10.013

[3] D.A. Tejada-Arango, S. Lumbreras, P. Sánchez-Martín, and A. Ramos "Which Unit-Commitment Formulation is Best? A Systematic Comparison", IEEE Transactions on Power Systems. DOI: 10.1109/TPWRS.2019.2962024

[4] C. Gentile, G. Morales-España, and A. Ramos "A tight MIP formulation of the unit commitment problem with start-up and shut-down constraints", EURO Journal on Computational Optimization 5 (1), 177-201 Mar 2017. DOI: 10.1007/s13675-016-0066-y

[5] G. Morales-España, A. Ramos, and J. Garcia-Gonzalez "An MIP Formulation for Joint Market-Clearing of Energy and Reserves Based on Ramp Scheduling", IEEE Transactions on Power Systems 29 (1): 476-488, Jan 2014. DOI: 10.1109/TPWRS.2013.2259601

[6] G. Morales-España, J. M. Latorre, and A. Ramos "Tight and Compact MILP Formulation for the Thermal Unit Commitment Problem", IEEE Transactions on Power Systems 28 (4): 4897-4908, Nov 2013. DOI: 10.1109/TPWRS.2013.2251373

[7] P. Damci-Kurt, S. Küçükyavuz, D. Rajan, and A. Atamtürk "A polyhedral study of production ramping", Math. Program., vol. 158, no. 1–2, pp. 175–205, Jul. 2016. DOI: 10.1007/s10107-015-0919-9

[8] D. Rajan and S. Takriti "Minimum up/down polytopes of the unit commitment problem with start-up costs", IBM, New York, Technical Report RC23628, 2005.