/openTEPES

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

Primary LanguagePythonMIT LicenseMIT

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

Simplicity and Transparency in Power Systems Planning

The openTEPES model has been developed at the Instituto de Investigación Tecnológica (IIT) of the Universidad Pontificia Comillas.

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.

In addition, the 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 expansion 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:

  1. 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:

    1. Period: one year

    2. Load level: 2030-01-01T00:00:00+01:00 to 2030-12-30T23:00:00+01:00

    The 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.

  2. 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 formulation 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: Locational Short-Run Marginal Costs (LSRMC)

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.