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MELP - Long Term Generation Expansion Model

MELP is a computational model developed by CEPEL for long-term generation expansion planning (GEP) studies of the Brazilian power system, which are usually performed for the next 20-30 years. One of the main objectives of GEP is to determine an expansion plan which ensures an economic and reliable supply for the future increasing demand. Mathematically, it leads to a large-scale multi-stage mixed-integer optimization problem with an objective function that minimizes the total investment and operation costs required to supply the demand according to a given reliability criteria. Investments include new generation plants and interconnection links. The reliability issue is concerned with an adequate energy supply under adverse conditions, which are uncertain. For large hydro-dominated power systems, uncertainties related to the water inflows are usually represented in a simplified manner in GEP studies, in order to allow the representation of other important uncertainties such as demand growth and fuel costs, thus obtaining an acceptable solution with a reasonable CPU time.

In MELP model, hydrology uncertainties are represented by considering a reduced number of hydrology scenarios. Expected energy availability for each hydro plant is assigned according to the hydrology scenario and this value considered as the maximum generation for that plant and scenario. Originally, MELP considered only the critical and the average (favorable) hydro scenarios to evaluate the system reliability and economic aspects, respectively, which avoided the need of assigning probabilities for each scenario. Currently, if probabilities are known, the user can define more than two scenarios. The expansion plan provided by the model can be evaluated by performing integrated simulation studies with the NEWAVE model, where uncertainty on the hydro inflows is better detailed. MELP model was used in the planning studies carried out for the 2030 Brazilian National Energy Plan.

The increasing use of natural gas for electricity generation requires an integrated expansion planning of both power and natural gas systems. For this purpose, MELP model has been improved by adding the natural gas system representation, which includes suppliers, pipelines and end users. Gas fired power plants link the natural gas to the power system. In order to exploit the seasonal production pattern of renewable sources (e.g. hydro, wind and cogeneration using sugar cane bagasse) and adequately estimate the interconnection reinforcements, operation analysis in MELP model is carried out on a three-monthly basis. In addition, for each of these periods, system operation is evaluated for three levels of daily demand.

The branch-and-cut (BC) algorithm available in the CPLEX/IBM computer package has been applied to solve MELP model. However, for more complex MELP cases, the performance of the standard BC approach has shown highly time consuming. In order to enhance computational efficiency, a local branching approach was developed to find high quality integer feasible solutions. Nonetheless, for even more complex higher dimension cases, the resulting mixed-integer program may easily reach a number of millions of variables and constraints, thus becoming intractable without an adequate decomposition approach. For this type of problems, an integer programming approach based on Dantzig-Wolfe decomposition was developed resulting in a state-of-the-art Branch-and-Price algorithm.

Regarding environmental concerns, the current version of MELP allows to consider any user-defined constraint such as a maximum level of accumulated greenhouse emissions over the planning horizon, renewable level in the electricity matrix etc. This type of constraints allows performing multi-criteria expansion planning analysis, taking into account economic and environmental aspects.

For a better evaluation of the system operation regarding hydrology uncertainties, MELP may be coupled to NEWAVE model (Long to Medium Term Operation Planning Model of Interconnected Hydrothermal Systems), thus improving the adequacy of the expansion plan. For this purpose, an interactive process can be performed for applications such as the ten-year expansion planning studies.

Key Data

1 - General data:
Planning horizon;
Discount rate.
2 - Eletrical system:
system configuration (generation subsystems and their interconnections);
energy demand projection for each subsystem;
technical and economic data for power generation plant projects
technical and economic data for the interconnection links;
fuel costs;
fixed and variable operating and maintenance costs;
3 - Natural gas system:
natural gas system configuration ( NG subsystems and pipelines);
natural gas non-electricity demand projection for each subsystem;
- technical and economic data for the natural gas processing plants projects, regasification units and gas pipeline projects.

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