Generation expansion planning in electricity markets: A novel framework based on dynamic stochastic MPEC |
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| Affiliation: | 1. Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, USA;2. Department of Chemical Engineering, Tsinghua University, Beijing, China;3. Air Products and Chemicals, Inc., Allentown, USA;1. PJM Interconnection, Norristown, PA 19403, USA;2. IMSE, University of South Florida, Tampa, FL 33613, USA;3. IT Operations Analytics, IBM;4. Energy Systems Division, Argonne National Laboratory, Argonne, IL 60439, USA;1. School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China;2. State Grid Energy Research Institute, State Grid Corporation of China, Beijing 102200, China;3. Energy Analysis and Environmental Impacts Division, Lawrence Berkeley National Laboratory, CA 94720, United States;4. Energy and Resources Group, University of California, Berkeley, CA 94720, United States;5. Department of Electrical Engineering, Tsinghua University, Beijing 100084, China |
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| Abstract: | This paper presents a novel framework for generation expansion planning (GEP) of restructured power systems under uncertainty in a multi-period horizon, which includes generation investment from a price maker perspective. The investment problem is modeled as a bi-level optimization problem. The first level problem includes decisions related to investment in order to maximize total profit in the planning horizon. The second level problem consists of maximizing social welfare where the power market is cleared. Rival uncertainties on offering and investment are modeled using sets of scenarios. The bi-level optimization problem is then converted to a dynamic stochastic MPEC and represented as a mixed integer linear program (MILP) after linearization. The proposed framework is examined on a typical six-bus power network, MAZANDARAN regional electric company (MREC) transmission network as an area of IRAN interconnected power system and IEEE RTS 24-bus network. Simulation results confirm that the proposed framework can be a useful tool for analyzing the behavior of investments in electricity markets. |
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| Keywords: | Dynamic stochastic MPEC Generation expansion planning (GEP) Strategic producer Uncertainty |
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