Qianya He, Zhenjia Lin, Haoyong Chen, et al. Bi-level optimization based two-stage market clearing model considering guaranteed accommodation of renewable energy generation[J]. Protection and Control of Modern Power Systems, 2022, 7(3): 1-13.
DOI:
Qianya He, Zhenjia Lin, Haoyong Chen, et al. Bi-level optimization based two-stage market clearing model considering guaranteed accommodation of renewable energy generation[J]. Protection and Control of Modern Power Systems, 2022, 7(3): 1-13.DOI: 10.1186/s41601-022-00253-y.
Bi-level optimization based two-stage market clearing model considering guaranteed accommodation of renewable energy generation
The existing electricity market mechanisms designed to promote the consumption of renewable energy generation complicate network participation in market transactions owing to an unfair market competition environment
where the low cost renewable energy generation is not reflected in the high bidding price of high cost conventional energy generation. This study addresses this issue by proposing a bi-level optimization based two-stage market clearing model that considers the bidding strategies of market players
and guarantees the accommodation of renewable energy generation. The first stage implements a dual-market clearing mechanism that includes a unified market for trading the power generations of both renewable energy and conventional energy units
and a subsidy market reserved exclusively for conventional generation units. A re-adjustment clearing mechanism is then proposed in the second stage to accommodate the power generation of remaining renewable energy units after first stage energy allocations. Each stage of the proposed model is further described as a bi-level market equilibrium problem and is solved using a co-evolutionary algorithm. Finally
numerical results involving an improved IEEE 39-bus system demonstrate that the proposed two-stage model meets the basic requirements of incentive compatibility and individual rationality. It can facilitate the rational allocation of resources
promote the economical operation of electric power grids
A Newly Permittable Spatially Coupled Demand Response Model for Fast Charging Station Loads
Optimal Planning of Renewable Energy and Storage Considering Capacity Credit Constraint
Integrated Energy-Water Nexus Optimization in Rural Microgrids: Leveraging Quantum-classical Robust Optimization for Sustainability
Synergistic Carbon Trading and Power Generation Decision Considering the Annual Compliance Cycle and Market Response: A Hybrid Mathematical-Deep Reinforcement Learning Optimization Approach
Enhanced Resilience and Efficiency in Multi-Energy Systems via Stochastic Gradient-Driven Robust Optimization
Related Author
Min Chen
Mengjie Liu
Yujie Sheng
Qinglai Guo
Renshun Wang
Shilong Wang
Guangchao Geng
Quanyuan Jiang
Related Institution
Department of Electrical Engineering, Beijing Jiaotong University
Department of Electrical Engineering, Tsinghua University
State Grid Fujian Electric Power Dispatching and Control Center, State Grid Fujian Electric Power Co., Ltd.
College of Electrical Engineering, Zhejiang University
State Grid Electric Power Research Institute (NARI Group Corporation)