Abstract
Networking of microgrids has received increasing attentions in recent years, which requires the uncertainty management associated with variations in the system. In this paper, a two-stage energy management strategy is developed for networked microgrids under the presence of high renewable resources. It decomposes the microgrids energy management into two stages to counteract the intra-day stochastic variations of renewable energy resources, electricity load and electricity prices. In the first stage (hourly time scale), a hierarchical hybrid control method is employed for networked microgrids, aiming to minimize the system operation cost. The mean–variance Markowitz theory is employed to assess the risk of operation cost variability due to the presence of uncertainties. In the second stage (5-min time scale), the components in microgrids are optimally adjusted to minimize the imbalance cost between day-ahead and real-time markets. Simulation study is conducted on an uncoordinated microgrids system as well as on the proposed networked system. According to the simulation results, the proposed method can identify optimal scheduling results, reduce operation costs of risk-aversion, and mitigate the impact of uncertainties.
1. Introduction
Heightened concerns about energy resource limits, climate change, as well as increasing energy prices, has led countries to increased integration of renewable energy sources (RESs) into modern power systems, primarily in the form of solar photovoltaic panels and wind turbines [1]. A transition from fossil-based and non-renewable fuels to renewable and sustainable energy is occurring around the world [2].
6. Conclusions and future research challenge
This paper proposes a two-stage, i.e. an hourly day-ahead scheduling and 5-min real-time dispatch, energy management strategy for networked MGs in the presence of high renewable penetration. In the day-ahead scheduling stage, a hybrid energy management system control method is adopted considering the hierarchical structure of networked microgrids The control objective is to minimize the operation cost on a daily basis and the operation cost variations are captured by incorporating mean-variance Markowitz theory into the objective function. Uncertainties on renewable energy resources output, electricity load, and electricity price are addressed in the first stage.
