Intelligent Volt/Var Control in Active Distribution Networks
In recent years, distributed generations (DG) including renewable energy resources (RESs) have been increasingly integrated into distribution networks. In the conventional VVC, on-load tap changers (OLTC) and capacitor banks (CBs) are responsible for mitigating voltage violations caused by the fluctuation of load power. The penetration of DGs could improve the flexibility and economy of active distribution networks (ADN) but will also pose new challenges to the conventional Volt/Var control (VVC). Especially for RES like solar photovoltaics (PV), the intermittency and uncertainty of PV outputs may cause a sharp fluctuation of feed power, resulting in severe voltage violation problems. In this project, we focus on volt/var control problems and explore potential effective and fast-responding methods to mitigate voltage violations in different timescales. Students are required to submit a final report with runnable Matlab codes.
Part 1: Day-Ahead Dispatch with Conventional Volt/Var Control
In this part, you are required to implement day-ahead scheduling of OLTCs and CBs to minimize network power loss while maintaining voltage levels within acceptable bounds.
1. Data preparation and model the system: Use at least the IEEE 9-bus distribution network as the testbed. (IEEE 33-bus distribution network is preferred). Determine the capacity, operation parameters and placement of voltage regulation devices according to your specific network topology.
2. Formulate the problem: Define the optimization problem as a mixed-integer second- order cone programming (MISOCP) model.
l Minimize the total power loss in the network.
l Ensure voltage levels remain within specified limits.
l Dist-flow constraints.
l Operational constraints of OLTCs and CBs.
l …etc.
3. Solve the problem: Use the hourly data (i.e., PV and load predictions) to simulate the day-ahead scenario. Implement the MISOCP formulation using Matlab. You can use any solver that is suitable for your specific optimization problem in Matlab.
4. Deliverables:
l The mathematical formulation of your specific optimization problem
l Explain the variables, objective function, each constraint in your specific optimization problem in detail.
l Provide the Matlab code solving the MISOCP problem.
l Demonstrate the results you obtained in figures or tables. Analyze the results (findings) based on the values you obtained. (i.e., voltage profiles before and after optimization and the switching actions of OLTCs and CBs, etc.)
Fig. 1. Diagram of the IEEE 33-bus distribution network
Part 2: Enhanced Volt/Var Control
As discussed, the increasing penetration of DGs, while beneficial for flexibility and economy, introduces challenges due to the intermittent and uncertain nature of resources like solar PVs. Voltage violations resulting from rapid fluctuations in PV outputs require a more dynamic approach than what conventional devices like OLTCs and CBs can provide. In this part, we are going to explore the potential effective and fast-responding methods to mitigate voltage violations in different timescales.
1. At the beginning, please do the literature review on the existing methods for VVC based on the implementation mechanism. (At least five existing research in recent years)
2. What are the limitations of OLTCs and CBs in responding to fast voltage fluctuations?
3. Please provide a candidate approach to coordinate real-time voltage control across different timescales. Explain your idea first, then formulate your problem mathematically.
4. Implement your proposed enhanced methods, and discuss the improvements compared with conventional volt/var control method in part 1. Demonstrate your results in figures or tables. Also, are there any limitations of your proposed solution?
5. Provide the runnable codes.