Stochastic Reactive Power Management in Microgrids with Renewables (1409.6758v2)

Abstract: Distribution microgrids are being challenged by reverse power flows and voltage fluctuations due to renewable generation, demand response, and electric vehicles. Advances in photovoltaic (PV) inverters offer new opportunities for reactive power management provided PV owners have the right investment incentives. In this context, reactive power compensation is considered here as an ancillary service. Accounting for the increasing time-variability of distributed generation and demand, a stochastic reactive power compensation scheme is developed. Given uncertain active power injections, an online reactive control scheme is devised. This scheme is distribution-free and relies solely on power injection data. Reactive injections are updated using the Lagrange multipliers of a second-order cone program. Numerical tests on an industrial 47-bus microgrid and the residential IEEE 123-bus feeder corroborate the reactive power management efficiency of the novel stochastic scheme over its deterministic alternative, as well as its capability to track variations in solar generation and household demand.

• The paper proposes a stochastic reactive power management framework that computes expected losses and compensates for renewable variability in microgrids.
• It utilizes a data-driven, distribution-free control scheme to dynamically adjust PV inverter injections for improved voltage regulation.
• It employs convex relaxation techniques (SOCP) to efficiently approximate the complex optimal power flow problem, validated on 47-bus and 123-bus systems.

Stochastic Reactive Power Management in Microgrids with Renewables

The paper explores the challenges and solutions in managing reactive power in microgrids characterized by significant penetration of renewable resources. The primary focus is on photovoltaic (PV) inverters, which, while traditionally designed for unity power factor operation, can be leveraged for reactive injection to assist with voltage regulation. The authors introduce a novel stochastic reactive power compensation scheme to address the uncertainties associated with renewable generation and consumption in microgrids.

Key Contributions

1. Stochastic Framework: Rather than relying on deterministic methods, the paper presents a stochastic reactive power management strategy. This approach computes expected power losses and compensates for reactive power injections accordingly, taking into account the variable nature of both solar generation and household demand.
2. Data-Driven Approach: The proposed control scheme is distribution-free, implying that it does not rely on any specific statistical distribution of power injections. Instead, it dynamically adjusts based on actual power data, making it versatile in diverse microgrid settings.
3. Convex Relaxation Techniques: To handle the intrinsic complexity of the optimal power flow (OPF) problem, the authors employ a second-order cone program (SOCP). This technique is noted for its effectiveness in ensuring that the solution to the relaxed problem closely approximates, if not equates, the solution to the original non-convex problem.
4. Numerical Validation: Through tests on a 47-bus industrial microgrid and the 123-bus IEEE feeder, the paper provides evidence for the efficiency of the stochastic approach in managing reactive power compared to traditional deterministic methods. Particularly, the stochastic scheme demonstrates superior performance in reducing power management costs and adjusting to variability in solar insolation and load demand.

Implications and Future Directions

Theoretical Implications: The paper advances the understanding of stochastic optimization in power systems, particularly in contexts where prediction errors or fast variations are prevalent. Its framework accommodates real-time updates and adaptive management in a computing resource-efficient manner.

Practical Implications: On the operational level, the proposed scheme can result in cost savings and improved voltage regulation in microgrids. This is particularly important in regions with high solar energy utilization, where voltage instabilities could otherwise undermine grid reliability and performance.

Speculative Future Research: Future work could extend these principles to other avenues of microgrid control, such as conservation voltage reduction strategies or decentralized decision models where individual PV inverters could autonomously manage their reactive power contributions. Moreover, the robustness of such schemes against cyber threats and data integrity issues presents an open area for exploration.

In conclusion, this paper contributes a rigorous yet practical stochastic reactive power management scheme that can be pivotal in the stability and economical operation of future microgrids heavily reliant on renewable energy sources.