Abstract
As an important part of smart grid construction, the distribution network (DN) optimization problem has always attracted great attention, especially under the background that large-scale penetration of distributed generators (DGs) and electric vehicles (EVs) into building cluster poses both opportunities and challenges to the energy management. This research presents a hierarchical optimization strategy, for improving the safe and economical operation of DN considering the DGs and EVs integration. In Stage 1, the MPPT control model of DGs is designed to obtain the best energy conversion efficiency. In Stage 2, load models of EVs and battery energy storage system (BESS) under coordinate charging/discharging stimulated by a time-of-use incentive mechanism are established respectively, to achieve a load curve with a minimized peak-to-valley difference (PVD). In Stage 3, aiming for the best compromise between the active power loss and node voltage excursion, daily optimal scheduling of the static Var compensator (SVC) capacitors is dynamically worked out according to the varying power demand, as the solution for the defined multi-objective optimization problem. For enhancing the convergence speed, an advanced genetic algorithm with elite preservation strategy is employed. The proposed hierarchical strategy is demonstrated on an IEEE 33-node DN test case, and the simulation results show that first, the MPPT control ensures the maximum power outputs of DGs; next, power supply pressure could be relieved by the load shifting effects of the coordinated vehicle-to-grid (V2G) service and BESS configuration, reflected in the decreased load peak from 4,370.1 to 3,424.99 kW, and the optimized PVD from 1763.8 to 703.8 kW; meanwhile, via applicable power planning of the SVC components, optimized power loss and voltage quality can both be achieved, proving the feasibility of the optimization strategy, which promotes the economic and reliable operation of the DN system.
Highlights
With the sustainable development of the energy industry, the excessive exploitation of traditional fossil energy has brought increasingly severe environmental pollution problems such as energy resource shortage and climate change, making it extremely urgent to utilize renewable energy as an alternative for fossil fuels (Brockway et al, 2019; Xiong et al, 2020)
Establishing on the fundamental principle of multi-source integration and distribution network (DN) optimization control, the hierarchical multi-source coordinated regulation strategy considering the penetration of distributed generators (DGs), electric vehicles (EVs), and battery energy storage system (BESS) is proposed in this study
Combining the efficient utilization of DGs, load shifting function of EVs and BESS, and the dynamic reactive compensation of static Var compensator (SVC) capacitor banks, the optimization strategy could effectively balance the tradeoff between active power loss and node voltage fluctuation, and its feasibility and effectiveness are illustrated through MATLAB simulation results
Summary
With the sustainable development of the energy industry, the excessive exploitation of traditional fossil energy has brought increasingly severe environmental pollution problems such as energy resource shortage and climate change, making it extremely urgent to utilize renewable energy as an alternative for fossil fuels (Brockway et al, 2019; Xiong et al, 2020). The large-scale penetration of renewable resources and new energy equipment alleviates the energy crisis, while bringing rigorous challenges to the power system optimizing configuration and secondary energy rational utilization (Peidong et al, 2009). The randomness and intermittency of power generated from wind turbines (WTs) or photovoltaic cells (PVs) and the time-space dimensional decentralization of electric vehicle (EV) charging, induce more uncertainty for present distribution network (DN) operations than ever before, as well as problems involving harmonic pollution (Siahroodi et al, 2021), three-phase voltage imbalance (Islam et al, 2020), and transformers aging (Elbatawy and Morsi, 2022). The enlarged peak-tovalley difference (PVD) of the load curve puts forward higher requirements for the power system. The serious peak load arisen from the aggregated charging behaviors of EV owners probably causes low-voltage even blackout, concurrently increasing system loss. Guiding measures for coordinated regulation should be taken to minimize the negative influences of integrated renewable energy and EVs while satisfying the power and travel demands of customers
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