{'fraction_non_alphanumeric': 0.017973856209150325, 'fraction_numerical': 0.0032679738562091504, 'mean_word_length': 5.282051282051282, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Dual-Objective MPC of Community Energy Storage in LV Distribution Feeders with Rooftop Solar PV

The technical challenges of large-scale integration of rooftop solar PV systems is a major concern for distribution network service providers (DNSPs) due to bidirectional power flow and voltage regulation issues. Energy storage devices have the potential to mitigate these adverse effects by storing excess energy during the day and providing peak shaving support at peak load. This paper presents a two-level dual-objective model predictive control (MPC) based algorithm to control DNSP owned community energy storage devices in LV residential distribution feeders. The proposed control method considers the feed-in tariff, spot price of energy and storage system operational costs. Both the economics of the system and voltage regulation are addressed. The individual modes of operation are activated by a high-level controller and a low-level controller provides the optimized charging/discharging rates according to the predefined objective cost functions. A case study 300m 4-wire LV feeder from NSW, Australia is used to demonstrate the efficacy of the proposed control method through a time series power flow simulation.