{'fraction_non_alphanumeric': 0.017857142857142856, 'fraction_numerical': 0.0, 'mean_word_length': 5.455497382198953, '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}}
Decision Support Model under Transactive Energy Markets for Profit Maximization

The proliferation of distributed energy resources (DER) demands a flexible marketplace in the distribution level to fully harness the local resources. Creation of local flexible market under transactive energy (TE) framework would enable small to medium-sized prosumers to participate in the energy market locally for transactions. In this context, a new decision support model is proposed to optimize the player's negotiations for day-ahead market. The proposed model assists the small players to maximize their profits in the market exchanges and is operates on the nature-inspired based water cycle algorithm (WCA). The efficiency of the proposed model is tested on a microgrid consisting of both dispatchable and non-dispatchable distributed generators. Moreover, the performance of WCA based technique is compared with other heuristic techniques such as particle swarm optimization and genetic algorithm. The reliability of the model is also studied for different energy markets. The results show that the proposed method is quite capable to minimize the overall day-ahead operational costs and explores the benefits of local energy transactions.