In this paper, a model has been developed for bidding strategy of grid-connected micro-grid (MG) considering both active and reactive power dispatch in deregulated environment. MG provides enhanced reliability with amalgamation of energy storage system (ESS) and renewable energy sources. The improvised bidding strategy prepared by MG operator helps to generate higher profits for MG. But the unpredictable nature of renewable sources possesses many constraints on MG for dispatching power. So, here an endeavor has been made by using improved whale optimization algorithm (IWOA) for maximizing the profit of MG taking the uncertainties with the renewable sources and load into account. These stochastic characteristics of renewable wind and solar sources are modeled by Weibull and Beta distribution functions, respectively and for load, Normal distribution is used. Additionally, it describes the charging and discharging state of storage system. The efficiency of proposed technique for bidding strategy is demonstrated on modified IEEE-33 distribution-network with and without ESS. Its performances are analyzed by comparing the outcomes with other optimized algorithms. The results show that, for proposed technique, the bidding strategy of MG yields high profit and low operating cost. As well as inclusion of ESS also reduces the operating cost of MG by increasing its daily profit.

在本文中，已经开发了一种模型，用于在放松管制环境下同时考虑有功和无功功率调度的并网微电网（MG）投标策略。MG 通过整合储能系统 (ESS) 和可再生能源提供更高的可靠性。MG运营商准备的即兴竞价策略有助于为MG创造更高的利润。但是可再生能源的不可预测性对 MG 的调度功率具有许多限制。因此，这里通过使用改进的鲸鱼优化算法 (IWOA) 进行了努力，以最大限度地提高 MG 的利润，同时考虑到可再生能源和负载的不确定性。可再生风能和太阳能的这些随机特性分别由 Weibull 和 Beta 分布函数建模，对于负载，使用正态分布。此外，它还描述了存储系统的充电和放电状态。在带有和不带有 ESS 的修改后的 IEEE-33 配电网络上证明了所提出的投标策略技术的效率。通过将结果与其他优化算法进行比较来分析其性能。结果表明，对于所提出的技术，MG的投标策略产生了高利润和低运营成本。除了包含 ESS 外，还通过增加其每日利润来降低 MG 的运营成本。通过将结果与其他优化算法进行比较来分析其性能。结果表明，对于所提出的技术，MG的投标策略产生了高利润和低运营成本。除了包含 ESS 外，还通过增加其每日利润来降低 MG 的运营成本。通过将结果与其他优化算法进行比较来分析其性能。结果表明，对于所提出的技术，MG的投标策略产生了高利润和低运营成本。除了包含 ESS 外，还通过增加其每日利润来降低 MG 的运营成本。