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Optimal Offering and Operating Strategies for Wind-Storage Systems With Linear Decision Rules

机译:带有线性决策规则的储风系统的最优产品和运营策略

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The participation of wind farm-energy storage systems (WF-ESS) in electricity markets calls for an integrated view of day-ahead offering strategies and real-time operation policies. Such an integrated strategy is proposed here by co-optimizing offering at the day-ahead stage and operation policy to be used at the balancing stage. Linear decision rules are seen as a natural approach to model and optimize the real-time operation policy. These allow enhancing profits from balancing markets based on updated information on prices and wind power generation. Our integrated strategies for WF-ESS in electricity markets are optimized under uncertainty in both wind power and price predictions. The resulting stochastic optimization problem readily yields optimal offers and linear decision rules. By adding a risk-aversion term in form of conditional value at risk into the objective function, the optimization model additionally provides flexibility in finding a trade-off between profit maximization and risk management. Uncertainty in wind power generation, as well as day-ahead and balancing prices, takes the form of scenario sets, permitting to reformulate the optimization problem as a linear program. Case studies validate the effectiveness of the strategy proposed by highlighting and quantifying benefits w.r.t. other existing strategies.
机译:风电场储能系统(WF-ESS)参与电力市场需要对日前提供策略和实时运营策略进行综合了解。通过在日前阶段优化供应和在平衡阶段使用的运营策略,在这里提出了这样一种集成策略。线性决策规则被视为建模和优化实时操作策略的自然方法。这些可以根据价格和风力发电的最新信息,通过平衡市场来提高利润。我们在风能和价格预测都存在不确定性的情况下优化了电力市场中WF-ESS的综合策略。由此产生的随机优化问题很容易产生最优报价和线性决策规则。通过将风险条件值形式的风险规避项添加到目标函数中,优化模型还可以在寻找利润最大化和风险管理之间的权衡时提供灵活性。风力发电的不确定性以及日前价格和平衡价格采用场景集的形式,从而可以将优化问题重新制定为线性程序。案例研究通过突出和量化收益来验证所提出策略的有效性。其他现有策略。

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