Offering strategy of a price-maker virtual power plant in the day-ahead market

IF 2.4 Q3 ENERGY & FUELS
Nhung Nguyen-Hong, Khai Bui Quang, Long Phan Vo Thanh, Duc Bui Huynh
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Abstract

With the rapid increase of renewable energy sources (RESs), the virtual power plant model (VPP) has been developed to integrate RESs, energy storage systems (ESSs), and local customers to overcome the RESs’ disadvantages. When the VPP’s capacity is large enough, it can participate in the electricity market as a price-maker instead of a price-taker to obtain a higher profit. This study proposes a bi-level optimization model to determine the optimal trading strategies of a price-maker VPP in the day-ahead (DA) market. The operation schedule of the components in the VPP is also optimized to achieve the highest profit for the VPP. In the bi-level optimization problem, the upper-level model is maximizing the VPP’s profit while the lower-level model is the DA market-clearing problem. The bi-level optimization problem is formulated as a Mathematical Problem with Equilibrium Constraints (MPEC), reformulated to a Mixed Integer Linear Problem (MILP), then solved by GAMS and CPLEX. This study applies the bi-level optimization model to a test VPP system, including wind plants (WP), solar plants (PV), biogas energy plants (BG), ESSs, and several customers. The maximum power outputs of WP and PV are 100MW and 90MW, respectively. The total installed capacity of BG is 70MW, while the ESS’ rated capacity is 100MWh. The local customers have the highest total consumption of 100MW. In addition to the VPP, four GENCOs and three retailers participate in the DA market. The results show that the market-clearing price varies depending on the participants’ production/consumption quantity and offering/bidding price. However, based on the optimization model, the VPP can take full advantage of WP and PV available power output, choose the right time to operate BG, then obtain the highest profit. The results also show that with the ESS’ rated capacity of 100MWh, the ESS’ rated discharging/charging power increased from 10MW to 50MW will increase VPP’s profit from 45987$ to 49464$. The obtained results show that the proposed model has practical significance
日前市场上定价商虚拟电厂的报价策略
随着可再生能源(RES)的快速增长,虚拟发电厂模型(VPP)已被开发出来,用于集成可再生能源、储能系统(ESS)和当地客户,以克服可再生能源的缺点。当VPP的容量足够大时,它可以作为价格制定者而不是价格接受者参与电力市场,以获得更高的利润。本研究提出了一个双层优化模型来确定价格制定者VPP在日前市场(DA)中的最优交易策略。VPP中组件的运行时间表也经过优化,以实现VPP的最高利润。在双层优化问题中,上层模型是VPP的利润最大化问题,而下层模型是DA市场清算问题。将双层优化问题转化为平衡约束数学问题(MPEC),转化为混合整数线性问题(MILP),然后用GAMS和CPLEX求解。本研究将双层优化模型应用于测试VPP系统,包括风力发电厂(WP)、太阳能发电厂(PV)、沼气发电厂(BG)、ESS和几个客户。WP和PV的最大输出功率分别为100MW和90MW。BG的总装机容量为70MW,而ESS的额定容量为100MWh。本地客户的总功耗最高,为100MW。除了VPP,还有四家GENCO和三家零售商参与DA市场。结果表明,市场清算价格随参与者的生产/消费数量和出价/出价而变化。然而,基于优化模型,VPP可以充分利用WP和PV的可用功率输出,选择合适的时间运行BG,从而获得最高的利润。结果还表明,当ESS的额定容量为100MWh时,ESS的额定放电/充电功率从10MW增加到50MW,VPP的利润将从45987$增加到49464$。结果表明,该模型具有一定的实用意义
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.50
自引率
16.00%
发文量
83
审稿时长
8 weeks
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