Mahir Oumaima, Rochd Abdelilah, Benazzouz Aboubakr, Ghennioui Hicham
Laboratory of Signals, Systems, and Components, FST Fez, University Sidi Mohamed Ben Abdellah, Fez, 30000, Morocco.
Green Energy Park, Benguerir, 43150, Morocco.
Heliyon. 2024 Oct 9;10(20):e39075. doi: 10.1016/j.heliyon.2024.e39075. eCollection 2024 Oct 30.
Incorporating renewable energy into forthcoming grid-connected or decentralized energy systems assumes an escalating significance and can potentially enhance endeavors toward accomplishing Sustainable Development Goal 7 (SDG7). Nevertheless, deploying sustainable renewable energy-intensive systems may present challenges related to their intermittency and cost instability. This paper proposes the development of a decision support model aimed at planning an optimal on-grid PV battery system. The model builds upon the Open Energy Modeling Framework (OEMOF) and defines asset capacities, energy dispatch, operational strategies, and optimal costs for the designated system. Key factors considered include energy demand profile, photovoltaic potential, electricity tariffs, and the availability of the National Grid. Furthermore, the model evaluation incorporates the computation of pertinent performance, feasibility, and viability indicators, notably the Levelized Cost of Energy (LCOE). To validate the framework, the article conducts a case study to determine the optimal sizing and planning of a grid-connected PV battery energy system. The objective is to cater to the electricity needs of an OCP (Office Chérifien des Phosphates) mining site in Morocco. The study considers the characteristics of the national power grid, incorporating time-varying electricity tariffs based on a Demand-Response program taking into account various rates according to the time of use (ToU). The case study includes a sensitivity analysis that examines different factors, namely the proportion of renewable energy, the investment costs of photovoltaic systems and batteries, and the financial parameter known as the weighted average cost of capital (WACC). Through this analysis, the study assesses the impact of these variables on the calculated cost of energy. Experimental results revealed a range of LCOE values from $0.07111/kWh to $0.11847/kWh for high renewable energies integration.
将可再生能源纳入即将到来的并网或分散式能源系统具有日益重要的意义,并有可能加强实现可持续发展目标7(SDG7)的努力。然而,部署可持续的可再生能源密集型系统可能会带来与其间歇性和成本不稳定相关的挑战。本文提出开发一种决策支持模型,旨在规划最优的并网光伏电池系统。该模型基于开放能源建模框架(OEMOF)构建,并定义了指定系统的资产容量、能源调度、运营策略和最优成本。考虑的关键因素包括能源需求曲线、光伏潜力、电价以及国家电网的可用性。此外,模型评估纳入了相关性能、可行性和可行性指标的计算,特别是平准化能源成本(LCOE)。为了验证该框架,文章进行了一个案例研究,以确定并网光伏电池能源系统的最优规模和规划。目标是满足摩洛哥OCP(摩洛哥磷酸盐公司)矿场的电力需求。该研究考虑了国家电网的特点,纳入了基于需求响应计划的时变电价,该计划根据使用时间(ToU)考虑了各种费率。案例研究包括敏感性分析,该分析考察了不同因素,即可再生能源的比例、光伏系统和电池的投资成本以及称为加权平均资本成本(WACC)的财务参数。通过该分析,研究评估了这些变量对计算出的能源成本的影响。实验结果显示,对于高可再生能源整合,LCOE值范围为0.07111美元/千瓦时至0.11847美元/千瓦时。