Behnam Akbari


Last Name

Akbari

First Name

Behnam

ORCID

0000-0002-1242-7605

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2021 - 202511
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Publications 1 - 10 of 11
  • Gas Flow Models and Computationally Efficient Methods for Energy Network Optimization
    Item type: Journal Article
    Akbari, Behnam; Gabrielli, Paolo; Sansavini, Giovanni (2024)
    Industrial & Engineering Chemistry Research
    The equations governing gas flow dynamics are computationally challenging for energy network optimization. This paper proposes an efficient solution procedure to enable tractability for an hourly resolved yearly decision horizon. The solution procedure deploys linear and second-order cone gas flow models alternatively based on the length-diameter ratio of pipes, achieving maximum efficiency within accuracy limits. Moreover, it addresses the computational complexity of bidirectional pipe flows by fixing the associated integer variables according to a preceding optimization with a static flow approximation. The procedure also precisely aggregates parallel and serial pipes for increased efficiency. Mathematical derivations and single-pipe analyses substantiate the model selection criterion. Network optimizations validate the accuracy, success rate, and scalability of the procedure, achieving up to 3.1% cost savings compared to static models, enhancing the success rate by a minimum of 96%, and boosting computational efficiency up to 3 orders of magnitude over full dynamic models.
  • Computationally efficient gas flow models for energy system optimization
    Item type: Conference Poster
    Akbari, Behnam; Gabrielli, Paolo; Sansavini, Giovanni (2023)
  • Flexibility provision in the Swiss integrated power, hydrogen, and methane infrastructure
    Item type: Journal Article
    Akbari, Behnam; Garrison, Jared; Raycheva, Elena; et al. (2024)
    Energy Conversion and Management
    The renewable energy transition hinges on balancing energy supply and demand across seasons. This paper investigates the potential flexibility of Switzerland’s integrated power, hydrogen, and methane infrastructure to balance temporal mismatches while complying with national energy policies for sustainability and security. It develops an optimization method for energy system expansion and operation planning, filling crucial research gaps by (1) explicitly modeling power and gas transmission networks to guide technology placement and pinpoint network expansions, and (2) incorporating flexibility in power demand via shedding and shifting and in hydrogen and methane demands via price elasticity. The findings suggest that a 6.7-fold capacity expansion of variable renewables (i.e., photovoltaic, wind, run-of-river) by 2050 offsets nuclear phase-out and demand growth. The winter power gap is filled by power imports, hydropower generation, and gas turbines fueled by cost-effective hydrogen or methane imports. However, fuel embargoes escalate winter hydrogen and methane prices, reducing demand by 3.8%–10.4% and increasing domestic fuel production from biomass and excess renewable power in summer. To bridge the seasonal hydrogen and methane supply–demand gaps, up to 1.9 terawatt-hours of gas cavern storage is deployed in geologically viable locations, while costly tank storage plays a minor role. Power-to-gas requirements and power trade restrictions necessitate further renewable expansion, including 8.0 to 9.5 gigawatts of wind installations.
  • Assessing Maximum Grid Loadability Under PV Deployment for Distribution Planning Support: A Swiss Case Study
    Item type: Conference Paper
    Kopka, Tim; Akbari, Behnam; Oneto, Alfredo Ernesto; et al. (2025)
    IET Conference Proceedings ~ CIRED 2024 Vienna Workshop
    The increasing integration of low-carbon technologies, such as solar photovoltaics (PV) and heat pumps, impacts the operational margins of distribution grids. This paper quantifies the margins to voltage violation and line overloading by calculating the maximum grid loadability (MGL). We quantify this metric for 873 inferred Swiss medium-voltage grids and investigate the effect of rooftop PV and heat pump deployment by 2040. Results show a median MGL increase of 4.8% due to PV in summer and a median decrease of 11.1% due to heat pumps in winter. Overall, MGL is projected to increase by 14.0% until 2040, primarily driven by efficiency measures decreasing conventional loads. We highlight grid diversity, flexibility, energy efficiency, and winter peak as distribution planning considerations influencing operational margins.
  • Modeling Flexibility in Integrated Power and Gas Networks for Sustainable Energy Systems
    Item type: Doctoral Thesis
    Akbari, Behnam (2024)
    The energy landscape is rapidly evolving to mitigate climate change. Variable renewable energy (VRE) sources are proliferating, with the global share of wind and solar power generation expected to increase from 12% in 2023 to 40% by 2030 to achieve carbon neutrality by mid-century. Concurrently, electrification initiatives in transportation and heating sectors are set to displace fossil fuels, facilitated by the adoption of electric vehicles and heat pumps. Sustainable bio- and electrofuels, such as hydrogen, are crucial for reducing greenhouse gas emissions in hard-to-abate sectors, where electrification is challenging. The energy transition necessitates strategic investments and operational innovations to ensure energy supply security amidst evolving challenges. The increasing share of VREs requires extensive upgrades to power distribution networks and the establishment of new power transmission corridors. Similarly, realizing hydrogen's decarbonization potential hinges on significant investments in low-carbon hydrogen production, transport, and storage infrastructure. The growing VRE penetration heightens power system flexibility requirements, driving the need for innovations such as demand response and battery storage for short-term flexibility and hydrogen storage for long-term flexibility. This thesis addresses these challenges in sector-coupled energy system planning through accurate representations of energy networks and flexible energy resources.
  • Short Term Security Assessment Of Natural Gas Supply In European Union And Policy Insights
    Item type: Conference Paper
    Akbari, Behnam; Zhang, Chao; Sansavini, Giovanni (2024)
    Advances in Reliability, Safety and Security: ESREL 2024 Contributions. Part 1
    This paper assesses the security of natural gas supply in the European Union (EU) during the 2023/24 winter in the aftermath of the 2022 Russian gas disruption. We develop an optimization framework with a network model capturing intra- and inter country constraints and incorporating recent EU measures to enhance supply security. Our findings underscore the significance of increased liquefied natural gas (LNG) imports and gas storages in keeping the annual demand reduction below 15% across most EU countries. This demonstrates the efficacy of the EU's 15% voluntary demand reduction target in avoiding involuntary demand reduction. Increased LNG imports largely substitute pipeline imports from Russia, especially in Finland, Greece, and Poland. Nevertheless, regions such as Central Europe, Denmark, and Sweden may face involuntary demand reduction, necessitating network capacity enhancements as a potential mitigation strategy.
  • Changing energy mix and its impact on grid stability
    Item type: Educational Material
    Sansavini, Giovanni; Gabrielli, Paolo; Gjorgiev, Blazhe; et al. (2021)
  • Sequential Second-Order Cone Programming for AC Load Maximization Problems
    Item type: Conference Paper
    Akbari, Behnam; Sansavini, Giovanni (2022)
    2022 IEEE 7th International Energy Conference (ENERGYCON)
    AC load maximization problems are challenging to solve in their nonconvex form. Second-order cone programming relaxations facilitate an efficient solution but often result in infeasible solutions especially for meshed networks. This paper proposes a sequential convex programming procedure to recover feasibility by augmenting the relaxed problem with linearized branch and voltage angle constraints. Systematic experiments on radial and meshed networks are designed to identify the effective formulations of constraints. The quantitative results certify the efficacy of the proposed procedure in retrieving near-global solutions for a wide range of test cases. Comparison with established nonlinear solvers reveals the computational superiority of the proposed procedure, which is especially important in making timely maximal load delivery decisions.
  • Adaptive robust AC optimal power flow considering intrahour uncertainties
    Item type: Journal Article
    Akbari, Behnam; Sansavini, Giovanni (2023)
    Electric Power Systems Research
    Given the increasing share of variable renewable energy resources (VREs), power system operations need to account for the associated uncertainty with a fine resolution. This paper formulates an adaptive robust optimal power flow, which secures the hourly schedule against uncertain intrahour power injections. The uncertainty is characterized by spatially correlated polytopic sets. Second-order cone programming relaxation is employed to address the nonconvexity of power flow constraints. A sequential convex programming (SCP) procedure is developed to close the relaxation gaps. Due to convexity, the vertices fully represent the uncertainty sets, which alleviates the computational complexity stemming from full recourse. The effectiveness of the proposed solution framework is verified on 14-, 118-, and 588-bus systems with 80% VRE penetration and various uncertainty sizes. The SCP procedure recovers high-quality AC-feasible solutions in 3–17 iterations within 0.1%–41.4% of the planning horizon time span, which makes it suitable for practical use. The robust optimization can prevent load shedding and reduce operational costs by 2.0%–13.6%, while incurring 2.5%–5.0% reduction in VRE utilization.
  • Robust scheduling of integrated electricity and gas systems: A cost and flexibility assessment
    Item type: Journal Article
    Akbari, Behnam; Sansavini, Giovanni (2024)
    International Journal of Electrical Power & Energy Systems
    Gas-fired generators and power-to-gas units support the deployment of variable renewable energy in integrated electricity and gas systems (IEGS) by absorbing the fluctuations in electricity generation and demand. The economical and secure operation of IEGSs with high variable renewable energy penetration requires coordinated uncertainty-aware decision support. This paper proposes an adaptive robust optimization for IEGS scheduling, which minimizes the base-case costs, while ensuring security against generation and demand uncertainties with full-recourse rescheduling. The AC power flow and dynamic gas flow equations are convexified using second-order cone relaxations and treated by sequential convex programming to recover feasible solutions. We assess the flexibility of the solutions in response to the realized uncertainties. Computational experiments on the modified IEEE 39-bus system and the Swiss natural gas system show that sequential convex programming reduces demand shedding by 79%–100% and variable renewable energy curtailment by 1%–68%. Robust scheduling prevents demand shedding at 1%–7% additional cost due to the need for additional generation from conventional generators. Power-to-gas enhances variable renewable energy utilization by synthesizing methane from excess renewable energy, especially when the system lacks other flexible resources.
Publications 1 - 10 of 11