Optimal Operation of a real Power Hub based on PV/FC/GenSet/BESS and Demand Response under Uncertainty

Kermani, Mostafa; Shirdare, Erfan; Najafi, Arsalan; Adelmanesh, Behin; Carnì, Domenico Luca; Martirano, Luigi

doi:10.1109/ias44978.2020.9391570

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…In the investigated local energy communities the uncertainties of PV production and load could be included and solved by e.g. information gap decision theory [39], [40], stochastic programming [41] or robust optimization [42].…”

Section: Discussionmentioning

confidence: 99%

A Heuristic Method to Calculate the Capacity of Residential PV-BESS in Providing Upward Flexibility Services in Energy Communities

Burgio¹,

Cimmino²,

Jasiński

et al. 2022

IEEE Access

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This paper proposes a heuristic method for calculating the capacity of a set of residential photovoltaic-battery systems in providing upward flexibility services to the grid in an energy communities framework. The proposed method has been designed to calculate the upward service capacity in a few minutes, assuming a scenario where the grid operator urgently needs an upward service in a specific area. The proposed method calculates the service capacity by exploiting the PV overgeneration and the state of charge of batteries, adopting a distributed approach. If the service capacity varies relevantly over time, a centralized approach is considered allowing the service capacity to remain constant over time. An algorithm is provided that implements the proposed heuristic method that can be easily translated into a software code and solved even in the absence of specific skills and expensive high-level computational tools, i.e. using costeffective single-board computers. The main benefits and advantages of the proposed method are due to its applicability in real-time problems and to its simplicity which makes it easy to be translated into software code and solved even in the absence of specific skills and high-level computational tools. Therefore, it is a simple and advantageous solution, especially for small energy communities. The numerical results demonstrate the effectiveness of the proposed method and algorithm, studying a set of four residential photovoltaic-battery systems and real input data. For this test case, the algorithm returns a flat service capacity of approximately 8 kW which remains perfectly constant for 1-hour. Lastly, the performance of the proposed heuristic method is compared with the solution of two optimization problems aiming at the same scope.

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Section: Discussionmentioning

confidence: 99%

A Heuristic Method to Calculate the Capacity of Residential PV-BESS in Providing Upward Flexibility Services in Energy Communities

Burgio¹,

Cimmino²,

Jasiński

et al. 2022

IEEE Access

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“…The application of SP techniques in a real microgrid with demand response capabilities is presented in [23].…”

Section: Resources a Review Of Related Cases And Approaches Followsmentioning

confidence: 99%

Operation and Planning of Energy Hubs Under Uncertainty—A Review of Mathematical Optimization Approaches

et al. 2023

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Co-designing energy systems across multiple energy carriers is increasingly attracting attention of researchers and policy makers, since it is a prominent means of increasing the overall efficiency of the energy sector. Special attention is attributed to the so-called energy hubs, i.e., clusters of energy communities featuring electricity, gas, heat, hydrogen, and also water generation and consumption facilities. Managing an energy hub entails dealing with multiple sources of uncertainty, such as renewable generation, energy demands, wholesale market prices, etc. Such uncertainties call for sophisticated decision-making techniques, with mathematical optimization being the predominant family of decision-making methods proposed in the literature of recent years. In this paper, we summarize, review, and categorize research studies that have applied mathematical optimization approaches towards making operational and planning decisions for energy hubs. Relevant methods include robust optimization, information gap decision theory, stochastic programming, and chance-constrained optimization. The results of the review indicate the increasing adoption of robust and, more recently, hybrid methods to deal with the multi-dimensional uncertainties of energy hubs.

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“…The authors have presented a bi-level model in [4] to minimise the total costs of an isolated microgrid and maximise the revenues of a storage system using a DR scheme. Mathematical optimisation models in a real energy hub considering demand response under uncertainties have been proposed in [5,6] to minimise the operation costs. Linear and non-linear optimisation models have been proposed in [7,8] to assess the economic feasibility of providing DR programs by hydrogen production units and their effect on power system flexibility.…”

Section: Introductionmentioning

confidence: 99%

Optimal price-based and emergency demand response programs considering consumers preferences

Dadkhah

Bayati

Shafie‐khah

et al. 2022

International Journal of Electrical Power & Energy Systems

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Optimal Operation of a real Power Hub based on PV/FC/GenSet/BESS and Demand Response under Uncertainty

Cited by 4 publications

References 16 publications

A Heuristic Method to Calculate the Capacity of Residential PV-BESS in Providing Upward Flexibility Services in Energy Communities

A Heuristic Method to Calculate the Capacity of Residential PV-BESS in Providing Upward Flexibility Services in Energy Communities

Operation and Planning of Energy Hubs Under Uncertainty—A Review of Mathematical Optimization Approaches

Optimal price-based and emergency demand response programs considering consumers preferences

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