Storage-integrated virtual power plants for resiliency enhancement of smart distribution systems

Piltan, Ghasem; Pirouzi, Sasan; Azarhooshang, Alireza; Jordehi, Ahmad Rezaee; Paeizi, Ali; Ghadamyari, Mojtaba

doi:10.1016/j.est.2022.105563

Cited by 74 publications

(31 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, the presence of renewable energy sources (RESs) such as wind and photovoltaics (PV) systems in the power system has grown significantly in recent years [2]. Also, storage devices and energy management programs such as demand response program (DRP) can assist in peak shaving and thus the energy demand from the upstream network or power plants is decreased, and this plays an effective role in reducing environmental pollutant emission from power plants [2]. Therefore, an EH is expected to contain these elements.…”

Section: Motivationmentioning

confidence: 99%

“…In constraints (7) and ( 8), the limitation of electrical output (active power generation) and heat output (heat power generation) are modelled, respectively [3]. The formulation of EES operation is mentioned in Equations ( 9)-( 11) [2,66], and the limitation of its charge and discharge rate is modelled in constraints ( 9) and (10), respectively. Also, the limit of the energy that can be stored in it is found according to constraint (11) [16].…”

Section: Upper-level Problemmentioning

confidence: 99%

“…It prevents the simultaneous operation of charging and discharging, so that if they have a value of zero (1) [3,16], that means that the storage devices are in the discharging (charging) operation mode. Formulation of DRP for electricity, heat, and gas consumers in the EH is as described in constraints ( 15)-( 20) [2]. Note that the sector uses incentive-based DRP, which is based on price signals [2].…”

Section: Upper-level Problemmentioning

confidence: 99%

“…Formulation of DRP for electricity, heat, and gas consumers in the EH is as described in constraints ( 15)-( 20) [2]. Note that the sector uses incentive-based DRP, which is based on price signals [2]. So, if the price of energy has the highest (lowest) value, consumers based on DRP reduce (increase) their energy consumption compared to the case without DRP.…”

Section: Upper-level Problemmentioning

confidence: 99%

“…So, if the price of energy has the highest (lowest) value, consumers based on DRP reduce (increase) their energy consumption compared to the case without DRP. Since high (low) energy prices correspond to peak (off-peak) hours [26], consumers in this DRP shift their energy consumption from peak to off-peak hours [2]. Therefore, constraints (15)- (17) expresses the control range of consumers power in the DRP [2].…”

Section: Upper-level Problemmentioning

confidence: 99%

See 4 more Smart Citations

Participation of energy hubs in the market clearing price‐based energy market considering generation and consumption uncertainty modelling

Farsani

Joorabian

Mortazavi

2023

IET Renewable Power Gen

View full text Add to dashboard Cite

The market clearing pricing (MCP) model is used to operate electricity, gas, and heating networks (EGHNs) with flexible energy hubs (EHs) in the day‐ahead energy market. It's two‐level optimization. Its higher level refers to EHs' participation in the market and their profit maximization bound by the operational model of power sources, storage devices, and responsive loads in the form of EHs and their flexibility limit. In the lower‐level problem, the MCP model calculates energy price and evaluates EH performance's effects on the networks' technical and economic indices. It optimizes power flow in the networks to reduce centralized generator operating costs. This approach is linear approximation. Unscented transformation (UT) model load and renewable power uncertainties. This technique contains the fewest situations, reducing issue volume and computing time. Benders decomposition (BD) technique calculates energy prices, EHs, and networks. Finally, the numerical results show that the proposed scheme can extract the optimal economic and flexibility states of EHs. EHs' optimal performance enhanced energy networks' economic and operating status compared to power flow studies and promoted societal welfare by lowering energy prices.

show abstract

Section: Motivationmentioning

confidence: 99%

Section: Upper-level Problemmentioning

confidence: 99%

Section: Upper-level Problemmentioning

confidence: 99%

Section: Upper-level Problemmentioning

confidence: 99%

Section: Upper-level Problemmentioning

confidence: 99%

See 3 more Smart Citations

Participation of energy hubs in the market clearing price‐based energy market considering generation and consumption uncertainty modelling

Farsani

Joorabian

Mortazavi

2023

IET Renewable Power Gen

View full text Add to dashboard Cite

show abstract

Sizing of storage‐based renewable off‐grid system according to supply of electrical and thermal energies considering unscented transformation‐based stochastic optimization: A case study

Bahmani,

Kiani,

Nejatian

et al. 2024

Optim Control Appl Methods

View full text Add to dashboard Cite

The paper presents the planning (sizing) of a hybrid islanded system containing only renewable sources including wind turbines, photovoltaics, and bio‐waste energy units for the simultaneous supply of electrical and thermal energy. The mentioned renewable sources are used to supply electrical energy. The bio‐waste unit (BEU) is equipped with combined electrical and thermal technology. It is used along with heat pumps to supply thermal energy. Electrical and thermal storage are employed to make the renewable power output as close as possible to the demand level. Electric storage can be either stationary (e.g., battery) or mobile (e.g., electric vehicles), but thermal storage is as stationary type of storage. In the following, the proposed scheme minimizes construction and maintenance costs imposed by power sources, storage devices, and power electronic converters, and expected storage degradation cost. This plan is bound to the model of operation of sources, storage devices, and power electronic converters. In this model, renewables are the main source of power to supply consumers, where storage is adopted to increase the generation level to make it as close as possible to the demand curve. The uncertain parameters are imposed by the load, renewable phenomena, and mobile storage parameters. To model these uncertainties, stochastic optimization based on unscented transformation is used. Finally, the findings of the paper demonstrate that the suggested scheme succeeds in the economic planning of the system with a simultaneous supply of electrical and thermal energy. The BEU equipped with a combined electricity and heat system along with thermal storage and a heat pump to supply thermal load besides providing electric energy can reduce the planning cost by 2.9% compared with the case with only electrical energy. Also, the mobile storage presence in the hybrid system can reduce the number of stationary storage devices, which alone results in a 7.7% decrease in the planning cost of the hybrid system.

show abstract

Resiliency-constrained placement and sizing of virtual power plants in the distribution network considering extreme weather events

Zadehbagheri,

Dehghan,

Kiani

et al. 2024

Electr Eng

View full text Add to dashboard Cite

Storage-integrated virtual power plants for resiliency enhancement of smart distribution systems

Cited by 74 publications

References 54 publications

Participation of energy hubs in the market clearing price‐based energy market considering generation and consumption uncertainty modelling

Participation of energy hubs in the market clearing price‐based energy market considering generation and consumption uncertainty modelling

Sizing of storage‐based renewable off‐grid system according to supply of electrical and thermal energies considering unscented transformation‐based stochastic optimization: A case study

Resiliency-constrained placement and sizing of virtual power plants in the distribution network considering extreme weather events

Contact Info

Product

Resources

About