An Optimal Dispatch Algorithm for Managing Residential Distributed Energy Resources

Karami, Hossein; Sanjari, M. J.; Hosseinian, Seyed Hossein; Gharehpetian, Gevork B.

doi:10.1109/tsg.2014.2325912

Cited by 123 publications

(80 citation statements)

References 18 publications

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“…In general, microgrids management is carried out by heuristic algorithms [11], [12], although there are applications that use MPC strategies, such as those presented in [13] and [14].…”

Section: Introductionmentioning

confidence: 99%

The use of Model Predictive Control (MPC) in the optimal distribution of electrical energy in a microgrid located in southeastern of Spain: A case study simulation

Hernández-Hernández¹,

Rodríguez²,

Moreno³

et al. 2017

REPQJ

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Abstract.The microgrids allow the integration of renewable sources of energy such as solar and wind and distributed energy resources such as combined heat and power, energy storage, and demand response. In addition, the use of local sources of energy to serve local loads helps reduce energy losses in transmission and distribution, further increasing efficiency of the electric delivery system. In this paper, the optimization problem of the energy in a microgrid (MG) located in southeastern of Spain, with Energy Storage System (ESS), which exchanges energy with the utility grid is developed using Model Predictive Control techniques. System modelling use the methodology of the Energy Hubs. The MPC techniques allow maximizing the economic benefit of the microgrid and to minimize the degradation of storage system.

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“…In general, microgrids management is carried out by heuristic algorithms [11], [12], although there are applications that use MPC strategies, such as those presented in [13] and [14].…”

Section: Introductionmentioning

confidence: 99%

The use of Model Predictive Control (MPC) in the optimal distribution of electrical energy in a microgrid located in southeastern of Spain: A case study simulation

Hernández-Hernández¹,

Rodríguez²,

Moreno³

et al. 2017

REPQJ

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show abstract

“…Many studies have examined ESSs to utilize renewable integration, peak shaving, ancillary services, and microgrids [1][2][3][4][5][6][7][8][9][10]. In [11], the authors presented the feasibility of an ESS for the operation of an island AC microgrid with photovoltaic generation.…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

Yang

Choi

et al. 2016

Energies

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An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge (SOC) range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC) signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This algorithm compensates for SOC errors by changing the base point of the ESS. The optimal scheduling algorithm is implemented in MATLAB by using the particle swarm optimization (PSO) method. In addition, changes in the SOC when the ESS performs frequency regulation in a real-time operation are confirmed using the PSCAD/EMTDC tool. The simulation results show that the optimal scheduling algorithm manages the SOC more efficiently than a commonly employed planning method. In addition, the proposed real-time SOC management algorithm is confirmed to be capable of performing SOC recovery.

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“…In this paper, simultaneous consideration of cable aging and voltage profile is investigated, by optimal siting and sizing of DSTATCOMs. Many optimization algorithms have been introduced and applied in the engineering problems [7][8][9][10][11][12]. In this paper, Biogeography Based Optimization (BBO) algorithm [13] is used to find the optimal sites and sizes of DSTATCOMs to improve voltage profile in the distribution network, considering cable aging issues.…”

Section: Introductionmentioning

confidence: 99%

Application of Biogeography Based Optimization Algorithm in Voltage Profile Improvement of Distribution Network by using DSTATCOM Considering Cable Aging Constraint

Ahmadi¹,

Karami²,

Vahidinasab³

et al. 2016

REPQJ

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Abstract:In this paper, Biogeography Based Optimization (BBO) algorithm is used to improve voltage profile of the distribution networks considering cable aging constraint and optimal siting and sizing of DSTATCOMs. Recently, researchers show the importance of cable aging effects in the planning of power systems. Cable aging mostly happens due to metallic structure of power equipment such as cable sheathing erosion. Decreasing reliability of the system and higher risk of failure are some results of cable aging. In order to overcome this issue in power system, one of the best methods is the reduction of cable current flow by installing Flexible Alternating Current Transmission System (FACTS) devices. FACTS devices can help to overcome the hazards that happen in the operation stage of power systems. In this regard, Distributed Static Compensator (DSTATCOM) is used here. The IEEE 33-bus standard network is used in our experimental studies as the test system and load flow calculations are carried out by Backward/Forward sweep method in this work. Three scenarios are investigated in the simulation and the BBO algorithm is used to find optimal sites and sizes for each scenario. The results obtained from BBO, show the privilege of the proposed method.

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An Optimal Dispatch Algorithm for Managing Residential Distributed Energy Resources

Cited by 123 publications

References 18 publications

The use of Model Predictive Control (MPC) in the optimal distribution of electrical energy in a microgrid located in southeastern of Spain: A case study simulation

The use of Model Predictive Control (MPC) in the optimal distribution of electrical energy in a microgrid located in southeastern of Spain: A case study simulation

Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

Application of Biogeography Based Optimization Algorithm in Voltage Profile Improvement of Distribution Network by using DSTATCOM Considering Cable Aging Constraint

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