A control architecture for optimal power sharing among interconnected microgrids

Sampath, L. P. Mohasha Isuru; Krishnan, Ashok; Chaudhari, Kalpesh; Gooi, Hoay Beng; Ukil, Abhisek

doi:10.1109/pesgm.2017.8274333

Cited by 7 publications

(14 citation statements)

References 14 publications

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“…Renewable energy sources such as solar photovoltaic (PV) and wind power plants are included as components of the MGs which are modelled in this paper. The operating costs of these RESs are assumed to be 0 [16]. The following paragraphs describe the modelling of the solar PV and wind power plants.…”

Section: Renewable Energy Sourcesmentioning

confidence: 99%

“…As the system load demand varies with time, it is essential to solve the OPF problem within a reasonable time. However, OPF is a nonconvex, nonlinear optimization problem which is NP-hard to solve [16]. Global optimization procedures to solve the OPF problem are computationally expensive.…”

Section: Stage 2: Optimal Power Flow Optimal Power Flow (Opf)mentioning

confidence: 99%

“…The authors of [15] proposed a jump and shift method for integrating the UC and OPF problems while including BESSs and RESs in the network. This approach was adapted for a multimicrogrid scenario in the authors' recent work [16]. However, these works do not consider load management strategies in the problem formulation.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

et al. 2018

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This paper proposes an efficient energy management system (EMS) for industrial microgrids (MGs). Many industries deploy large pumps for their processes. Oftentimes, such pumps are operated during hours of peak electricity prices. A lot of industries use a mix of captive generation and imported utility electricity to meet their energy requirements. The MG considered in this paper includes diesel generators, battery energy storage systems, renewable energy sources, flexible loads, and interruptible loads. Pump loads found in shipyard dry docks are modelled as exemplar flexible industrial loads. The proposed EMS has a two-stage architecture. An optimal MG scheduling problem including pump scheduling and curtailment of interruptible loads (ILs) is formulated and solved in the first stage. An optimal power flow problem is solved in the second stage to verify the feasibility of the MG schedule with the network constraints. An iterative procedure is used to coordinate the two EMS stages. Multiple case studies are used to demonstrate the utility of the proposed EMS. The case studies highlight the efficacy of load management strategies such as pump scheduling and curtailment of ILs in reducing the total electricity cost of the MG.

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Section: Renewable Energy Sourcesmentioning

confidence: 99%

Section: Stage 2: Optimal Power Flow Optimal Power Flow (Opf)mentioning

confidence: 99%

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Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

et al. 2018

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“…Furthermore, the iterative procedure in [59] also included a provision to account for the MG network losses in the optimal scheduling problem. The author's previous work in [60] adapted and modified the jump and shift approach in [59] to perform the optimal scheduling of a multi-MG system while also permitting the trading of energy between the individual MGs constituting the multi-MG system. of Singapore's electricity is produced using natural gas.…”

Section: Network Constraintsmentioning

confidence: 99%

“…The following constraints need to be considered while operating TESS p: [60]. The modelling of the solar PV and wind power plants is briefly outlined in the following paragraphs.…”

Section: Battery Energy Storage Systemmentioning

confidence: 99%

Optimal scheduling of energy systems incorporating load management schemes

Krishnan¹

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Framework for Network-Constrained Cooperative Trading of Multi-Microgrid Systems

Isuru

Krishnan

Foo

et al. 2020

2020 59th IEEE Conference on Decision and Control (CDC)

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The rising penetration of renewable energy sources (RESs) has led to increased research interest in the optimal scheduling and management of multi-microgrid (MMG) systems. This is due to the potential economic benefits which can be derived from the sharing of resources between the MGs which constitute the MMG. Advanced optimization procedures such as robust optimization (RO) frameworks have been proposed in the literature to handle any uncertainties caused by the stochastic nature of the RES generation, the load demand, and the electricity prices. However, the existing works in the literature do not consider the nonlinear network constraints of individual MGs which might significantly impact the power balance and the power sharing between MGs in MMG systems. This paper proposes a cooperative trading scheme including a two-stage network-constrained robust energy management system to optimize the resource utilization within each MG and the sharing of resources between the constituent MGs of a MMG system. The results clearly highlight the performance of the proposed approach and the impact of including the AC network constraints on the optimal dispatch of the MMG system under varying uncertainties.

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A control architecture for optimal power sharing among interconnected microgrids

Cited by 7 publications

References 14 publications

Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

Optimal Scheduling of a Microgrid Including Pump Scheduling and Network Constraints

Optimal scheduling of energy systems incorporating load management schemes

Framework for Network-Constrained Cooperative Trading of Multi-Microgrid Systems

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