A comparison between central- and self-dispatch storage management principles in island systems

Psarros, Georgios N.; Dratsas, Pantelis A.; Papathanassiou, Stavros A.

doi:10.1016/j.apenergy.2021.117181

Cited by 13 publications

(7 citation statements)

References 51 publications

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“…On the other hand, if PV power output realized in real-time is less than the scheduled power, the generation of DG would have to be ramped up, or stored energy of BESS has to be discharged, or load shedding has to be implemented as a last measure. A mathematical model incorporating these conditions is shown in (20). This constraint consists of both here-and-now variables and wait-and-see variables.…”

Section: Constraints That Represent the Coordination Between Pv And Bessmentioning

confidence: 99%

“…The power from PV is represented by the realized forecast scenarios, P S tω , and the possible curtailment in the wait-and-see stage, P S cur tω . Load demand, in (20), consists of the point forecast of load demand, (P D t ), at the time, t, and the load not served, (P D ns tω ), depending on the scenario, ω.…”

Section: Constraints That Represent the Coordination Between Pv And Bessmentioning

confidence: 99%

“…The objective function of the proposed model in reference [17] is to maximize the profit earned from the hybrid power station since the model is from the station owner's perspective and not from the system operator's (SO). References [18][19][20] reported deterministic generation dispatch models wherein its power-output-point forecast represents RES. Hence, the optimal commitment and generation scheduling levels have not considered the uncertain characterization of a probabilistic forecast.…”

Section: Introductionmentioning

confidence: 99%

“…But since wind and pumped hydro storage facilities, the mathematical formulation is structured around the technical needs of pumped storage technologies. A summary of the literature survey for reference work [15][16][17][18][19][20][21][22][23][24] is shown in Table 1. Comparison of different optimal scheduling strategies shown in Table 1 suggests that a stochastic formulation with technical constraints supporting the inclusion of PV and BESS in insular grids has not been discussed to date to the best of our knowledge.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Stochastic Generation Scheduling of Insular Grids with High Penetration of Photovoltaic and Battery Energy Storage Systems: South Andaman Island Case Study

et al. 2022

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Insular grids are fragile owing to lower inertia and the absence of interconnection with other grids. With the increasing penetration of non-dispatchable renewable energy sources, the vulnerability of such insular grids increases further. The government of India has proposed several projects to improve the photovoltaic systems (PV) penetration in the Andaman and Nicobar Islands’ grid. This paper investigates joint stochastic scheduling of energy and reserve generation for insular grids fed from diesel and gas-based generators, PV, and battery energy storage systems (BESS). The proposed stochastic scheduling model considers a wide range of probabilistic forecast scenarios instead of a deterministic model that assumes a single-point forecast. Hence, it provides an optimal solution that is technically feasible for a wide range of PV power forecast scenarios. The striking feature of the model developed in this work is the inclusion of stochastic constraints that represent (i) the coordination between PV and BESS, (ii) reserve constraints, (iii) battery charging/discharging limit constraints, and (iv) non-anticipatory constraints that ensure technical viability of scheduling decisions. The proposed model is validated on the dataset for South Andaman Island. Results reveal the applicability and feasibility of the proposed stochastic dispatch model for different generation mix scenarios.

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Section: Constraints That Represent the Coordination Between Pv And Bessmentioning

confidence: 99%

Section: Constraints That Represent the Coordination Between Pv And Bessmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Stochastic Generation Scheduling of Insular Grids with High Penetration of Photovoltaic and Battery Energy Storage Systems: South Andaman Island Case Study

et al. 2022

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“…In order to improve the level of wind power consumption, this paper establishes the model by means of effective cooperation between the energy-intensive load and energy storage system. Wind farms are equipped with energy storage systems [28], relying on the peak-load shifting of the energy storage systems to improve system flexibility and reduce wind curtailment rate.…”

Section: Model Of Energy Storage Capacity Configurationmentioning

confidence: 99%

The Bi-Level Optimization Model Research for Energy-Intensive Load and Energy Storage System Considering Congested Wind Power Consumption

Zhang

et al. 2021

Processes

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Due to the uncertainty of wind power output, the congestion of wind power has become prominent. Exactly how to improve the capacity of wind power consumption has become a problem that needs to be studied urgently. In this paper, an energy storage system and energy-extensive load with adjustable characteristics are used as an important means of consuming wind power. Firstly, we analyze the reasons for the congestion according to the characteristics of wind power output, and establish a model of the grid’s ability to integrate wind power based on the concept of a wind power admissible interval. Secondly, we analyze the energy-extensive load regulation characteristics and establish an energy-extensive load dispatch model. Thirdly, on the basis of considering the energy-extensive load and energy storage system adjustment constraints, a bi-level optimization model is established. The upper level determines the configured capacity of the energy storage system with the goal of minimizing the total economic investment of the energy storage system, and the lower level coordinates the dispatching with the goal of maximizing wind power consumption and minimizing system operating costs. Finally, a certain region is taken as an example to verify the validity of the proposed method.

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Energy‐Sharing Economy with Renewable Integration and Management in Communities—a State‐of‐the‐Art Review

Zhou

2024

Adv Energy and Sustain Res

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Climate change and extreme weather events impose urgent necessities on distributed energy systems with energy flexibility and resilience to survive the district power supply systems. Compared to centralized energy systems, distributed energy systems show more superiorities in power shifting, fast demand response, regional energy allocations, and so on. However, electrification transformation‐ enabled flexible energy sharing, smart energy integration, and advanced management are still in their infancy stages, with unsolved but urgent issues, like large‐scale energy system planning and optimization, energy trading and pricing mechanisms, so on. In this study, energy‐sharing economy with renewable integration and management in communities has been comprehensively reviewed. The “source–grid–load–storage” framework has been implemented on district energy systems with complex relationships among the energy supply–storage–transmission–distribution chain. Roles of energy sharing, integration, and management on energy system sustainability have been provided. Considering widely installed large‐scale renewable energy systems, planning and optimization platforms and tools are provided to guide the distributed/centralized system planning and accurate capacity sizing. Results showed that, multi‐directional power interactions with electrification in buildings and E‐mobility spatiotemporal energy sharing and smart grids enable high renewable penetration, fast power response, energy supply reliability, etc. Unlike traditional fossil fuel‐based power plants, distributed renewable‐supported energy systems (like BIPVs, electric vehicles, etc.) enable emerging energy sharing, integration, and management for energy flexibility and resilience with fast response and energy survivals. Roles of advanced energy include power shifting, fast demand response, regional energy allocations, and so on. Electricity market liberalization can incentivize multi‐stakeholders’ proactivity and market vitality for distributed renewable energy spatiotemporal microgrids. Dynamic energy pricing for the shared power is dependent on the supply–demand relationship, and cost–benefit allocations among different stakeholders need to be investigated for justice and fairness. To avoid performance over or underestimations, advanced approaches are highly necessary for large‐scale energy system planning and optimization. Research results can pave paths for upcoming studies in urban energy system planning, design, and optimization with high energy efficiency and low carbon emissions through joint collaborations from highly economically incentivized participators.

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A comparison between central- and self-dispatch storage management principles in island systems

Cited by 13 publications

References 51 publications

Stochastic Generation Scheduling of Insular Grids with High Penetration of Photovoltaic and Battery Energy Storage Systems: South Andaman Island Case Study

Stochastic Generation Scheduling of Insular Grids with High Penetration of Photovoltaic and Battery Energy Storage Systems: South Andaman Island Case Study

The Bi-Level Optimization Model Research for Energy-Intensive Load and Energy Storage System Considering Congested Wind Power Consumption

Energy‐Sharing Economy with Renewable Integration and Management in Communities—a State‐of‐the‐Art Review

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