Energies

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18 pages, 3186 KiB

Open AccessArticle

Combined Optimal Planning and Operation of a Fast EV-Charging Station Integrated with Solar PV and ESS

by Leon Fidele Nishimwe H. and Sung-Guk Yoon

Energies 2021, 14(11), 3152; https://doi.org/10.3390/en14113152 - 28 May 2021

Cited by 32 | Viewed by 4099

Abstract

Sufficient and convenient fast-charging facilities are crucial for the effective integration of electric vehicles. To construct enough fast electric vehicle-charging stations, station owners need to earn a reasonable profit. This paper proposed an optimization framework for profit maximization, which determined the combined planning [...] Read more.

Sufficient and convenient fast-charging facilities are crucial for the effective integration of electric vehicles. To construct enough fast electric vehicle-charging stations, station owners need to earn a reasonable profit. This paper proposed an optimization framework for profit maximization, which determined the combined planning and operation of the charging station considering the vehicle arrival pattern, intermittent solar photovoltaic generation, and energy storage system management. In a planning horizon, the proposed optimization framework finds an optimal configuration of a grid-connected charging station. Besides, during the operation horizon, it determines an optimal power scheduling in the charging station. We formulated an optimization framework to maximize the expected profit of the station. Four types of costs were considered during the planning period: the investment cost, operational cost, maintenance cost, and penalties. The penalties arose from vehicle customers’ dissatisfaction associated with waiting time in queues and rejection by the station. The simulation results showed the optimal investment configuration and daily power scheduling in the charging station in various environments such as the downtown, highway, and public stations. Furthermore, it was shown that the optimal configuration was different according to the environments. In addition, the effectiveness of solar photovoltaic, energy storage system, and queue management was demonstrated in terms of the optimal solution through a sensitivity analysis. Full article

(This article belongs to the Special Issue Advanced System Operation and Market Design in Smart Grids)

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10 pages, 1703 KiB

Open AccessArticle

Data-Driven Evaluation for Demand Flexibility of Segmented Electric Vehicle Chargers in the Korean Residential Sector

by Keon Baek, Sehyun Kim, Eunjung Lee, Yongjun Cho and Jinho Kim

Energies 2021, 14(4), 866; https://doi.org/10.3390/en14040866 - 07 Feb 2021

Cited by 2 | Viewed by 2001

Abstract

The rapid spread of renewable energy resources has increased need for demand flexibility as one of the solutions to power system imbalance. However, to properly estimate the demand flexibility, demand characteristics must be analyzed first and the corresponding flexibility measures must be validated. [...] Read more.

The rapid spread of renewable energy resources has increased need for demand flexibility as one of the solutions to power system imbalance. However, to properly estimate the demand flexibility, demand characteristics must be analyzed first and the corresponding flexibility measures must be validated. Thus, in this study, a novel approach is proposed to evaluate the demand flexibility provided by Electric Vehicle Chargers (EVC) in the residential sector based upon a new process of electric charging demand characteristic data analysis. The proposed model estimates the frequency, consistency, and operation scores of the flexible demand resource (FDR) during identified ramp-up/down intervals presented in our previous work. The scores are included in the components that calculate the flexibility score referring that the closer it is to 1, the higher utilization as an FDR. A case study was conducted by considering EV user segmentation based on their demand characteristic analysis. The results confirm that flexibility scores of segmented EVC groups are about 0.0273 in ramp-up and ramp-down intervals. Based on the experimental results, the flexibility score can be utilized for multi-dimensional analysis and verification in perspectives of seasonality, participation time interval, customer group classification, and evaluation. Thus, the proposed method can be used as an indicator to determine how a segmented EVC group is adequate to participate as an FDR while suggesting meaningful implications through EVC demand data analysis. Full article

(This article belongs to the Special Issue Advanced System Operation and Market Design in Smart Grids)

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19 pages, 12800 KiB

Open AccessArticle

Economic Analysis of Special Rate for Renewable Energy Based on the Design of an Optimized Model for Distributed Energy Resource Capacities in Buildings

by Jihun Jung, Keon Baek, Eunjung Lee, Woong Ko and Jinho Kim

Energies 2021, 14(3), 645; https://doi.org/10.3390/en14030645 - 27 Jan 2021

Cited by 2 | Viewed by 1651

Abstract

Various incentive schemes are being implemented to improve the economic return of distributed energy resources (DERs). Accordingly, research on the optimal capacity design and operations of photovoltaic (PV) power generation and energy storage systems (ESSs) is important to ensure the economic efficiency of [...] Read more.

Various incentive schemes are being implemented to improve the economic return of distributed energy resources (DERs). Accordingly, research on the optimal capacity design and operations of photovoltaic (PV) power generation and energy storage systems (ESSs) is important to ensure the economic efficiency of DERs. This study presents the models of optimal capacity and facility operation methods based on long-term operational changes of DERs in a building with self-consumption. Key policy variables are derived for a renewable energy system. We first analyzed the operating environments of the DERs according to the basic types of PVs and ESSs, and by examining the detailed benefit structure of a special rate for renewable energy. The optimal capacity of PVs and ESSs with the lowest net cost was estimated using various parameters in consideration of long-term operations (~15 years), and by setting rules for a special rate for renewable energy. It was confirmed that the combined use of peak and rate reductions constituted the most economical operational approach. A case study confirmed the economic sensitivity of cost and benefit analyses based on actual load data. Correspondingly, it is inferred that this study will identify core policy variables that can aid decision-making in the long-term perspective. Full article

(This article belongs to the Special Issue Advanced System Operation and Market Design in Smart Grids)

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21 pages, 5271 KiB

Open AccessArticle

Optimal Operation Scheduling Considering Cycle Aging of Battery Energy Storage Systems on Stochastic Unit Commitments in Microgrids

by Yong-Rae Lee, Hyung-Joon Kim and Mun-Kyeom Kim

Energies 2021, 14(2), 470; https://doi.org/10.3390/en14020470 - 17 Jan 2021

Cited by 14 | Viewed by 2627 | Correction

Abstract

As renewable penetration increases in microgrids (MGs), the use of battery energy storage systems (BESSs) has become indispensable for optimal MG operation. Although BESSs are advantageous for economic and stable MG operation, their life degradation should be considered for maximizing cost savings. This [...] Read more.

As renewable penetration increases in microgrids (MGs), the use of battery energy storage systems (BESSs) has become indispensable for optimal MG operation. Although BESSs are advantageous for economic and stable MG operation, their life degradation should be considered for maximizing cost savings. This paper proposes an optimal BESS scheduling for MGs to solve the stochastic unit commitment problem, considering the uncertainties in renewables and load. Through the proposed BESS scheduling, the life degradation of BESSs is minimized, and MG operation becomes economically feasible. To address the aforementioned uncertainties, a scenario-based method was applied using Monte Carlo simulation and the K-means clustering algorithm for scenario generation and reduction, respectively. By implementing the rainflow-counting algorithm, the BESS charge/discharge state profile was obtained. To formulate the cycle aging stress function and examine the life cycle cost (LCC) of a BESS more realistically, the nonlinear cycle aging stress function was partially linearized. Benders decomposition was adopted for minimizing the BESS cycle aging, total operating cost, and LCC. To this end, the general problem was divided into a master problem and subproblems to consider uncertainties and optimize the BESS charging/discharging scheduling problem via parallel processing. To demonstrate the effectiveness and benefits of the proposed BESS optimal scheduling in MG operation, different case studies were analyzed. The simulation results confirmed the superiority and improved performance of the proposed scheduling. Full article

(This article belongs to the Special Issue Advanced System Operation and Market Design in Smart Grids)

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18 pages, 2317 KiB

Open AccessArticle

Data Driven Robust Energy and Reserve Dispatch Based on a Nonparametric Dirichlet Process Gaussian Mixture Model

by Li Dai, Dahai You and Xianggen Yin

Energies 2020, 13(18), 4642; https://doi.org/10.3390/en13184642 - 07 Sep 2020

Cited by 1 | Viewed by 1674

Abstract

Traditional robust optimization methods use box uncertainty sets or gamma uncertainty sets to describe wind power uncertainty. However, these uncertainty sets fail to utilize wind forecast error probability information and assume that the wind forecast error is symmetrical and independent. This assumption is [...] Read more.

Traditional robust optimization methods use box uncertainty sets or gamma uncertainty sets to describe wind power uncertainty. However, these uncertainty sets fail to utilize wind forecast error probability information and assume that the wind forecast error is symmetrical and independent. This assumption is not reasonable and makes the optimization results conservative. To avoid such conservative results from traditional robust optimization methods, in this paper a novel data driven optimization method based on the nonparametric Dirichlet process Gaussian mixture model (DPGMM) was proposed to solve energy and reserve dispatch problems. First, we combined the DPGMM and variation inference algorithm to extract the GMM parameter information embedded within historical data. Based on the parameter information, a data driven polyhedral uncertainty set was proposed. After constructing the uncertainty set, we solved the robust energy and reserve problem. Finally, a column and constraint generation method was employed to solve the proposed data driven optimization method. We used real historical wind power forecast error data to test the performance of the proposed uncertainty set. The simulation results indicated that the proposed uncertainty set had a smaller volume than other data driven uncertainty sets with the same predefined coverage rate. Furthermore, the simulation was carried on PJM 5-bus and IEEE-118 bus systems to test the data driven optimization method. The simulation results demonstrated that the proposed optimization method was less conservative than traditional data driven robust optimization methods and distributionally robust optimization methods. Full article

(This article belongs to the Special Issue Advanced System Operation and Market Design in Smart Grids)

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14 pages, 1812 KiB

Open AccessArticle

Cooperative Game-Based Synergistic Gains Allocation Methods for Wind-Solar-Hydro Hybrid Generation System with Cascade Hydropower

by Liqin Zhang, Jun XIE, Xingying CHEN, Yongsheng Zhan and Lv Zhou

Energies 2020, 13(15), 3890; https://doi.org/10.3390/en13153890 - 30 Jul 2020

Cited by 12 | Viewed by 1783

Abstract

In order to encourage hybrid generation of multiple wind/solar/hydro power stakeholders, synergistic gains from hybrid generation should be allocated fairly, efficiently and reasonably to all power stakeholders. This paper explores how cooperative game theory resolves conflicts among multiple wind/solar/hydro power stakeholders. Elaborate allocation [...] Read more.

In order to encourage hybrid generation of multiple wind/solar/hydro power stakeholders, synergistic gains from hybrid generation should be allocated fairly, efficiently and reasonably to all power stakeholders. This paper explores how cooperative game theory resolves conflicts among multiple wind/solar/hydro power stakeholders. Elaborate allocation processes of the nucleolus, Shapley value and MCRS methods are presented in resolve synergistic gains allocation problems of wind–solar–hydro hybrid generation system with cascade hydropower. By analyzing properties such as existence, uniqueness and rationality, we find that both the Shapley value and MCRS methods are fair, efficient and rational allocation methods whereas the nucleolus method is limited by reservoir volume of hydro power stakeholders. Analyses on computational feasibility show that the Shapley value method may induce combinational explosion problem with the integration of more power stakeholders. A further application in Yalong River basin demonstrates that, compared with the Shapley value method, the MCRS method significantly simplifies allocating process and improves computational efficiency. Therefore, the MCRS method is recommend as a fair, efficient, rational and computational feasible allocation method for hybrid generation system with large number of wind/solar/hydro power stakeholders. Full article

(This article belongs to the Special Issue Advanced System Operation and Market Design in Smart Grids)

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Review

Jump to: Research, Other

41 pages, 2466 KiB

Open AccessReview

A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources

by Ibrahim Alotaibi, Mohammed A. Abido, Muhammad Khalid and Andrey V. Savkin

Energies 2020, 13(23), 6269; https://doi.org/10.3390/en13236269 - 27 Nov 2020

Cited by 111 | Viewed by 10757

Abstract

The smart grid is an unprecedented opportunity to shift the current energy industry into a new era of a modernized network where the power generation, transmission, and distribution are intelligently, responsively, and cooperatively managed through a bi-directional automation system. Although the domains of [...] Read more.

The smart grid is an unprecedented opportunity to shift the current energy industry into a new era of a modernized network where the power generation, transmission, and distribution are intelligently, responsively, and cooperatively managed through a bi-directional automation system. Although the domains of smart grid applications and technologies vary in functions and forms, they generally share common potentials such as intelligent energy curtailment, efficient integration of Demand Response, Distributed Renewable Generation, and Energy Storage. This paper presents a comprehensive review categorically on the recent advances and previous research developments of the smart grid paradigm over the last two decades. The main intent of the study is to provide an application-focused survey where every category and sub-category herein are thoroughly and independently investigated. The preamble of the paper highlights the concept and the structure of the smart grids. The work presented intensively and extensively reviews the recent advances on the energy data management in smart grids, pricing modalities in a modernized power grid, and the predominant components of the smart grid. The paper thoroughly enumerates the recent advances in the area of network reliability. On the other hand, the reliance on smart cities on advanced communication infrastructure promotes more concerns regarding data integrity. Therefore, the paper dedicates a sub-section to highlight the challenges and the state-of-the-art of cybersecurity. Furthermore, highlighting the emerging developments in the pricing mechanisms concludes the review. Full article

(This article belongs to the Special Issue Advanced System Operation and Market Design in Smart Grids)

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