Mitigation of frequency stability issues in low inertia power systems using synchronous compensators and battery energy storage systems

Mosca, Carmelo; Arrigo, F; Mazza, Andrea; Bompard, Ettore; Carpaneto, Enrico; Chicco, Gianfranco; Cuccia, Paolo

doi:10.1049/iet-gtd.2018.7008

Cited by 36 publications

(28 citation statements)

References 24 publications

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“…The hourly market results are used to feed the aggregated dynamic model described in [30] to evaluate the frequency performance indicators. Dynamic simulations are performed for each hour of the year, selecting the worst-case underfrequency contingency as reference incident (it can be either the largest thermal power plant or the HVDC connection, depending on the operating conditions).…”

Section: A Technical-economic Results and Mcdamentioning

confidence: 99%

“…The aggregate model is formed by: System inertia; Equivalent traditional power plant transfer function with a pole and a zero; Primary frequency control model; and Frequency-dependent loads. More details on the developed aggregate model can be found in [30].…”

Section: Methodology For the Technical-economic Compromise Selecmentioning

confidence: 99%

“…However, frequency stability is determined by the overall response as evidenced by its mean frequency [29]. This mean frequency conducts to the concept of an aggregated dynamic model, which can estimate the essential characteristics of a synchronously isolated system's frequency response [11], [30]. Considering the inertia constant of the generation units, the aggregated inertia of the system is:…”

Section: B Inertia Constraintsmentioning

confidence: 99%

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Technical and Economic Impact of the Inertia Constraints on Power Plant Unit Commitment

Mosca

Bompard

Chicco

et al. 2020

IEEE Open J. Power Energy

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The whole interconnected European network is involved in the energy transition towards power systems based on renewable power electronics interfaced generation. In this context, the major concerns for both network planning and operation are the inertia reduction and the frequency control due to the progressive decommissioning of thermal power plants with synchronous generators. This paper investigates the impact of different frequency control constraints on the unit commitment of power plants resulting from market simulations. The market outputs are compared in terms of system costs, and of frequency stability performance evaluated on the basis of the rate of change of frequency and the maximum frequency excursion. The best compromise solution is found using a multiple-criteria decision analysis method, depending on the choice of the decision maker's weighting factors. The proposed approach is tested on a real case taken from one of the most relevant future scenarios of the Italian transmission system operator. The results show how the best compromise solution that can be found depends on the decision maker preference towards cost-based or frequency stability-based criteria. Index Terms-frequency stability, inertia constraints, multiple-criteria decision analysis, power system inertia, rate of change of frequency, unit commitment.

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Section: A Technical-economic Results and Mcdamentioning

confidence: 99%

Section: Methodology For the Technical-economic Compromise Selecmentioning

confidence: 99%

Section: B Inertia Constraintsmentioning

confidence: 99%

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Technical and Economic Impact of the Inertia Constraints on Power Plant Unit Commitment

Mosca

Bompard

Chicco

et al. 2020

IEEE Open J. Power Energy

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“…A well-designed Inertia Emulation (IE) controller empowers the wind generator, or storage element, to release the stored energy for arresting the frequency drop within 10.0 seconds [15]- [18]. Fast frequency controllers can be classified in three main families, namely, droop-based controllers (or proportional controllers) [19]- [21], derivative-based controllers [22]- [24], and other approaches which are usually based on the swing equation of conventional SG, thus attempting to represent a Virtual Synchronous Machine (VSM) for IE [25]- [26].…”

Section: Introductionmentioning

confidence: 99%

FAPI Controller for Frequency Support in Low-Inertia Power Systems

Rakhshani

Perilla

Rueda

et al. 2020

IEEE Open J. Power Energy

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This paper presents different forms of Fast Active Power Injection (FAPI) control schemes for the analysis and development of different mitigation measures to address the frequency stability problem due to the growth of the penetration level of the Power Electronic Interfaced Generation (PEIG) in sustainable interconnected energy systems. Among the studied FAPI control schemes, two different approaches in the form of a derivative-based control and a virtual synchronous power (VSP) based control for wind turbine applications are also proposed. All schemes are attached to the PEIG represented by a generic model of wind turbines type 4. The derivative-based FAPI control is applied as an extension of the droop based control scheme, which is dependent on the measurement of the network frequency. By contrast, the proposed VSP-based FAPI is fed by the measurement of the active power deviation. Additionally, unlike existing approaches for virtual synchronous machines, which are characterized by high-order transfer functions, the proposed VSP-based FAPI is defined by a second-order transfer function, which can contribute to fast mitigation of the system primary frequency deviations during containment period. The Great Britain (GB) test system, for the Gone-Green planning scenario for the year 2030 (GG2030), is used to evaluate the effects of the proposed FAPI controllers on the dynamics of the system frequency within the frequency containment period. Thanks to proposed FAPI controllers, it is possible to reach up to 70% for the share of wind power generation without violating the threshold limits for frequency stability. For verification purposes, a full-scale wind turbine facilitated with each FAPI controller is tested in EMT real-time simulation environment.

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“…In the transmission system, the positive impacts of BESSs for providing a fast response to frequency deviations [3], mitigating under-frequency transients [4], and being exploited for energy arbitrage [5] have been observed. The integration of BESSs with appropriate control strategies has been shown to be able to improve the frequency stability [6]. At the distribution system level, a BESS is mainly used for enhancing the grid integration of RES by mitigating the effects of the uncertainty on load and distributed generation [7,8], improving the distribution system reliability by avoiding operations close to the line thermal limits and thus more exposed to the risk of protection trips [9], enhancing the quality of the supply with relatively high-power and low-energy solutions [10], reducing the need for grid expansion, shaving the power demand peaks through load shifting or load leveling [9], optimizing the energy transaction costs [11], and integrating BESSs with the demand response in microgrid applications [12].…”

Section: Introductionmentioning

confidence: 99%

Location and Sizing of Battery Energy Storage Units in Low Voltage Distribution Networks

et al. 2019

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Proper planning of the installation of Battery Energy Storage Systems (BESSs) in distribution networks is needed to maximize the overall technical and economic benefits. The limited lifetime and relatively high cost of BESSs require appropriate decisions on their installation and deployment, in order to make the best investment. This paper proposes a comprehensive method to fully support the BESS location and sizing in a low-voltage (LV) network, taking into account the characteristics of the local generation and demand connected at the network nodes, and the time-variable generation and demand patterns. The proposed procedure aims to improve the overall network conditions, by considering both technical and economic aspects. An original approach is presented to consider both the planning and scheduling of BESSs in an LV system. This approach combines the properties of metaheuristics for BESS sizing and placement with a greedy algorithm to find viable BESS scheduling in a relatively short time considering a specified time horizon, and the application of decision theory concepts to obtain the final solution. The decision theory considers various scenarios with variable energy prices, the diffusion of local renewable generation, evolution of the local demand with the integration of electric vehicles, and a number of planning alternatives selected as the solutions with top-ranked objective functions of the operational schedules in the given scenarios. The proposed approach can be applied to energy communities where the local system operator only manages the portion of the electrical grid of the community and is responsible for providing secure and affordable electricity to its consumers. 417Regarding the calculation of the load profiles, it takes into account the real contractual delivery 418 powers to each load. Two nodes are considered as commercial consumers, while the other ones 419 refer to residential customers. For the profiles, due to lack of complete information from the actual 420 profiles, relevant (residential and commercial) profiles have been taken from an open-source 421 dataset (OpenEI) [36], normalized and multiplied by the nominal powers.422 3.2.2 PV generation 423 The considered PV production, in the simulation, is calculated based on yearly solar irradiance 424 and the nominal installed power [37]. Yearly solar irradiance data is obtained through collected 425 data from third party weather service provider [38] for specific location of study case with the 426 coordination of 46.4746° N, 11.2479° E.427 3.2.3 EVs relevant information 428 EVs are considered in some scenarios, through the load profile caused by their charging. 429Within this analysis, the number of EVs that determines the EV charging profile, is set to 10 in the 430 beginning of the scenarios with EV and that number increments gradually by rate of one EV per 431year. The nominal power of the EV chargers are considered to be 3.6 kW, i.e., a standard power 432 level of charging stations, and charging events occur mainly during the night...

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Mitigation of frequency stability issues in low inertia power systems using synchronous compensators and battery energy storage systems

Cited by 36 publications

References 24 publications

Technical and Economic Impact of the Inertia Constraints on Power Plant Unit Commitment

Technical and Economic Impact of the Inertia Constraints on Power Plant Unit Commitment

FAPI Controller for Frequency Support in Low-Inertia Power Systems

Location and Sizing of Battery Energy Storage Units in Low Voltage Distribution Networks

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