• Energy Research

Abstract The impact of the spatial variation of inertial response and fast frequency services has not been fully investigated in power system scheduling models incorporating constraints on network security. This paper demonstrates the importance of acknowledging the variety of local frequency dynamics in the aftermath of a generation loss. It proposes a novel scheduling methodology that enables the system security in all areas of the system thus preventing potential tripping of distributed generation triggered by locally-measured high rates of change of frequency. The proposed methodology highlights the positive contribution to local frequency dynamics from an HVDC link, whose capacity is optimally dispatched to allocate power flow and fast-frequency services. The novel power system scheduling model is applied to analyze a typical 2030 GB low-carbon scenario. Results show that there are changes in the commitment decisions compared to the solution obtained with a one-area formulation when local security is taken into account. These changes translate into additional operational cost.

Future changes in the generation mix may reduce the overall amount of system inertia. It becomes crucial to provide response services more quickly to secure postfault transient frequency dynamics. This paper proposes a novel mixed integer linear programming unit commitment formulation that simultaneously optimizes energy production and the allocation of inertial response (IR), enhanced frequency response (EFR), and primary response (PR) against largest plant outage. A set of linearized inertia-dependent and multispeed constraints on frequency evolution explicitly recognizes the quicker provision of EFR compared to PR and their mutual interplay with IR. The proposed model is applied to analyze a typical 2030 GB low-carbon scenario. Results demonstrate the value, as reduction of system operational cost, when battery storage provides EFR, facilitating a cost-efficient transition toward the low-carbon electricity sector.

Under future low-carbon scenarios, it will be crucial to boost the rapidity in the delivery of frequency response services, especially those provided by conventional generators. This paper proposes a novel framework for the scheduling of frequency response services that incentivizes a rapid response from different system assets, including conventional generators. Differently from other approaches which envisage a fixed delivery time for frequency response services, the proposed methodology implements time-varying delivery intervals, which coincide with the time of frequency nadir occurrence. A relevant set of linearized constraints is embedded in a typical power system scheduling model. Results indicate that the proposed methodology reduces the unnecessary overscheduling associated with traditional methodologies, leading to significant operational cost savings.

Power systems are facing complex challenges in order to achieve environmental targets, such as a strong abatement of CO2 emissions. Hence, an increasing share of renewable energy sources (RES) will change the generation portfolio. This is likely to push network operation into a risky territory, due to a lack of system inertia. This paper quantifies the impact of providing `effective inertia' by controlling domestic thermostatic loads. This inertial support mechanism would permit full absorption of available wind power even for those scenarios characterized by low demand and high wind penetration.

This paper investigates the potential contribution that interconnectors can provide to efficiently support the security of interconnected power systems. The proposed modelling setup introduces a radical paradigm shift in the operation of the interconnectors and in their interactions with multiple markets. To the best of our knowledge, this is the first paper that models a simultaneous allocation of the interconnector capacity for the exchange of energy and of inertia-dependent primary frequency response. The benefits and impact of this new methodology are evaluated with typical market indicators (e.g. social welfare and interconnector revenues) under two different paradigms: a centralized approach where the interconnectors are operated to minimize the system operational cost and a market-based framework where the interconnectors are privately-owned assets with self-interested objectives. By modelling the interconnectors as price-maker, the proposed work quantifies the potential inefficiencies of market solutions while considering key elements such as capacity withdrawing. A case study of the GB-France systems assesses the value of interconnectors on system efficiency and security under the considered paradigms.

Thermostatically controlled loads (TCLs) can effectively support network operation through their intrinsic flexibility and play a pivotal role in delivering cost effective decarbonization. This paper proposes a scalable distributed solution for the operation of large populations of TCLs providing frequency response and performing energy arbitrage. Each TCL is described as a price-responsive rational agent that participates in an integrated energy/frequency response market and schedules its operation in order to minimize its energy costs and maximize the revenues from frequency response provision. A mean field game formulation is used to implement a compact description of the interactions between typical power system characteristics and TCLs flexibility properties. In order to accommodate the heterogeneity of the thermostatic loads into the mean field equations, the whole population of TCLs is clustered into smaller subsets of devices with similar properties, using k-means clustering techniques. This framework is applied to a multi-area power system to study the impact of network congestions and of spatial variation of flexible resources in grids with large penetration of renewable generation sources. Numerical simulations on relevant case studies allow to explicitly quantify the effect of these factors on the value of TCLs flexibility and on the overall efficiency of the power system.

Renewable energy communities foster the users’ engagement in the energy transition, paving the way to the integration of distributed renewable energy sources. So far, the scientific literature has focused on residential users in energy communities, thus overlooking the opportunities for industrial and commercial members. This paper seeks to bridge this gap by extending the analysis to the role of non-residential users. The proposed methodology develops an effective clustering approach targeted to actual non-residential consumption profiles. It is based on the k-means algorithm and statistical characterization based on relevant probability density function curves. The employed clusterization procedure allows for effectively reducing a sample of 49 real industrial load profiles up to 11 typical consumption curves, whilst capturing all the relevant characteristics of the initial population. Furthermore, a peer-to-peer sharing strategy is developed accounting for distributed and shared storage. Three scenarios are considered to validate the model with different shares of non-residential users, and the results are then evaluated by means of shared energy, self-consumption, and self-sufficiency indices. Moreover, the results show that the integration of a large non-residential prosumer in a REC may increase the self-sufficiency of residential members by 8.2%, self-consumption by 4.4%, and the overall shared energy by 37.3%. Therefore, the residential community consistently benefits from the presence of non-residential users, with larger users inducing more pronounced effects.

This paper analyses the potential benefits for flexible operation of interconnectors in cross-border power systems. The underlying modelling approach enables the simultaneous cross-border exchange of power and inertiadependent frequency response services through the interconnector. Two main operational paradigms are adopted. The first considers the interconnectors as centrally-operated assets; the latter envisages them as profit-seeking private entities. Furthermore, the proposed work adopts a samplingbased method to assess the impact of wind and demand variability on the short-term operation of the interconnectors, evaluating the sensitivities of relevant operational and economical metrics with respect to wind availability and demand levels. A comprehensive set of case studies is developed considering the Great Britain (GB)-France interconnected systems. The studies show significant value for interconnectors under a wide range of system conditions.

The paper proposes a novel generalized formulation of the energy-power dynamics of aggregate thermostatic loads to include power profiles that linearly increase/decrease with time within scheduling intervals. It extends previous models admitting only constant profiles. A MILP optimization problem is built to optimize the dispatch of the devices’ energy/power and the simultaneous allocation of multiple frequency services. Case studies, tailored on the Great Britain electricity context, validate the proposed formulation.