Showing papers by "Pierluigi Mancarella published in 2022"

Microgrids Against Wildfires: Distributed Energy Resources Enhance System Resilience

Abstract: In recent years, countries around the world have been severely affected by catastrophic wildfires with significant environmental, economic, and human losses. Critical infrastructures, including power systems, have been severely damaged, compromising the quality of life and the continuous and reliable provision of essential services, including the electricity supply.

Quantifying the Impacts of Modelling Assumptions on Accuracy and Computational Efficiency for Integrated Water-Energy System Simulations Under Uncertain Climate

Abstract: Jointly managing water and energy systems, rather than treating each system independently, is recognised as an approach that can lead to a more cost-effective and reliable supply, which is particularly critical in water-rich and developing countries. This has motivated the development of various integrated water-energy simulators, each one catering for specific modelling needs through the use of specific sets of modelling assumptions, e.g., representing water and energy with balance equations, or dedicated river flow and power network equations. In this context, it becomes critical to assess the effectiveness of different modelling assumptions to improve the design of water-energy simulators. In particular, it is important to develop a methodology that can identify, based on a systematic assessment process, the portfolios of modelling assumptions that better capture the uncertain future conditions in the water and energy sectors, e.g., climate-driven stresses and shocks such as water scarcity, temperature rise, etc. To address this challenge, this paper proposes a Mixed Integer Linear Programming (MILP) integrated water-energy system simulation methodology designed to adapt and quantify different modelling assumptions under various weather-related conditions (e.g., water scarcity and high temperatures). The models were developed to capture the characteristics of non-pressurised water systems (e.g., channels and rivers) and electricity systems. The methodology is used to investigate typical modelling assumptions (e.g., temporal resolutions and water and power system models) and novel approaches to model the impacts of high temperatures on generation capacity to capture the effects of extreme weather on power generation. The methodology is demonstrated on the Ghanaian integrated water-energy system. The results highlight the benefits in terms of computational costs and modelling accuracy, of the customisable simulation, and provide guidance to select adequate modelling assumptions.

Dynamics of Inverter-Based Resources in Weak Distribution Grids

Abstract: This work presents the modelling fundamentals to study the dynamics of inverter-based resources (IBRs) in weak distribution grids and derive disturbance performance characteristics describing how they should behave under different conditions. More specifically, with respect to small-signal disturbances we study the possible voltage violations following frequency response from IBRs due to low system strength and also propose specific design requirements for IBR d–q current control to guarantee a stable response. In the context of large-signal disturbances, we highlight how active power-voltage control may not be effective due to a delay imposed by the physical features of the distribution network. Further, we mathematically discuss how IBR reactive power control could enhance its phase-locked loop stability. The proposed disturbance performance characteristics are then integrated into the IBR converter control via a novel voltage-priority reference generation strategy. Simulation results on a real Australian network show the efficacy of the proposed operational and control design requirements, and highlight possible unexpected active/reactive power interactions in weak distribution grids.

Market and regulatory frameworks for operational security in decarbonising electricity systems: from physics to economics

Abstract: Grid integration of low-carbon resources comes with new, significant technical challenges for keeping a power system secure. Given a multitude of grid services with varying interactions and risks, the economics of power system security are similarly, if not more, complex. In this paper we discuss the fundamental relationship between the physical and economic aspects of power system security in low-carbon grids. Specifically, we formulate a physics-informed approach for classifying power system security products and services. The approach yields two critical findings. First, we show that these services, rather than being a homogenous set of public goods, are more preferably regarded as a set of products/services (basket of goods) that have both public and private characteristics. Second, the framework reveals that many new system services are consistent with a common pool resource characterisation. This implies an enhanced role for more localised network planning and co-ordination of access and service provision.

Towards Optimal Integrated Planning of Electricity and Hydrogen Infrastructure for Large-Scale Renewable Energy Transport

Abstract: —The imminent advent of large-scale green hydrogen (H 2 ) production raises the central question of which of the two options, transporting “green” molecules, or transporting “green” electrons, is the most cost-effective one. This paper proposes a first-of-its-kind mathematical framework for the optimal integrated planning of electricity and H 2 infrastructure for transporting large-scale variable renewable energy (VRE). In contrast to most existing works, this work incorporates essential nonlinearities such as voltage drops due to losses in high-voltage alternating current (HVAC) and high-voltage direct current (HVDC) transmission lines, losses in HVDC converter stations, reactive power flow, pressure drops in pipelines, and linepack, all of which play an important role in determining the optimal infrastructure investment decision. Capturing these nonlinearities requires casting the problem as a nonconvex mixed-integer nonlinear program (MINLP), whose complexity is further exacerbated by its large size due to the relatively high temporal resolution of RES forecasts. This work then leverages recent advancements in convex relaxations to instead solve a tractable alternative in the form of a mixed-integer quadratically constrained programming (MIQCP) problem. The impact of other fundamental factors such as transmission distance and RES capacity is also thoroughly analysed on a canonical two-node system. The integrated planning model is then demonstrated on a

Markets for Flexibility: It Don’t Mean a Thing If It Ain’t Got That Swing [Book Reviews]

Abstract: This book proposes a new wholesale electricity market design paradigm, with a focus on North America, for centrally managed electricity markets that are based on the novel concept of swing contracts. The author, a professor at Iowa State University, has been working on electricity market design and agent-based computational economics for many years. Her extensive academic, research, and industry experiences, as well as her training in both economics and mathematics, make her highly qualified to provide fresh thinking in this important area. The book proposes the adoption of swing contracts between the system operator and relevant resources to provide flexibility. This flexibility is represented in the form of future availability of dispatchable power paths (“reserve”) with prespecified physical attributes and economic attributes (for pricing purposes). The book contains rigorous mathematical descriptions of the proposed mechanism and implementations.

Tracing, Ranking and Pricing DER Flexibility in Active Distribution Networks

Abstract: —This paper presents a framework for analysing the aggregated flexibility of active distribution networks (ADNs) with distributed energy resources (DER). The analysis takes a different perspective than existing studies, which focus on characterising flexibility as the limits of the flexible power provision, i.e., the set of the network feasible operating points in the P-Q space. Instead, this work aims to estimate the contributions of different flexible units to the aggregated flexibility, which is essential for flexible power ranking and pricing. The proposed framework exploits cost-minimising OPF models complemented with cooperative game formulations that are able to capture the combinatorial nature of activating multiple flexible units. Moreover, in contrast to existing studies that imply perfect coordination of units, the proposed framework specifies the actions needed to reach feasible operating points, reflecting the nonlinearities of the network flexibility model. Extensive simulations are performed for different flexibility metrics to demonstrate the applicability of the framework. Depending on the metric selected (capacity, cost, or economic surplus of flexibility), distribution system operators (DSOs) can identify the most critical flexible units or remunerate units for participating in flexibility services provision.

Daily and seasonal thermal energy storage for enhanced flexible operation of low-temperature heating and cooling network

Abstract: Synergic operation of electricity, heating and cooling networks can bring savings and low carbon footprint through energy efficiency. In such context, the present work proposes a novel Smart Thermal Loop (STL) solution: a fully electrified thermal generation and distribution system where a low-temperature underground loop and reversible heat pumps are used to supply users’ heating and cooling demand. Additionally, STL includes short and long-term thermal energy storage (TES) by means of sensible storage tanks and geothermal boreholes. The proposed solution is described and investigated in the case of the new campus of the University of Melbourne (with aggregated peak load of about 2 and 3 MWth, respectively, for heating and cooling). A numerical model is proposed to simulate the yearly operation of STL with 1-hour resolution. Key features include (i) network model for the underground loop to track temperature evolution over space and time, (ii) variable heat pump performance, which depends on network temperatures, (iii) physical model for the heat transfer between system and soil, in the geothermal storage, (iv) modelling of the interaction between neighbouring boreholes. Results explore the dynamics of the integrated STL system, with a focus on the role that energy storage over different timescales plays in enabling efficient and flexible operation of system components. TES contribution to system operation goes beyond the use of low-price electricity and allows energy savings through efficient scheduling of heat pumps operation and reduction of pumping work. Benefits from the flexible operation of STL are quantified as a 10% reduction in energy expenditure and 28% in system running costs. The presented model can also instruct on the impact of different design choices on STL operation.

Assessing Power System Resilience to Floods: A Geo-Referenced Statistical Model for Substation Inundation Failures

Abstract: Floods can cause widespread and prolonged power outages by inundating substations. However, assessing the inundation failure of substations to improve power system resilience is challenging, as there may not be sufficient historical data to capture the impact of flooding on substations at a given location, due to their evident temporal and spatial variability. To tackle this gap in knowledge, this paper proposes a geo-referenced statistical model that is not constrained by historical flooding data. The geo-referenced model embeds a hydrological model that uses established digital rainfall and topography data to simulate flood depths at the location of selected substations, and calculate associated inundation risks. The stochastic inundation profiles are used within a Monte Carlo simulation to model substation failures and explore options to improve power system resilience (e.g., asset elevation). The proposed model is demonstrated using a case study from Bintulu, Malaysia, where real empirical data was used to identify the breaking points of the power system and estimate probability density functions of energy not supplied caused by inundated substations. The simulation results show that substation failures can abruptly lead to significant energy not being supplied, whereas elevating the substation to withstand an additional 20 cm flood depth will significantly delay flood impacts, and effectively improve system resilience. The proposed methodology and key findings will enable system planners and operators to understand when and where the power system will experience energy losses under unpredictable extreme floods and help them to decide on the most effective resilience enhancement strategies.

Tracing, Ranking and Valuation of Aggregated DER Flexibility in Active Distribution Networks

Abstract: The integration of distributed energy resources (DER) makes active distribution networks (ADNs) natural providers of flexibility services. However, the optimal operation of flexible units in ADNs is highly complex, which poses challenges for distribution system operators (DSOs) in aggregating DER flexibility. For example, to maximise the provision of services, flexible units must be strongly coordinated to manage network constraints, e.g., perform power swaps. Furthermore, due to the nonlinearities of aggregated DER flexibility provision, some units may need to rapidly change their outputs to enable the services. To address these challenges, this paper brings together exact AC optimal power flow (OPF) models and a cooperative game formulation and presents a new framework for tracing, ranking, and valuation of aggregated DER flexibility in ADNs. Extensive tests and simulations performed for the 33-bus radial distribution network demonstrate that the framework enables translating complex DER interactions into useful information for DSOs by ranking the criticality of flexible units and performing flexibility valuation based on its cost or economic surplus. Additionally, the framework proposes no-swap constraints and a nonlinearity metric which can be used by DSOs to identify unreliable operating regions with power swaps or rapid changes in flexible unit dispatch.

Introducing Oxford Open Energy and the energy quest

Abstract: Energy stands in the focal point of reducing the emissions. To reach the Paris Climate Agreement goals requiring carbon neutrality by the middle of this century, the emissions would need to be halved every ten years. The energy transition ahead thus encompasses a huge societal change, urging to view the change in a framework integrating technology, economics, policies and social aspects. Oxford Open Energy emerges from such a multi-dimensional and complex energy quest and from the demand to create a suitable platform to deal with the multi-disciplinary issues in energy, but with an innovative touch.

Assessing Active Distribution Network Flexibility: On the Effects of Nonlinearities and Nonconvexities

Abstract: —A widespread approach to characterise the aggre- gated flexibility of active distribution networks (ADNs) is to estimate the boundary of the feasible network operating areas using convex polygons in the P-Q space. However, such approximations can be inaccurate under realistic conditions where, for example, the nonlinear nature of the network is captured, and the behaviour of flexible units is constrained. This letter demonstrates, using a small ADN example with four flexible units and considering only nonlinearities from the network, that reaching the full P-Q flexibility areas would require perfect coordination of units and high ramping rates. Without these requirements, the P-Q areas become nonconvex. Thus, if the effects of nonlinearities and nonconvexities are ignored, existing approaches in the literature can result in overestimation of ADN flexibility and give rise to impractical solutions, hampering coor- dination between transmission and distribution system operators.