Imperial College London

DrAntoniode Paola

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Visiting Researcher
 
 
 
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Contact

 

antonio.de-paola09 CV

 
 
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Location

 

Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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30 results found

Dong Z, Angeli D, Paola A, Strbac Get al., 2021, An iterative algorithm for regret minimization in flexible demand scheduling problems, Advanced Control for Applications, Vol: 3, ISSN: 2578-0727

Journal article

Ndawula MB, Hernando-Gil I, Li R, Gu C, De Paola Aet al., 2021, Model order reduction for reliability assessment of flexible power networks, INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, Vol: 127, ISSN: 0142-0615

Journal article

Trovato V, De Paola A, Strbac G, 2020, Distributed Control of Clustered Populations of Thermostatic Loads in Multi-Area Systems: A Mean Field Game Approach, ENERGIES, Vol: 13

Journal article

Paola AD, Savelli I, Morstyn T, 2020, A novel ex-ante tariff scheme for cost recovery of transmission investments under elasticity of demand, 2020 17th International Conference on the European Energy Market (EEM), Publisher: IEEE

Conference paper

Savelli I, De Paola A, Li F, 2020, Ex-ante dynamic network tariffs for transmission cost recovery, APPLIED ENERGY, Vol: 258, ISSN: 0306-2619

Journal article

Papadaskalopoulos D, Fan Y, De Paola A, Moreno R, Strbac G, Angeli Det al., 2020, Game-theoretic modeling of merchant transmission investments, Lecture Notes in Energy, Pages: 381-414

Merchant transmission investment planning has recently emerged as a promising alternative or complement to the traditional centralized planning paradigm and it is considered as a further step toward the deregulation and liberalization of the electricity industry. However, its widespread application requires addressing two fundamental research questions: which entities are likely to undertake merchant transmission investments and whether this planning paradigm can maximize social welfare as the traditional centralized paradigm. Unfortunately, previously proposed approaches to quantitatively model this new planning paradigm do not comprehensively capture the strategic behavior and decision-making interactions between multiple merchant investors. This Chapter proposes a novel non-cooperative game-theoretic modeling framework to capture these realistic aspects of merchant transmission investments and provide insightful answers to the above research questions. More specifically, two different models, both based on non-cooperative game theory, have been developed. The first model addresses the first research question by adopting an equilibrium programming approach. The decision-making problem of each merchant investing player is formulated as a bi-level optimization problem, accounting for the impacts of its own actions on locational marginal prices (LMP) as well as the actions of all competing players. This problem is solved after converting it to a mathematical program with equilibrium constraints (MPEC). An iterative diagonalization method is employed to search for the likely outcome of the strategic interactions between multiple players, i.e., Nash equilibria (NE) of the game. Case studies on a simple 2-node system demonstrate that merchant networks investments will be mostly undertaken by generation companies in areas with low LMP and demand companies in areas with high LMP, as apart from collecting congestion revenue they also increase their energy surpluses. These

Book chapter

Gong X, De Paola A, Angeli D, Strbac Get al., 2019, A game-theoretic approach for price-based coordination of flexible devices operating in integrated energy-reserve markets, Energy, Vol: 189, Pages: 1-12, ISSN: 0360-5442

This paper presents a novel distributed control strategy for large scale deployment of demand response. In the considered framework, large populations of storage devices and electric vehicles (EVs) participate to an integrated energy-reserve market. They react to prices and autonomously schedule their operation in order to optimize their own objective functions. The price signals are obtained through the resolution of an optimal power flow problem that explicitly takes into account the impact of demand response on the optimal power dispatch and reserve procurement of committed generation. Differently from previous approaches, the adopted game-theoretic framework provides rigorous theoretical guarantees of convergence and optimality of the proposed control scheme in a multi-price setup that includes ancillary services. The performance of the coordination scheme is also evaluated in simulation on the PJM 5-bus system, demonstrating its capability to flatten demand profiles and reduce the costs of generators and flexible devices.

Journal article

De Paola A, Trovato V, Angeli D, Strbac Get al., 2019, A mean field game approach for distributed control of thermostatic loads acting in simultaneous energy-frequency response markets, IEEE Transactions on Smart Grid, Vol: 10, Pages: 5987-5999, ISSN: 1949-3053

This paper proposes a novel distributed solution for the operation of large populations of thermostatically controlled loads (TCLs) providing frequency support. A game-theory framework is adopted, modeling the TCLs as price-responsive rational agents that schedule their energy consumption and allocate frequency response provision in order to minimize their operational costs. The novelty of this work lies in the use of mean field games to abstract the complex interactions of large numbers of TCLs with the grid and in the introduction of an innovative market structure, envisioning distinct price signals for electricity and response. Differently from previous approaches, such prices are not designed ad hoc but are derived instead from an underlying system scheduling model.

Journal article

Gong X, De Paola A, Angeli D, Strbac Get al., 2019, Distributed coordination of flexible loads using locational marginal prices, IEEE Transactions on Control of Network Systems, Vol: 6, Pages: 1097-1110, ISSN: 2325-5870

This paper presents a novel distributed control strategy for large-scale deployment of flexible demand in power systems. A game theoretical setting is adopted, modeling the loads as rational players that aim to complete an assigned task at minimum cost and compete for power consumption at the cheapest hours of the day. The main novelty is the analysis of power systems with congestion: the proposed modeling framework envisages heterogeneous groups of loads that operate at different buses, connected by transmission lines of limited capacity. The locational marginal prices of electricity, different in general for each bus, are calculated through an optimal power flow problem, accounting for the impact of the flexible devices on power demand and generation. A new iterative scheme for flexible demand coordination is analytically characterized as a multivalued mapping. Its convergence to a stable market configuration (i.e., variational Wardrop equilibrium) and global optimality are analytically demonstrated, for any penetration level of flexible demand and any grid topology. Distributed implementations of the proposed control strategy are discussed, evaluating their performance with simulations on the IEEE 24-bus system.

Journal article

De Paola A, Fele F, Angeli D, Strbac Get al., 2019, Distributed coordination of price-responsive electric loads: a receding horizon approach, 57th IEEE Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 6033-6040, ISSN: 0743-1546

This paper presents a novel receding horizon framework for the power scheduling of flexible electric loads performing heterogeneous periodic tasks. The loads are characterized as price-responsive agents and their interactions are modelled through an infinite-time horizon aggregative game. A distributed control strategy based on iterative better-response updates is proposed to coordinate the loads, proving its convergence and global optimality with Lyapunov stability tools. Robustness with respect to variations in the number and tasks of players is also ensured. Finally, the performance of the control scheme is evaluated in simulation, coordinating the daily battery charging of a large fleet of electric vehicles.

Conference paper

Ndawula MB, De Paola A, Hernando-Gil I, 2019, Disaggregation of Reported Reliability Performance Metrics in Power Distribution Networks, 2nd International Conference on Smart Energy Systems and Technologies (SEST), Publisher: IEEE

Conference paper

De Paola A, Trovato V, Angeli D, Strbac Get al., 2019, Value of Thermostatic Loads in Energy/Frequency Response Markets: a Mean Field Game Approach, IEEE Milan PowerTech Conference, Publisher: IEEE

Conference paper

Ndawula MB, De Paola A, Hernando-Gil I, 2019, Evaluation of Customer-oriented Power Supply Risk with Distributed PV-Storage Energy Systems, IEEE Milan PowerTech Conference, Publisher: IEEE

Conference paper

Gong X, De Paola A, Angeli D, Strbac Get al., 2018, A distributed price-based strategy for flexible demand coordination in multi-area, IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Publisher: IEEE, ISSN: 2165-4816

This paper presents a novel distributed control strategy for large-scale deployment of price-responsive flexible demand. Differently from previous theoretical studies on the subject, the proposed analysis explicitly models multi-area systems, accounting for transmission lines of limited capacity and different locational marginal prices (LMP) throughout the network. A game-theoretic framework is adopted, designing a demand coordination scheme that converges to a stable market configuration (characterized as an aggregative equilibrium) through iterative price broadcasts. The performance of the proposed control strategy, that also ensures flattened generation profiles and reduced generation costs, is evaluated in simulation on a five-bus power system.

Conference paper

de Paola A, Angeli D, Strbac G, 2018, On distributed scheduling of flexible demand and Nash equilibria in the electricity market, Dynamic Games and Applications, Vol: 8, Pages: 761-798, ISSN: 2153-0785

This paper presents a novel game theory approach for large-scale deployment of price-responsive electrical appliances. In the proposed distributed control scheme, each appliance independently schedules its power consumption on the basis of a broadcast demand/price signal, aiming to complete its task at minimum cost. The conflicting interactions of the appliances, competing for power consumption at the cheapest hours of the day, are modelled through a differential game with a continuum of players, and efficient deployment of flexible demand is characterized as a Nash equilibrium. A novel approach is adopted to derive necessary and sufficient equilibrium conditions: intrinsic properties of the problem (price monotonicity, unidirectionality of power transfers) are exploited to perform an equilibrium study based on sublevel sets of the considered demand profiles. As a result, it is possible to determine for which penetration levels of flexible demand, types of appliances and inflexible demand profiles it is possible to achieve an equilibrium. Such stable configuration is achieved through the broadcast of a single demand/price signal and does not require iterated exchange of information between devices and coordinator. In addition, the global optimality of the equilibrium is proved, necessary conditions for Pareto optimality are derived, and a preliminary analysis of devices with partial time availability is carried out. The performance of the proposed control strategy is evaluated in simulation, considering realistic future scenarios of the UK power system with large penetration of flexible demand.

Journal article

De Paola A, Gong X, Angeli D, Strbac Get al., 2018, Coordination of micro-storage devices in power grids: a multi-agent system approach for energy arbitrage, IEEE Conference on Control Technology and Applications (CCTA), Publisher: IEEE, Pages: 871-878

Conference paper

De Paola A, Papadaskalopoulos D, Angeli D, Strbac Get al., 2018, Investigating the social efficiency of merchant transmission planning through a non-cooperative game-theoretic framework, IEEE Transactions on Power Systems, Vol: 33, Pages: 4831-4841, ISSN: 0885-8950

Merchant transmission planning is considered as a further step towards the full liberalization of the electricity industry. However, previous modeling approaches do not comprehensively explore its social efficiency as they cannot effectively deal with a large number of merchant companies. This paper addresses this fundamental challenge by adopting a novel non-cooperative game-theoretic approach. Specifically, the number of merchant companies is assumed sufficiently large to be approximated as a continuum. This allows the derivation of mathematical conditions for the existence of a Nash Equilibrium solution of the merchant planning game. By analytically and numerically comparing this solution against the one obtained through the traditional centralized planning approach, the paper demonstrates that merchant planning can maximize social welfare only when the following conditions are satisfied: a) fixed investment costs are neglected and b) the network is radial and does not include any loops. Given that these conditions do not generally hold in reality, these findings suggest that even a fully competitive merchant transmission planning framework, involving the participation of a very large number of competing merchant companies, is not generally capable of maximizing social welfare.

Journal article

Fele F, De Paola A, Angeli D, Strbac Get al., 2018, A framework for receding-horizon control in infinite-horizon aggregative games, Annual Reviews in Control, Vol: 45, Pages: 191-204, ISSN: 1367-5788

A novel modelling framework is proposed for the analysis of aggregative games on an infinite-time horizon, assuming that players are subject to heterogeneous periodic constraints. A new aggregative equilibrium notion is presented and the strategic behaviour of the agents is analysed under a receding horizon paradigm. The evolution of the strategies predicted and implemented by the players over time is modelled through a discrete-time multi-valued dynamical system. By considering Lyapunov stability notions and applying limit and invariance results for set-valued correspondences, necessary conditions are derived for convergence of a receding horizon map to a periodic equilibrium of the aggregative game. This result is achieved for any (feasible) initial condition, thus ensuring implicit adaptivity of the proposed control framework to real-time variations in the number and parameters of players. Design and implementation of the proposed control strategy are discussed and an example of distributed control for data routing is presented, evaluating its performance in simulation.

Journal article

De Paola A, Angeli D, Strbac G, 2018, Distributed schemes for efficient deployment of price-responsive demand with partial flexibility, Journal of Control and Decision, Vol: 5, Pages: 164-194, ISSN: 2330-7706

This paper presents novel methodologies for efficient deployment of flexible demand. Large populations of price-responsive loads are coordinated through a price signal and a power constraint broadcast by a central entity. Such quantities are designed in order to minimise a global objective function (e.g. total generation costs) and ensure a one-step convergence to a stable solution, characterised as a Nash equilibrium. Conditions for the sought equilibrium are preliminarily expressed as monotonicity of demand profiles under reordered coordinates and then they are imposed as constraints of a global optimisation, whose solution is calculated numerically. To reduce the computational complexity of the problem in scenarios with high penetration of flexible demand, clustering of the appliances is introduced. The global properties of the final stable solution and its optimality with respect to the task times of the appliances are analysed both theoretically and through simulation results.

Journal article

De Paola A, Angeli D, Strbac G, 2018, Integration of price-responsive appliances in the energy market through flexible demand saturation, IEEE Transactions on Control of Network Systems, Vol: 5, Pages: 154-166, ISSN: 2325-5870

This paper proposes a novel decentralized technique for efficient integration of flexible demand in the electricity market. The analysis focuses on price-responsive appliances that schedule their power consumption on the basis of a demand/price signal received by a central entity. Previous work has shown that, when the devices population is sufficiently large to be described as a continuum, it is possible to provide necessary and sufficient conditions for the existence of a Nash equilibrium (no device has unilateral interest in changing its scheduling when considering the resulting profile of aggregate demand). These results are now extended in order to achieve an equilibrium also when the mentioned conditions are violated. To this purpose, a time-varying proportional constraint (equal for all devices) is introduced on the power rate of the price-responsive appliances so as to limit the variation of flexible demand that they can introduce at critical time instants. The proposed design technique not only guarantees existence of a Nash equilibrium but it also minimizes the global operation time of the appliances population. Simulation results are provided and it is shown that, under the considered assumptions, each individual appliance completes its task in minimum time.

Journal article

de Paola A, Angeli D, Strbac G, 2018, Convergence and optimality of a new iterative price-based scheme for distributed coordination of flexible loads in the electricity market, 2017 IEEE 56th Annual Conference on Decision and Control (CDC), Publisher: IEEE

This paper proposes a novel distributed control strategy for large-scale deployment of flexible demand. The devices are modelled as competing players that respond to iterative broadcasts of price signals, scheduling their power consumption to operate at minimum cost. By describing their power update at each price broadcast through a multi-valued discrete-time dynamical system and by applying Lyapunov techniques, it is shown that the proposed control strategy always converges to a stable final configuration, characterized as a Wardrop (or aggregative) equilibrium. It is also proved that such equilibrium is socially efficient and optimizes some global performance index of the system (e.g. minimizes total generation costs). These results are achieved under very general assumptions on the electricity price and for any penetration level of flexible demand. Practical implementation of the proposed scheme is discussed and tested in simulation on a future scenario of the UK-grid with large numbers of flexible loads.

Conference paper

De Paola A, Papadaskalopoulos D, Angeli D, Strbac Get al., 2018, A Game-Theoretic Modeling Approach for Merchant Transmission Planning, 15th International Conference on the European Energy Market (EEM), Publisher: IEEE, ISSN: 2165-4077

Conference paper

De Paola A, Angeli D, Strbac G, 2017, Price-Based Schemes for Distributed Coordination of Flexible Demand in the Electricity Market, IEEE TRANSACTIONS ON SMART GRID, Vol: 8, Pages: 3104-3116, ISSN: 1949-3053

Journal article

De Paola A, Angeli D, Strbac G, 2017, A semi-decentralized scheme for integration of price-responsive appliances in the electricity market, 20th IFAC World Congress, Publisher: Elsevier, Pages: 6729-6736, ISSN: 1474-6670

A novel semi-decentralized control strategy is proposed for the integration in the power system of large populations of flexible loads, such as electric vehicles and “smart” appliances. To characterize the interactions between the single agents and their effects on the grid, a game theory framework is adopted. The price responsive appliances are modelled as competing players, characterizing a stable and efficient solution as a Nash equilibrium (no device has unilateral interest in changing its scheduled power consumption when the final electricity price is considered). We extend previous results on distributed control of flexible demand, proposing a partial centralization of the power scheduling at critical time instants. In this way, it is possible to ensure convergence to a Nash equilibrium for a wider range of scenarios, considering higher penetration levels of flexible demand and a wider range of parameters for the devices. The effectiveness of the proposed scheme is theoretically proved and its performance is evaluated in simulations, considering a future UK grid with high penetration of flexible demand.

Conference paper

De Paola A, Angeli D, Strbac G, 2016, Decentralized coordination of large populations of flexible electrical appliances through demand saturation, 2016 IEEE 55th Conference on Decision and Control, CDC 2016, Publisher: Institute of Electrical and Electronics Engineers (IEEE), Pages: 4937-4943

This paper presents a novel decentralized control strategy for integration of price-responsive loads in the electricity market. Previous work has shown that, by approximating the devices population as a continuum, it is possible to provide necessary and sufficient conditions for the existence of a Nash equilibrium (no device has unilateral interest in changing its scheduling when considering the resulting profile of aggregate demand). These results are now extended by introducing a time varying proportional constraint on the maximum power consumption of the appliances. This allows to saturate the flexible demand and obtain a Nash equilibrium for a much wider range of scenarios. The performance of the proposed control technique, which also minimizes the task time of all appliances, is tested in simulation.

Conference paper

De Paola A, Angeli D, Strbac G, 2016, Frequency support by scheduling of variable-speed wind turbines, 19th IFAC World Congress, Publisher: Elsevier, Pages: 7904-7910, ISSN: 1474-6670

This paper characterizes optimal control policies for wind farms operated as frequency response services in case of a fault of conventional generators. The frequency support is provided through temporary over-production: when frequency drops, the turbines move from the steady-state operating point and extra power is produced by slowing down the turbines and releasing part of their kinetic energy. The control task is formulated and solved as an optimal containment problem: the time during which an extra quantity of power can be produced, within the set speed constraints for each turbine, is maximized. The solutions are calculated and compared for different assumptions on the electric torque of the turbines.

Conference paper

De Paola A, Angeli D, Strbac G, 2016, Analysis of Nash equilibria in energy markets with large populations of price-responsive flexible appliances, 2015 54th IEEE Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 5587-5592, ISSN: 0743-1546

This paper deals with flexible electrical devices that, on the basis of a broadcast price signal, schedule their individual power consumption in order to minimize their energy cost. If the devices population is sufficiently large to be described as a continuum, it is possible to provide necessary and sufficient conditions for the existence of a Nash equilibrium in the energy market. This is done by comparing two functions which characterize, respectively, the valley capacity of the inflexible demand and the global properties of the appliances population. The equilibrium conditions, which do not require any iterative procedure to be applied, are finally tested in simulations.

Conference paper

De Paola A, Angeli D, Strbac G, 2016, Scheduling of Wind Farms for Optimal Frequency Response and Energy Recovery, IEEE Transactions on Control Systems Technology, Vol: 24, Pages: 1764-1778, ISSN: 1063-6536

This paper deals with control of variable speed wind turbines, which provide frequency support through temporary overproduction. In particular, it determines the optimal profile of power extraction among multiple generators in order to minimize the total loss of efficiency, while allowing for a prescribed increase in generation. Starting with the simplifying assumption of unconstrained generated/supplied power for the single turbine, the scheduling is characterized as the solution of an optimal control problem. On the basis of this result, a heuristic control strategy is proposed for the case of turbines with limited power output, investigating under which conditions this choice achieves optimality. Using a similar approach, the problem of energy recovery is also considered, calculating the optimal power profiles that bring back the turbines to their working point of maximum efficiency after having provided frequency response.

Journal article

De Paola A, Angeli D, Strbac G, 2015, Distributed Control of Micro-Storage Devices With Mean Field Games, IEEE Transactions on Smart Grid, Vol: 7, Pages: 1119-1127, ISSN: 1949-3061

This paper proposes a fully distributed control strategyfor the management of micro-storage devices that performenergy arbitrage. For large storage populations the problem canbe approximated as a differential game with infinite players(Mean Field Game). Through the resolution of coupled partialdifferential equations (PDEs), it is possible to determine, as afixed point, the optimal feedback strategy for each player andthe resulting price of energy if that strategy is applied. Oncethis price is calculated, it can be communicated to the deviceswhich are able to independently determine their optimal chargeprofile. Simulation results are provided, calculating the fixedpoint through numerical integration of the PDEs. The originalmodel is then extended in order to consider additional elementssuch as multiple population of devices and demand uncertainty.

Journal article

Angeli D, de Paola A, Strbac G, 2012, Distributed frequency control by means of responsive wind generation, 51st IEEE Annual Conference on Decision and Control (CDC), Publisher: IEEE, Pages: 5834-5839, ISSN: 0743-1546

Conference paper

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