Publications
541 results found
Falugi P, Konstantelos I, Strbac G, 2018, Planning with multiple transmission and storage investment options under uncertainty: a nested decomposition approach, IEEE Transactions on Power Systems, Vol: 33, Pages: 3559-3572, ISSN: 0885-8950
Achieving the ambitious climate change mitigation objectives set by governments worldwide is bound to lead to unprecedented amounts of network investment to accommodate low-carbon sources of energy. Beyond investing in conventional transmission lines, new technologies such as energy storage can improve operational flexibility and assist with the cost-effective integration of renewables. Given the long lifetime of these network assets and their substantial capital cost, it is imperative to decide on their deployment on a long-term cost-benefit basis. However, such an analysis can result in large-scale Mixed Integer Linear Programming (MILP) problems which contain many thousands of continuous and binary variables. Complexity is severely exacerbated by the need to accommodate multiple candidate assets and consider a wide range of exogenous system development scenarios that may occur. In this manuscript we propose a novel, efficient and highly-generalizable framework for solving large-scale planning problems under uncertainty by using a temporal decomposition scheme based on the principles of Nested Benders. The challenges that arise due to the presence of non-sequential investment state equations and sub-problem non-convexity are highlighted and tackled. The substantial computational gains of the proposed method are demonstrated via a case study on the IEEE 118 bus test system that involve planning of multiple transmission and storage assets under long-term uncertainty.
Ye Y, Papadaskalopoulos D, Strbac G, 2018, Investigating the ability of demand shifting to mitigate electricity producers’ market power, IEEE Transactions on Power Systems, Vol: 33, Pages: 3800-3811, ISSN: 0885-8950
Previous work on the role of the demand side in imperfect electricity markets has demonstrated that its self-price elasticity reduces electricity producers' ability to exercise market power. However, the concept of self-price elasticity cannot accurately capture consumers' flexibility, as the latter mainly involves shifting of loads' operation in time. This paper provides for the first time theoretical and quantitative analysis of the beneficial impact of demand shifting (DS) in mitigating market power by the generation side. Quantitative analysis is supported by a multiperiod equilibrium programming model of the imperfect electricity market, accounting for the time-coupling operational constraints of DS as well as network constraints. The decision making process of each strategic producer is modeled through a bi-level optimization problem, which is solved after converting it to a Mathematical Program with Equilibrium Constraints (MPEC) and linearizing the latter through suitable techniques. The oligopolistic market equilibria resulting from the interaction of multiple independent producers are determined by employing an iterative diagonalization method. Case studies on a test market reflecting the general generation and demand characteristics of the GB system quantitatively demonstrate the benefits of DS in mitigating producers' market power, by employing relevant indexes from the literature.
Moreira A, Fanzeres B, Strbac G, 2018, Energy and reserve scheduling under ambiguity on renewable probability distribution, ELECTRIC POWER SYSTEMS RESEARCH, Vol: 160, Pages: 205-218, ISSN: 0378-7796
Giannelos S, Konstantelos I, Strbac G, 2018, Endogenously Stochastic Demand Side Response Participation on Transmission System Level, IEEE International Energy Conference (ENERGYCON), Publisher: IEEE, ISSN: 2164-4322
Giannelos S, Konstantelos I, Strbac G, 2018, Option Value of Dynamic Line Rating and Storage, IEEE International Energy Conference (ENERGYCON), Publisher: IEEE, ISSN: 2164-4322
Fele F, De Paola A, Angeli D, et 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.
Teng F, Dupin R, Kariniotakis G, et al., 2018, Understanding the benefits of dynamic line rating under multiple sources of uncertainty, IEEE Transactions on Power Systems, Vol: 33, Pages: 3306-3314, ISSN: 0885-8950
This paper analyses the benefits of dynamic line rating (DLR) in the system with high penetration of wind generation. A probabilistic forecasting model for the line ratings is incorporated into a two-stage stochastic optimization model. The scheduling model, for the first time, considers the uncertainty associated with wind generation, line ratings and line outages to co-optimize the energy production and reserve holding levels in the scheduling stage as well as the re-dispatch actions in the real-time operation stage. Therefore, the benefits of higher utilization of line capacity can be explicitly balanced against the costs of increased holding and utilization of reserve services due to the forecasting error. The computational burden driven by the modelling of multiple sources of uncertainty is tackled by applying an efficient filtering approach. The case studies demonstrate the benefits of DLR in supporting costeffective integration of high penetration of wind generation into the existing network. We also highlight the importance of simultaneously considering the multiple sources of uncertainty in understanding the benefits of DLR. Furthermore, this paper analyses the impact of different operational strategies, the coordination among multiple flexible technologies and installed capacity of wind generation on the benefits of DLR.
Gong X, de Paola A, Angeli D, et al., 2018, Coordination of micro-storage devices in power grids: a multi-agent system approach for energy arbitrage, 2018 IEEE Conference on Control Technology and Applications (CCTA)
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.
Qiu D, Papadaskalopoulos D, Ye Y, et al., 2018, Investigating the impact of demand flexibility on electricity retailers, PSCC 2018, 20th Power Systems Computation Conference
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.
Sun M, Teng F, Konstantelos I, et al., 2018, An objective-based scenario selection method for transmission network expansion planning with multivariate stochasticity in load and renewable energy sources, Energy, Vol: 145, Pages: 871-885, ISSN: 0360-5442
Transmission Network Expansion Planning (TNEP) in modern electricity systems is carried out on a cost-benefit analysis basis; the planner identifies investments that maximize the social welfare. As the integration of Renewable Energy Sources (RES) increases, there is a real challenge to accurately capture the vast variability that characterizes system operation within a planning problem. Conventional approaches that rely on a large number of scenarios for representing the variability of operating points can quickly lead to computational issues. An alternative approach that is becoming increasingly necessary is to select representative scenarios from the original population via clustering techniques. However, direct clustering of operating points in the input domain may not capture characteristics which are important for investment decision-making. This paper presents a novel objective-based scenario selection framework for TNEP to obtain optimal investment decisions with a significantly reduced number of operating states. Different clustering frameworks, clustering variable s and clustering techniques are compared to determine the most appropriate approach. The superior performance of the proposed framework is demonstrated through a case study on a modified IEEE 118-bus system.
Rodrigues T, Ramirez PJ, Strbac G, 2018, Risk-averse bidding of energy and spinning reserve by wind farms with on-site energy storage, IET RENEWABLE POWER GENERATION, Vol: 12, Pages: 165-173, ISSN: 1752-1416
Rodrigues T, Moreira R, Strbac G, 2018, Coordinated operation of distributed energy storage in low carbon networks, 2017 IEEE PES General Meeting, Publisher: IEEE, ISSN: 1944-9925
Recent developments on climate change regulations are leading to significant changes in the electricity industry with volatility levels and uncertainty increasing significantly. As aresult, systemoperators are extending the procurement of flexibility to end-users and encourage more pro-active behaviors, including provision of system balancing services. In this context, this paper will investigate the potential flexibility and benefits that a coordinated operation of multiple households’ rooftop solar and energy storage can offer to the various sectors of the electricity market. The model will analyze the coordinated operation of multiple households and minimize the supply costs for the whole community while offering flexibility services to the system operator and provide peak demand reduction at the distribution network level. Fundamentally, the proposed model will consider the possibility of households to share energy resources in a peer-to-peer arrangement and thus minimize energy supply costs. In addition, the model also considers the provision of frequency response and reserve services and their associated revenues.Our results have shown significant cost savings can be achieved through a coordinated energy trading and consequently reduce energy transactions with suppliers. Provision offlexibility throughbalancing services becomes the major benefit to support the business case for coordinated operation of storagein low carbon communities.
Yang Y, Hao J, Sun M, et al., 2018, Deep Multiagent Q-Learning for Autonomous Agents in Future Smart Grid, Goran Strbac
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.
Teng F, Pudjianto D, Aunedi M, et al., 2018, Assessment of Future Whole-System Value of Large-Scale Pumped Storage Plants in Europe, Energies, Vol: 11, ISSN: 1996-1073
This paper analyses the impacts and benefits of the pumped storage plant (PSP) and its upgrade to variable speed on generation and transmission capacity requirements, capital costs, system operating costs and carbon emissions in the future European electricity system. The combination of a deterministic system planning tool, Whole-electricity System Investment Model (WeSIM), and a stochastic system operation optimisation tool, Advanced Stochastic Unit Commitment (ASUC), is used to analyse the whole-system value of PSP technology and to quantify the impact of European balancing market integration and other competing flexible technologies on the value of the PSP. Case studies on the Pan-European system demonstrate that PSPs can reduce the total system cost by up to €13 billion per annum by 2050 in a scenario with a high share of renewables. Upgrading the PSP to variable-speed drive enhances its long-term benefits by 10–20%. On the other hand, balancing market integration across Europe may potentially reduce the overall value of the variable-speed PSP, although the effect can vary across different European regions. The results also suggest that large-scale deployment of demand-side response (DSR) leads to a significant reduction in the value of PSPs, while the value of PSPs increases by circa 18% when the total European interconnection capacity is halved. The benefit of PSPs in reducing emissions is relatively negligible by 2030 but constitutes around 6–10% of total annual carbon emissions from the European power sector by 2050.
Badesa L, Teng F, Strbac G, 2018, Economic value of inertia in low-carbon power systems, 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Publisher: IEEE
Most renewable energy sources (RES) do not provide any inertial response. Their integration in a power grid implies a highly reduced level of system inertia, which leads to a deteriorated frequency performance. Then, the requirement for frequency response is significantly increased in order to maintain frequency security. Alternatively, enhanced provision of inertia from auxiliary sources may alleviate this problem. However, the benefits of inertia provision are not yet fully understood. In this paper, an inertia-dependent Stochastic Unit Commitment (SUC) tool is applied to quantify the economic value of inertia. The results demonstrate that enhanced provision of inertia would lead to significant economic savings, although these savings vary under different system conditions. These results should be brought to the attention of both market operators and investors, in order to inform the design of an ancillary-services market for inertia and the investment in auxiliary provision of inertia.
Sanz IM, Judge PD, Spallarossa CE, et al., 2018, Effective Damping Support through VSC-HVDC Links with Short-Term Overload Capability, IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Publisher: IEEE, ISSN: 2165-4816
Damping service provision through VSC-based HVDC links has been extensively covered in the literature. However, little or no attention has been paid to the available range of active and reactive power modulation when the HVDC link is already operating at rated capacity. In these conditions some overload capability is usually assumed, ignoring the physical constraints imposed by the safe operating area of the IGBT modules in the converter. This paper presents, in a unified framework, the provision of damping support from VSC-HVDC links equipped with additional control for short-term overload capability. The performance of a Model Predictive Control (MPC) damping controller that accounts for the extended P/Q operating area of the converter is analysed. Case studies are presented to show that the extracted short-term overload capability can significantly improve the damping support from VSC-HVDC links. Simulation results also include the impact of damping control action on the junction temperatures of the IGBT modules of the converters, quantifying the effect of this service on the semiconductor temperature dynamics.
Teng F, Aunedi M, Strbac G, et al., 2018, Provision of ancillary services in future low-carbon UK electricity system, IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Publisher: IEEE, ISSN: 2165-4816
Integration of intermittent RES into the electricity system imposes a considerable demand for additional flexibility. This paper analyses the challenges on the provision of ancillary services and potential solutions from emerging flexible technologies (including flexible generation, energy storage, demand side response and interconnection) in the future UK electricity system. The results suggest that the cost of reserve and response services in 2030 may increase up to 1.23 B£ and 1.04 B£, respectively. Alternative flexible technologies have been demonstrated to play an important role in the provision of ancillary services, although the benefits vary among different technologies. Furthermore, these flexible technologies can also reduce carbon emission and hence the required amount of high-cost low-carbon generation to achieve the same carbon target.
De Paola A, Papadaskalopoulos D, Angeli D, et 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
Konstantelos I, Strbac G, 2018, The role of storage in transmission investment deferral and management of future planning uncertainty, ENERGY STORAGE AT DIFFERENT VOLTAGE LEVELS: TECHNOLOGY, INTEGRATION, AND MARKET ASPECTS, Editors: Zobaa, Ribeiro, Aleem, Afifi, Publisher: INST ENGINEERING TECH-IET, Pages: 113-145, ISBN: 978-1-78561-349-4
Yang Y, Hao J, Sun M, et al., 2018, Recurrent Deep Multiagent Q-Learning for Autonomous Brokers in Smart Grid, 27th International Joint Conference on Artificial Intelligence (IJCAI), Publisher: IJCAI-INT JOINT CONF ARTIF INTELL, Pages: 569-575
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Ameli H, Qadrdan M, Strbac G, 2017, Techno-economic assessment of battery storage and Power-to-Gas: A whole-system approach, 9th International Conference on Applied Energy (ICAE), Publisher: Elsevier, Pages: 841-848, ISSN: 1876-6102
The power systems in many countries are undergoing a radical transformation through employing a large capacity of renewable generation technologies such as wind turbine and solar photovoltaic. The power generation by wind and solar resources are variable and difficult to predict. Therefore, growing capacities of such technologies is expected to introduce challenges regarding balancing electricity supply and demand. This paper investigates the role of battery storage and power-to-gas systems to accommodate large capacity of intermittent power generation from wind and solar and therefore facilitates matching electricity supply and demand. The Combined Gas and Electricity Networks (CGEN) model was used to optimize the operation of gas and electricity networks in GB for typical weeks in winter and summer in 2030. The role of different capacity of battery storage and power-to-gas systems in reducing the wind curtailment and operating cost of the system were quantified and compared with the annualized cost of these technologies.
Wang S, Wang K, Teng F, et al., 2017, Optimal Allocation of ESSs for Mitigating Fluctuation in Active Distribution Network, 9th International Conference on Applied Energy (ICAE), Publisher: ELSEVIER SCIENCE BV, Pages: 3572-3577, ISSN: 1876-6102
Zhang X, Strbac G, Djapic P, et al., 2017, Optimization of Heat Sector Decarbonization Strategy through Coordinated Operation with Electricity System, Energy Procedia, Vol: 142, Pages: 2858-2863, ISSN: 1876-6102
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
Tzelepis D, Rousis AO, Dysko A, et al., 2017, A new fault-ride-through strategy for MTDC networks incorporating wind farms and modular multi-level converters, INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, Vol: 92, Pages: 104-113, ISSN: 0142-0615
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.
Teng F, Aunedi M, Moreira R, et al., 2017, Business case for distributed energy storage, 24th International Conference & Exhibition on Electricity Distribution (CIRED), Pages: 1605-1608
© 2017 The Institution of Engineering and Technology. All rights reserved. This study presents the analysis carried out to quantify the value that distributed energy storage (ES) installation may deliver to its owner by simultaneously providing multiple services to a number of entities in the electricity sector. In this analysis, a full spectrum of services that ES may deliver are considered: energy arbitrage, balancing services, supporting low-carbon generation, network support, frequency regulation services, and capacity market. The results demonstrate that the net revenues from any single service would be difficult to justify the relatively high investment cost. Optimised provision of multiple services is therefore the key route for ES to make a profitable business case in the market. The potential synergies and conflicts between TSO and DNO services supplied by ES are also analysed.
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