Publications
43 results found
Strbac G, Moreno Vieyra R, Konstantelos I, et al., 2014, Strategic Development of North Sea Grid Infrastructure to Facilitate Least-Cost Decarbonisation, Strategic Development of North Sea Grid Infrastructure to Facilitate Least-Cost Decarbonisation, Publisher: E3G
Offshore wind power is expected to make a significant contribution towards de-carbonisingthe European energy system. It is envisaged that today’s installed capacity levels of about 5GW of offshore wind generation may reach 150GW by 2030, with approximately half of thiscapacity located in the North Seas. Given Europe’s goal of increased integration of the powermarkets by expanding cross-border interconnectors, there is a significant opportunity tointegrate offshore wind generation and interconnector projects in the North Seas in order totake advantage of potentially significant economies of scale and thus reduce network costs.
Pudjianto D, Aunedi M, Djapic P, et al., 2014, Whole-systems assessment of the value of energy storage in low-carbon electricity systems, IEEE Transactions on Smart Grid, Vol: 5, Pages: 1098-1109, ISSN: 1949-3061
Energy storage represents one of the key enabling technologies to facilitate an efficient system integration of intermittent renewable generation and electrified transport and heating demand. This paper presents a novel whole-systems approach to valuing the contribution of grid-scale electricity storage. This approach simultaneously optimizes investment into new generation, network and storage capacity, while minimising system operation cost, and also considering reserve and security requirements. Case studies on the system of Great Britain (GB) with high share of renewable generation demonstrate that energy storage can simultaneously bring benefits to several sectors, including generation, transmission and distribution, while supporting real-time system balancing. The analysis distinguishes between bulk and distributed storage applications, while also considering the competition against other technologies, such as flexible generation, interconnection and demand-side response.
Aunedi M, Kountouriotis P-A, Calderon JEO, et al., 2013, Economic and Environmental Benefits of Dynamic Demand in Providing Frequency Regulation, IEEE TRANSACTIONS ON SMART GRID, Vol: 4, Pages: 2036-2048, ISSN: 1949-3053
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- Citations: 91
Papadaskalopoulos D, Strbac G, Mancarella P, et al., 2013, Decentralized Participation of Flexible Demand in Electricity Markets-Part II: Application With Electric Vehicles and Heat Pump Systems, IEEE TRANSACTIONS ON POWER SYSTEMS, Vol: 28, Pages: 3667-3674, ISSN: 0885-8950
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- Citations: 109
Pudjianto D, Djapic P, Aunedi M, et al., 2013, Smart control for minimizing distribution network reinforcement cost due to electrification, ENERGY POLICY, Vol: 52, Pages: 76-84, ISSN: 0301-4215
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- Citations: 98
Strbac G, Aunedi M, Pudjianto D, et al., 2013, Smart Grid: Facilitating Cost-Effective Evolution to a Low-Carbon Future, TRANSITION TO RENEWABLE ENERGY SYSTEMS, Editors: Stolten, Scherer, Publisher: WILEY-V C H VERLAG GMBH, Pages: 741-771
Aunedi M, Strbac G, 2013, Efficient System Integration of Wind Generation through Smart Charging of Electric Vehicles, 8th International Conference and Exhibition on Ecological Vehicles and Renewable Energies (EVER), Publisher: IEEE
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- Citations: 10
Silva V, Stanojevic V, Aunedi M, et al., 2012, Smart domestic appliances as enabling technology for demand-side integration: Modelling, value and drivers, The Future of Electricity Demand: Customers, Citizens and Loads, Pages: 243-281, ISBN: 9781107008502
Introduction: Decarbonization of future electricity systems requires a significant proportion of electricity consumption to be supplied from nuclear, carbon capture and storage (CCS) plant and renewable sources. Since nuclear and CCS plant are less flexible than, for instance, natural gas-fired combined cycle plants, and renewable sources such as wind, solar and tidal are intermittent, this creates serious challenges to the way the current system is operated. In order to ensure that the system is capable of maintaining a supply and demand balance, the reduction in generation flexibility as a result of incorporating more low-carbon generation technologies has to be balanced with an increase in flexibility from demand. Consequently demand-side flexibility needs to be developed and smart domestic appliances can play an important role (IEA, 2008). In order to gain insight and understanding of the role and value of smart appliances, comprehensive studies of its economic value are required. Such analysis needs to consider relevant parameters such as consumers' behaviour and acceptance, appliance technology and future scenarios of power-system development regarding flexibility of generation and network capacity. This chapter presents a framework to assess the value of smart appliances, as flexible demand, to increase system flexibility and to provide new sources of ancillary services. The increased flexibility will improve system efficiency, reduce operating costs and carbon emissions, and increase utilization of renewable sources; from these benefits the value of smart appliances will be derived. However, any decrease in the value of energy services received as a result of, for instance, inconvenience caused by curtailment or rescheduling of consumption should, in theory, be deducted from such benefits. At the core of the framework is a model that simulates annual system operation, scheduling simultaneously generation and smart appliances, in order to minimize system oper
Pudjianto D, Gan CK, Stanojevic V, et al., 2010, Value of Integrating Distributed Energy Resources in the UK Electricity System, IEEE-Power-and-Energy-Society General Meeting, Publisher: IEEE, ISSN: 1944-9925
Aunedi M, Štrbac G, Pudjianto D, 2009, Characterisation of portfolios of distributed energy resources under uncertainty
The paper proposes a model to determine the optimal strategy of offering electricity at the day-ahead market for a portfolio of Distributed Energy Resources. The stochastic nature of the problem is taken into account through uncertainty of generator output and forecasts of day-ahead and imbalance prices. The model attempts to maximise the expected profit of the portfolio when exposed to imbalance prices and output uncertainty. Portfolios analysed included conventional generators, wind generators, or both. The results indicate that the proposed approach is able to adapt the offering strategy to the risk profile in different times of the day. Also, significant synergic effects are demonstrated when wind and conventional generators are aggregated into a single portfolio, due to increased flexibility in internal portfolio balancing.
Aunedi M, Škrlec D, Štrbac G, 2008, Optimizing the operation of distributed generation in market environment using genetic algorithms, Pages: 780-785
Restructuring and deregulation of the electricity sector have altered the behavior of market players, shifting the objective from cost minimization to profit maximization. Development of distributed generation units, along with concerns raised over the security of supply has prompted many customers to consider the installation of their own local capacity for generating electricity (and heat). This paper proposes a methodology for optimizing the operation of a portfolio of distributed units, based on profit maximization using genetic algorithms. Genetic algorithms are an optimization method based on the analogy with biological evolution, where the so-called population of solutions evolves through generations as a result of recombination, mutation and selection processes. Optimization is carried out based on the day-ahead forecast of hourly market prices of electricity. The method is tested on a set of distributed units, demonstrating the ability to find good solutions in an acceptable time period. © 2008 IEEE.
Aunedi M, Ortega Calderon JE, Silva V, et al., 2008, Economic and Environmental Impact of Dynamic Demand
Aunedi M, Skrlec D, Strbac G, 2008, Optimizing the Operation of Distributed Generation in Market Environment Using Genetic Algorithms, IEEE Mediterranean Electrotechnical Conference, Publisher: IEEE, Pages: 759-+, ISSN: 2158-8481
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- Citations: 1
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