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  • 1. Coville, Aidan
    et al.
    Siddiqui, Afzal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Vogstad, Klaus-Ole
    The effect of missing data on wind resource estimation2011In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 36, no 7, p. 4505-4517Article in journal (Refereed)
    Abstract [en]

    Investment in renewable energy sources requires reliable data. However, meteorological datasets are often plagued by missing data, which can bias energy resource estimates if the missingness is systematic. We address this issue by considering the influence of missing data due to icing of equipment during the winter on the wind resource estimation for a potential wind turbine site in Norway. Using a mean-reverting jump-diffusion (MRJD) process to model electricity prices, we also account for the impact on the expected revenue from a wind turbine constructed at the site. While missing data due to icing significantly bias the wind resource estimate downwards, their impact on revenue estimates is dampened because of volatile electricity spot prices. By contrast, with low-volatility electricity prices, the effect of missing data on revenue estimates is highly significant. The seasonality-based method we develop removes most of the bias in wind resource and revenue estimation caused by missing data.

  • 2.
    Olsson, Olle
    et al.
    Stockholm University, Stockholm Environment Institute. School for Forest Management, Swedish University of Agricultural Sciences (SLU).
    Hillring, Bengt
    School for Forest Management, Swedish University of Agricultural Sciences (SLU).
    The wood fuel market in Denmark: price development, market efficiency and internationalization2014In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 78, p. 141-148Article in journal (Refereed)
    Abstract [en]

    In this paper, the Danish wood fuel market is investigated. The analysis consists of three parts. First, the development of price dispersion over time for wood chips and wood pellets is examined as a proxy for market transparency. Second, the interconnections between the prices of pellets, chips and straw are studied by use of cointegration analysis. Finally, relations between wood fuel prices in Denmark and Sweden are analyzed. The result is that price dispersion has decreased notably for wood pellets, but not for wood chips. In terms of intra-fuel cointegration, the results point towards the presence of cointegration between prices of wood chips and straw. There are also indications that the Swedish and Danish markets for wood pellets are integrated but this is not the case for wood chips. Given that Sweden and Denmark trade wood pellets between each other and also import from common third sources, it is logical that pellet prices are cointegrated. The conclusions from this study strengthen the view that markets for wood chips and wood pellets have different characteristics, not least as a result of the lack of transparency resulting from the significant product heterogeneity for wood chips.

  • 3. Quiggin, Daniel
    et al.
    Cornell, Sarah
    Stockholm University, Stockholm Resilience Centre.
    Tierney, Michael
    Buswell, Richard
    A simulation and optimisation study: Towards a decentralised microgrid, using real world fluctuation data2012In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 41, no 1, p. 549-559Article in journal (Refereed)
    Abstract [en]

    A transition to a decentralised, decarbonised energy system for the domestic sector is constrained by the difficulty of obtaining energy balance between fluctuating demand and the intermittent, non-dispatchable power supply delivered by most renewables. A microgrid system including a mix of renewable generation technologies, energy storage and demand response (DR) systems has been modelled using a linear programming approach, based on real world data of residential energy consumption and weather variables. This model allows the exploration of the effects of fluctuations in demand and supply, microgrid scale and configuration, energy management options and alternative optimisation criteria. The model demonstrates quantitatively that a mixed-renewables microgrid system can reduce demand fluctuations and improve energy balance. Peak demand hour fluctuations were reduced by up to 19% for a simulated microgrid containing 144 households with one renewable unit and four batteries per household, with a renewables mix of 83% photovoltaic (PV) panels and 17% wind turbines. With this system, the demand on macrogrid energy supply was reduced by 16%, CO2 emissions associated with energy use were reduced by 10% for all hours of operation, and by 74% during the hours of renewable supply. These findings suggest that microgrids using contemporary technologies can contribute significantly to CO2 mitigation targets.

  • 4. Reichenberg, Lina
    et al.
    Siddiqui, Afzal S.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. University College London, United Kingdom; HEC, Canada.
    Wogrin, Sonja
    Policy implications of downscaling the time dimension in power system planning models to represent variability in renewable output2018In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 159, p. 870-877Article in journal (Refereed)
    Abstract [en]

    Due to computational constraints, power system planning models are typically unable to incorporate full annual temporal resolution. In order to represent the increased variability induced by large amounts of variable renewable energy sources, two methods are investigated to reduce the time dimension: the integral approach (using typical hours based on demand and renewable output) and the representative days method (using typical days to capture annual variability). These two approaches are tested with a benchmark implementation that incorporates full time representation in order identify their suitability for assessing power systems with high renewable penetration. The integral method predicts renewable capacities within a 10% error margin, this paper's main performance metric, using just 32 time steps, while the representative days approach needs 160–200 time steps before providing similarly accurate renewable capacity estimates. Since the integral method generally cannot handle variation management, such as trade and storage, without enhancing the state-space representation, it may be more applicable to one-node models, while the representative days method is suitable for multi-regional models. In order to assess power systems with increasing renewable policy targets, models should be designed to handle at least the 160 time steps needed to provide results that do not systematically overestimate the renewable capacity share.

  • 5. Rintamäki, Tuomas
    et al.
    Siddiqui, Afzal S.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. University College London, United Kingdom.
    Salo, Ahti
    How much is enough? Optimal support payments in a renewable-rich power system2016In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 117, no 1, p. 300-313Article in journal (Refereed)
    Abstract [en]

    The large-scale deployment of intermittent renewable energy sources may cause substantial power imbalance. Together with the transmission grid congestion caused by the remoteness of these sources from load centers, this creates a need for fast-adjusting conventional capacity such as gas-fired plants. However, these plants have become unprofitable because of lower power prices due to the zero marginal costs of renewables. Consequently, policymakers are proposing new measures for mitigating balancing costs and securing supply. In this paper, we take the perspective of the regulator to assess the effectiveness of support payments to flexible generators. Using data on the German power system, we implement a bi-level programming model, which shows that such payments for gas-fired plants in southern Germany reduce balancing costs and can be used as part of policy to integrate renewable energy.

  • 6. Rocha, Paula
    et al.
    Kaut, Michal
    Siddiqui, Afzal S.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. University College London, United Kingdom.
    Energy-efficient building retrofits: An assessment of regulatory proposals under uncertainty2016In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 101, p. 278-287Article in journal (Refereed)
    Abstract [en]

    Improving energy efficiency in European Union buildings will require retrofitting much of the existing stock due to limited new construction opportunities. Given uncertainty in energy prices and technology costs stemming from deregulation, a stochastic optimisation framework is desirable for long-term decision support. We synthesise treatment of uncertainty and risk management to obtain insights about the impact of retrofits on energy consumption, costs, CO2 emissions, and risk at real buildings in Austria and Spain. The optimal strategy for the Spanish site is to invest in photovoltaic and solar thermal technologies. This lowers expected costs by 8.5% and reduces expected primary energy consumption and CO2 emissions by 20% relative to using existing equipment. By limiting exposure to volatile energy prices, the strategy also yields a nearly 10% reduction in risk. We obtain similar results also for the Austrian site. Via this framework, tradeoffs among competing objectives and the effectiveness of proposed regulation may be assessed. Specifically, we find that more stringent restrictions on energy efficiency are economically viable if regulation also facilitates enhanced operational decision support for buildings. Indeed, primary energy consumption can be lowered only through more on-site generation such as combined heat and power, which is more complex for building managers to deploy.

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