Now showing 1 - 8 of 8
  • Publication
    Optimal firm wind capacity allocation to power systems with security constraints
    Many countries have declared future renewable energy penetration targets. Wind power connection to power systems is delayed by limited transmission system capacity as attractive wind sites are often located in weakly designed transmission areas. Optimal use of existing transmission system resources should be made in the allocation of capacity connection permits. The volume of wind power connection applications and their power production statistical inter-dependencies suggest that they should be assessed in a collective probabilistic manner. This paper uses a sequential probabilistic load flow method in tandem with a linear programming computational geometry constraint redundancy approach to optimally allocate wind capacities given the transmission system capacity that is securely available.
    Scopus© Citations 17  1987
  • Publication
    Aspects of wind energy characteristics in transmission related optimisation models : invited panel discussion paper
    This invited panel paper discussion will outline a number of aspects of wind energy characteristics relevant to the optimal wind/transmission model formulation task. Optimal placement of wind capacity on a constrained transmission network is a typical example of this type of problem. In particular the relevance of advanced and computationally intensive stochastic unit commitment to the model formulation will be debated. Optimization constraint matrix structure and techniques to exploit it will be shown to be of considerable importance for this type of problem. The relative merits of different model dimensionality reduction schemes, either through multivariate component analysis and probability discretisation or indeed scenario reduction, will be discussed. A pragmatic acceptance of the imprecise impact of long-term power system uncertainties will be maintained throughout, and wherever possible generality to different types of power systems will be considered.
    Scopus© Citations 1  475
  • Publication
    Factors influencing wind energy curtailment
    Nonphysically firm wind generation connections (i.e., those to which curtailment can apply) may be necessary for significant wind integration to congested transmission networks. A study of factors influencing this associated wind energy curtailment is, therefore, of timely importance. In this paper, the wind curtailment estimation effects of natural inter-yearly wind profile variability, system demand-profile/fuel-price parameter uncertainty, and minimum system inertial constraints are studied in detail. Results indicate that curtailment estimation error can be reduced by appropriate wind data year-length and sampling-rate choice, though a pragmatic consideration of system parameter uncertainty should be maintained. Congestion-related wind energy curtailment risk due to such parameter uncertainty exhibits appreciable interlocational dependency, suggesting there may be scope for effective curtailment risk management. The coincidence of wind energy curtailment estimated due to network thermal congestion and system wide inertial-stability issues also has commercial significance for systems with very high wind energy penetration targets, suggesting there may be appreciable interaction between different sources of curtailment in reality
    Scopus© Citations 132  2500
  • Publication
    A study of principal component analysis applied to spatially distributed wind power
    Multivariate dimension reduction schemes could be very useful in limiting the number of random statistical variables needed to represent distributed wind power spatial diversity in transmission integration studies. In this paper, principal component analysis (PCA) is applied to the covariance matrix of distributed wind power data from existing Irish wind farms, with the eigenvector/eigenvalue analysis generating a lower number of uncorrelated alternative variables. It is shown that though uncorrelated, these wind components may not necessarily be statistically independent however. A sample application of PCA combined with multivariate probability discretization is also outlined in detail. In that case study, the capability of PCA to reduce the number and prioritize the order of the alternative statistical variables is key to potential wind power production costing simulation efficiency gains, when compared to exhaustive multiyear time series load flow investigations.
    Scopus© Citations 43  1228
  • Publication
    A study of optimal non-firm wind capacity connection to congested transmission systems
    As wind is a low capacity factor source of power generation, a non-physically-firm connection strategy is key to its cost-effective and timely integration to presently constrained transmission networks. This paper therefore outlines the design and study of an optimal non-firm wind capacity allocation model. While a precise statistical representation of wind power variations and geographical inter-dependency requires a significant number of data samples, the structured very-large-scale linear programming problem that results is shown to be exploitable by the Benders’ decomposition scheme. Various wind capacity target levels are considered, and important sensitivity analyses performed for multiple load profiles, wind profiles, and fuel price parameter values. Interestingly, the optimal wind capacity allocation is found to be reasonably robust to sizeable load and fuel price deviations, and while the effect of a limited historical wind data profile is more influential, the associated cost-function penalty is not significantly critical. The economic value of combining wind connection with advanced post-contingency network remedial action schemes is also highlighted.
    Scopus© Citations 32  1165
  • Publication
    Transmission connected wind curtailment with increasing wind capacity connection
    Many countries have ambitious plans to increase wind energy penetration levels in the near future. With a low capacity factor and even lower capacity credit, wind power is a fundamentally different power generation source than conventional plant. Traditional planning methodologies focusing solely on the impact of turbine capacity’s impact on line flow worst-case scenarios may unnecessarily impede cost-effective wind integration. This paper assesses the impact of increased wind capacity connection on wind energy curtailment indices using a security-contrained optimal power flow model. Results indicate significant scope for increased wind capacity connection exists if small levels of wind energy curtailment are accepted.
    Scopus© Citations 12  636
  • Publication
    Maximizing firm wind connection to security constrained transmission networks
    Prudent use of existing transmission capacity could be achieved by an optimal allocation of wind capacity to distinct transmission nodes. The statistical interdependency of geographically separate wind sites and the partially-dispatchable nature of wind power require a collective analysis of all potential wind farms over an extended time-frame in any optimized transmission planning study. The methodology presented in this paper separates this large optimization problem into smaller subtasks, including a year-long sequential time series hourly integer unit commitment, a linear dc load-flow network model with hourly security constraints, and a linear programming optimization model to estimate the maximum firm wind energy penetration for a given network. A novel maximal vector based constraint redundancy analysis is employed to significantly reduce the linear programming optimization dimensionality. Firm wind capacity connections are facilitated in this paper—i.e., those to which wind curtailment to manage congestion is not applicable within a typical system "planning" timeframe analysis. Each bus is allocated firm capacity on the basis of maximizing the possible firm wind energy penetration in the transmission system as a whole, while preserving traditional network security standards.
    Scopus© Citations 78  1429
  • Publication
    Optimal wind power location on transmission systems - a probabilistic load flow approach
    Renewable electrical energy grid connection is hampered by transmission capacity limitations and public opposition to new transmission development. This paper presents a methodology to find the optimal positions on an existing transmission system network to connect ‘firm’ wind capacity to reach desired renewable energy penetration targets in a secure, least-cost manner. The methodology accounts for geographical statistical dependencies of individual bus load and wind farm power outputs, as well as the temporal dependencies of the conventional plant unit-commitment process on total system load and wind patterns. This is accomplished using a probabilistic load flow technique based on DC load-flow and recorded load and wind time series. A discretised model of the resultant multi-dimensional probability density function is used to define line flow constraints in a linear programming optimization model. The algorithm objectively allocates wind capacity with respect to the wind resource and transmission capacity in each area.
      2066