Now showing 1 - 10 of 17
  • Publication
    Lumped Parameter Building Model Calibration using Particle Swarm Optimization
    This paper presents a methodology for the automated calibration of deterministic lumped parameter models in building energy simulation using optimization methods. A heterogeneous model topology is proposed to represent a residential building archetype developed in the EnergyPlus simulation environment. The archetype model has previously been used to characterize the domestic building stock in Ireland. The automated calibration problem is solved as a least squares error problem solved using a local optimization method (Sequential Quadratic Programming) and two heuristics methods (Particle Swarm Optimization and Genetic Algorithm). It is shown that Particle Swarm Optimization provides the best performance for this particular problem and provides an inherent robustness under model uncertainty.
  • Publication
    An integrated Building-to-Grid model for evaluation of energy arbitrage value of Thermal Storage
    Thermal Electric Storage (TES) has emerged as a promising technology for enhancing the flexibility of the built environment to participate in active Demand Side Management (DSM). These devices allow the decoupling of intra-day scheduling of electric power demand from the time of thermal energy end-use. Therefore, if enabled with communication with the grid, these devices can facilitate load shifting and energy arbitrage. This study evaluates the energy arbitrage value of smart TES devices in residential buildings across Ireland. A Building-to-Grid (B2G) model has been developed which integrates the buildings thermal dynamics and end-use constraints with the power systems economic dispatch model. The thermal behavior of the houses and the TES space heater and hot water tank is modeled through linear state space models for three different mid-flat archetypes. The optimization results show the load shifting and arbitrage potential of TES and its impacts on wind curtailment considering various penetration levels of these devices.
  • Publication
    Optimal charging schedules for thermal electric storage in the absence of communication
    Thermal Electric Storage (TES) has emerged as a promising power-to-heat technology with the potential of enabling active Demand Side Management (DSM). Optimal exploitation of the DSM capability of TES devices requires twoway communication with the grid. However, several contingencies and/or limitations on communication capabilities would render these storage devices incapable of being of any service to the system. This study presents the development of optimal charging schedules for the distributed TES devices which would determine the operation of these devices in the absence of communication. Different strategies are proposed which determine optimal TES charging dependence on local parameters including time of the day, household power consumption and outside temperature. Performance of the proposed charging schedules is then compared to the optimal communication-enabled and the conventional night-time charging scenarios for the All-Island Power System (AIPS). The results demonstrate the superiority of the proposed strategies as compared to the conventional night-time charging in terms of significant reduction in annual generation costs and energy consumption. Additionally, charging based on the proposed strategies can achieve up to 43% of the total cost savings potential of the communication-enabled scenario.
  • 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.
  • Publication
    Challenges in utilisation of demand side response for operating reserve provision
    Utilisation of flexible demand to provide contingency reserves is generally considered beneficial to power systems, and can be a key enabler for ambitious renewable energy penetrations. Detailed techno-economic analysis of reserve provision from flexible demand is considered in this paper. A unit commitment/economic dispatch problem is set up that recognises demand side response (DSR) as a source of primary operating reserve (POR). Dispatch schedules are then verified with frequency stability assessments to quantify any changes in system performance. It has been demonstrated that while generally beneficial, utilization of DSR does not always improve system performance. Factors such as changes in plant dispatch (largest in-feed contingency can be greater) and flexible demand resource variability have been shown to limit the benefits of DSR under certain conditions. Actual activation of DSR for POR is also shown to compromise network integrity in some cases. All results are demonstrated using the Irish power system.       
  • 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.
      1064Scopus© Citations 31
  • Publication
    Ensemble Calibration of Lumped Parameter Retrofit Building Models using Particle Swarm Optimization
    Simulation-based building retrofit analysis tools and electricity grid expansion planning tools are not readily compatible. Their integration is required for the combined study of building retrofit measures and electrified heating technologies using low-carbon electricity generation. The direct coupling of these modelling frameworks requires the explicit mathematical representation of Energy Conservation Measures (ECMs) in building-to-grid energy system models. The current paper introduces an automated calibration methodology which describes retrofitted buildings as parametric functions of ECMs. The buildings are represented using a lumped parameter modelling framework. A baseline model, representative of the building prior to retrofit, and the retrofit functions are calibrated using Particle Swarm Optimization. Synthetic temperature and heating load time-series data were generated using an EnergyPlus semi-detached house archetype model. The model is representative of this residential building category in Ireland. It is shown that the proposed methodology calibrates retrofitted building models to an acceptable level of accuracy (MAE below 0.5 °C). The methodologies introduced in the current paper are capable of generating lumped parameter building models with similar dynamics for different ECMs for any archetype building energy model. The identified building retrofit models have the potential to be integrated with electricity grid models in a computationally-efficient manner.
      410Scopus© Citations 16
  • Publication
    Evaluation of Flexibility Impacts of Thermal Electric Storage Using an Integrated Building-to-Grid Model
    Demand Side Management (DSM) using Thermal Electric Storage (TES) presents a promising opportunity for enhancing the system flexibility, resulting in reliable and economic operation of future low-carbon power systems. Systemwide analysis of the flexibility potential of TES necessitates representation of dynamic thermal models in large-scale power systems models. Therefore, this study presents a novel Buildingto- Grid (B2G) model integrating buildings’ thermal dynamics and end-use constraints with a security-constrained unit commitment model for energy and reserve scheduling. The behaviour of residential thermal demand is represented through linear state space (RC-equivalent) models for different residential archetypes. The B2G model is subsequently used to evaluate the energy arbitrage and reserve provision potential of TES for a test system and various sensitivity analyses for wind penetration levels and presence of other flexibility options have been conducted. The optimisation results highlight the significant value of TES in terms of annual generation cost savings, reserve provision, peak load reduction and utilization of wind energy. The findings also emphasize the importance of co-optimising energy arbitrage and reserve provision from TES devices vis-a-vis system performance and household energy consumption scheduling
      404Scopus© Citations 3
  • 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
      2353Scopus© Citations 121