Distributed MPC for Thermal Comfort and Load Allocation with Energy Auction

This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using an integrated demand-side management approach that involves a power price auction and an appliance loads allocation scheme. The control objective for each subsystem (house or building) aims to minimize the energy cost while maintaining the indoor temperature inside comfort limits. In a distributed coordinated multi-agent ecosystem, each house or building control agent achieves its objectives while sharing, among them, the available energy through the introduction of particular coupling constraints in their underlying optimization problem. Coordination is maintained by a daily green energy auction bring in a demand-side management approach. Also the implemented distributed MPC algorithm is described and validated with simulation studies.

Constrained Consumption Shifting Management in the Distributed Energy Resources Scheduling Considering Demand Response

Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

Optimization of Generation and Aggregated Consumption Shifting for Demand Response Programs Definition

The concept of demand response has drawing attention to the active participation in the economic operation of power systems, namely in the context of recent electricity markets and smart grid models and implementations. In these competitive contexts, aggregators are necessary in order to make possible the participation of small size consumers and generation units. The methodology proposed in the present paper aims to address the demand shifting between periods, considering multi-period demand response events. The focus is given to the impact in the subsequent periods. A Virtual Power Player operates the network, aggregating the available resources, and minimizing the operation costs. The illustrative case study included is based on a scenario of 218 consumers including generation sources.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.

Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy

One of the most common Demand Side Management programs consists of Time-of-Use (TOU) tariffs, where consumers are charged differently depending on the time of the day when they make use of energy services. This paper assesses the impacts of TOU tariffs on a dataset of residential users from the Province of Trento in Northern Italy in terms of changes in electricity demand, price savings, peak load shifting and peak electricity demand at substation level. Findings highlight that TOU tariffs bring about higher average electricity consumption and lower payments by consumers. A significant level of load shifting takes place for morning peaks. However, issues with evening peaks are not resolved. Finally, TOU tariffs lead to increases in electricity demand for substations at peak time.

Controlo preditivo distribuído em edifícios para conforto térmico e alocação de cargas

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Demand response from the non-domestic sector: early UK experiences and future opportunities

Demand response is believed by some to become a major contributor towards system balancing in future electricity networks. Shifting or reducing demand at critical moments can reduce the need for generation capacity, help with the integration of renewables, support more efficient system operation and thereby potentially lead to cost and carbon reductions for the entire energy system. In this paper we review the nature of the response resource of consumers from different non-domestic sectors in the UK, based on extensive half hourly demand profiles and observed demand responses. We further explore the potential to increase the demand response capacity through changes in the regulatory and market environment. The analysis suggests that present demand response measures tend to stimulate stand-by generation capacity in preference to load shifting and we propose that extended response times may favour load based demand response, especially in sectors with significant thermal loads.

Using standby generators in support of an electricity network: logistics and experience

Electricity load shifting is becoming a big topic in the world of ‘green’ retail. Marks & Spencer (M&S) aim to become the world’s most sustainable retailer (1) and part of that commitment means contributing to the future electricity network. While intelligent operation of fridges and Heating, Ventilation and Air Conditioning (HVAC) systems are a wide area of research, standby generators should be considered too, as they are the most widely adopted form of distributed generation. In this paper, the experience of using standby generators in Northern Ireland to support the grid is shared and the logistics of future projects are discussed. Interactions with maintenance schedules, electricity costs, grid code, staffing and store opening times are discussed as well as the financial implications associated with running generators for grid support.

Determinação do posicionamento ótimo de apoios em pontes

This paper presents a study to determine the optimal support positions in bridges, as well as the optimal relation between the spans of beams, aiming both the reduction and the unifirmization of the efforts in these structures. The mathematical problem is formulated in order to minimize the maximum bending moments, taking the coordinate of each internal support as design variable. To take into account possible location limitations, size constraints are also considered in the formulation. The software developed based on this study determines the efforts in each support for load shifting along the structure by the usage of the Displacement Method, and the optimization is performed with a mathematical programming technique. The structures analyzed from the computational implementation of the idealized model point to the validation and efficiency of the proposed procedure.

El papel de la hidroelectricidad en el contexto de las energías renovables en España

En el artículo se discute el papel de la energía hidroeléctrica en el marco del sistema eléctrico español, donde existe una elevada penetración de energías no gestionables con una tendencia clara a aumentar en los próximos años. El desarrollo de nuevas centrales hidroeléctricas se basará probablemente en centrales reversibles. La energía hidroeléctrica es una tecnología madura y eficiente para el almacenamiento de energía a gran escala y contribuye por tanto de manera decisiva a la integración de fuentes renovables no gestionables. Los beneficios obtenidos con la operación punta-valle pueden ser insuficientes para compensar el coste de una nueva central. Sin embargo, los ingresos obtenidos pueden incrementarse sustancialmente mediante su participación en los servicios de ajuste del sistema. Ello requeriría un diseño apropiado del mercado eléctrico. La contribución de las centrales hidráulicas reversibles al balance producción-consumo puede extenderse a las horas valle utilizando, bien bombeo en velocidad variable o bien una configuración de cortocircuito hidráulico. La necesidad de mitigar los efectos hidrológicos aguas abajo de las centrales hidroeléctricas puede introducir algunas restricciones en la operación que limitaría de algún modo los servicios descritos más arriba. Sin embargo, cabe esperar que los efectos ambientales provocados por las centrales hidráulicas reversibles sean significativamente menores. In this paper the role of hydropower in electric power systems is discussed, in the framework of the Spanish system, where a high penetration of intermittent power sources exists, showing a clear trend to increase in next years. The development of new hydro power facilities will be likely based on pumped storage hydro power plants. Hydropower is a mature and efficient technology for large-scale energy storage and therefore represents a key contribution for the integration of intermittent power sources, such as wind or photovoltaic. The benefits obtained from load shifting may be insufficient to compensate the costs of a new plant. However, the obtained revenues can significantly increase through its contribution to providing ancillary services. This would require an appropriate design of the electricity market. The contribution of pumped storage hydro power plants to balancing services can be extended to off-peak hours, using either variable speed pumping or the hydraulic shortcircuit configuration. The need to mitigate hydrological effects downstream of hydro plants may introduce some operational constraints which could limit to some extent the services described above. However environmental effects caused by pumped storage hydro power plants are expected to be significantly smaller.

Contraction due to microtubule disruption is associated with increased phosphorylation of myosin regulatory light chain.

Microtubules have been proposed to function as rigid struts which oppose cellular contraction. Consistent with this hypothesis, microtubule disruption strengthens the contractile force exerted by many cell types. We have investigated alternative explanation for the mechanical effects of microtubule disruption: that microtubules modulate the mechanochemical activity of myosin by influencing phosphorylation of the myosin regulatory light chain (LC20). We measured the force produced by a population of fibroblasts within a collagen lattice attached to an isometric force transducer. Treatment of cells with nocodazole, an inhibitor of microtubule polymerization, stimulated an isometric contraction that reached its peak level within 30 min and was typically 30-45% of the force increase following maximal stimulation with 30% fetal bovine serum. The contraction following nocodazole treatment was associated with a 2- to 4-fold increase in LC20 phosphorylation. The increases in both force and LC20 phosphorylation, after addition of nocodazole, could be blocked or reversed by stabilizing the microtubules with paclitaxel (former generic name, taxol). Increasing force and LC20 phosphorylation by pretreatment with fetal bovine serum decreased the subsequent additional contraction upon microtubule disruption, a finding that appears inconsistent with a load-shifting mechanism. Our results suggest that phosphorylation of LC20 is a common mechanism for the contractions stimulated both by microtubule poisons and receptor-mediated agonists. The modulation of myosin activity by alterations in microtubule assembly may coordinate the physiological functions of these cytoskeletal components.

Effects of Information and Time of Use Pricing on Irish Electricity Demand and Supply

In this dissertation I quantify residential behavior response to interventions designed to reduce electricity demand at different periods of the day. In the first chapter, I examine the effect of information provision coupled with bimonthly billing, monthly billing, and in-home displays, as well as a time-of-use (TOU) pricing scheme to measure consumption over each month of the Irish Consumer Behavior Trial. I find that time-of-use pricing with real time usage information reduces electricity usage up to 8.7 percent during peak times at the start of the trial but the effect decays over the first three months and after three months the in-home display group is indistinguishable from the monthly treatment group. Monthly and bi-monthly billing treatments are not found to be statistically different from another. These findings suggest that increasing billing reports to the monthly level may be more cost effective for electricity generators who wish to decrease expenses and consumption, rather than providing in-home displays. In the following chapter, I examine the response of residential households after exposure to time of use tariffs at different hours of the day. I find that these treatments reduce electricity consumption during peak hours by almost four percent, significantly lowering demand. Within the model, I find evidence of overall conservation in electricity used. In addition, weekday peak reductions appear to carry over to the weekend when peak pricing is not present, suggesting changes in consumer habit. The final chapter of my dissertation imposes a system wide time of use plan to analyze the potential reduction in carbon emissions from load shifting based on the Ireland and Northern Single Electricity Market. I find that CO2 emissions savings are highest during the winter months when load demand is highest and dirtier power plants are scheduled to meet peak demand. TOU pricing allows for shifting in usage from peak usage to off peak usage and this shift in load can be met with cleaner and cheaper generated electricity from imports, high efficiency gas units, and hydro units.

Optimal switch allocation for automatic load transfer in distribution substations

This work proposes a methodology for optimized allocation of switches for automatic load transfer in distribution systems in order to improve the reliability indexes by restoring such systems which present voltage classes of 23 to 35 kV and radial topology. The automatic switches must be allocated on the system in order to transfer load remotely among the sources at the substations. The problem of switch allocation is formulated as nonlinear constrained mixed integer programming model subject to a set of economical and physical constraints. A dedicated Tabu Search (TS) algorithm is proposed to solve this model. The proposed methodology is tested for a large real-life distribution system. © 2011 IEEE.

The effect of load on agent-based algorithms for distributed task allocation

Multi-agent algorithms inspired by the division of labour in social insects and by markets, are applied to a constrained problem of distributed task allocation. The efficiency (average number of tasks performed), the flexibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved efficiency and robustness. We employ nature inspired particle swarm optimisation to obtain optimised parameters for all algorithms in a range of representative environments. Although results are obtained for large population sizes to avoid finite size effects, the influence of population size on the performance is also analysed. From a theoretical point of view, we analyse the causes of efficiency loss, derive theoretical upper bounds for the efficiency, and compare these with the experimental results.