The Experts below are selected from a list of 60210 Experts worldwide ranked by ideXlab platform
W Wim Zeiler - One of the best experts on this subject based on the ideXlab platform.
-
Economic model predictive control for Demand Flexibility of a residential building
Energy, 2019Co-Authors: Cj Christian Finck, Rongling Li, W Wim ZeilerAbstract:Future building energy management systems will have to be capable of adapting to variation in the rate of production of energy from renewable sources. Controllers employing a model predictive control (MPC) framework can optimise and schedule energy usage based on the availability of renewably generated energy. In this paper, an MPC using artificial neural networks (ANNs) was implemented in a residential building. The ANN-MPC was successfully tested and demonstrated good performance predicting the building's energy consumption. The controller was then modified to function as an economic MPC (EMPC) to optimise Demand Flexibility (i.e., the ability to adapt energy Demands to fluctuations in supply). The operational costs of energy usage were associated with this Demand Flexibility, which was represented by three Flexibility indicators: Flexibility factor, supply cover factor, and load cover factor. The results from a day-long test showed that these Flexibility indicators were maximised (Flexibility factor ranged from −0.88 to 0.67, supply cover factor from 0.04 to 0.13, and load cover factor from 0.07 to 0.16) when the EMPC controller's Demand Flexibility was compared to that of a conventional proportional-integral (PI) controller. The EMPC framework for Demand Flexibility can be used to regulate on-site energy generation, grid consumption, and grid feed-in and can thus serve as a basis for overall optimisation of the operation of heating systems to achieve greater Demand Flexibility.
-
Quantifying Demand Flexibility of power-to-heat and thermal energy storage in the control of building heating systems
Applied Energy, 2018Co-Authors: Cj Christian Finck, Rp Rick Kramer, W Wim ZeilerAbstract:Abstract In the future due to continued integration of renewable energy sources, Demand-side Flexibility would be required for managing power grids. Building energy systems will serve as one possible source of energy Flexibility. The degree of Flexibility provided by building energy systems is highly restricted by power-to-heat conversion such as heat pumps and thermal energy storage possibilities of a building. To quantify building Demand Flexibility, it is essential to capture the dynamic response of the building energy system with thermal energy storage. To identify the maximum Flexibility a building’s energy system can provide, optimal control is required. In this paper, optimal control serves to determine in detail Demand Flexibility of an office building equipped with heat pump, electric heater, and thermal energy storage tanks. The Demand Flexibility is quantified using different performance indicators that sufficiently characterize Flexibility in terms of size (energy), time (power) and costs. To fully describe power Flexibility, the paper introduces the instantaneous power Flexibility as power Flexibility indicator. The instantaneous power Flexibility shows the potential power Flexibility of TES and power-to-heat in any case of charging, discharging or idle mode. A simulation case study is performed showing that a water tank, a phase change material tank, and a thermochemical material tank integrated with building heating system can be designed to provide Flexibility with optimal control.
Goran Strbac - One of the best experts on this subject based on the ideXlab platform.
-
Investigating the impact of flexible Demand on market-based generation investment planning
International Journal of Electrical Power & Energy Systems, 2020Co-Authors: Temitayo Oderinwale, Dimitrios Papadaskalopoulos, Goran StrbacAbstract:Abstract Demand Flexibility has attracted significant interest given its potential to address techno-economic challenges associated with the decarbonisation of electricity systems. However, previous work has investigated its long-term impacts through centralized generation planning models which do not reflect the current deregulated environment. At the same time, existing market-based generation planning models are inherently unable to capture the Demand Flexibility potential since they neglect time-coupling effects and system reserve requirements in their representation of the electricity market. This paper investigates the long-term impacts of Demand Flexibility in the deregulated environment, by proposing a time-coupling, bi-level optimization model of a self-interested generation company’s investment planning problem, which captures for the first time the energy shifting Flexibility of the Demand side and the operation of reserve markets with Demand side participation. Case studies investigate different cases regarding the Flexibility of the Demand side and different market design options regarding the allocation of reserve payments. The obtained results demonstrate that, in contrast with previous centralised planning models, the proposed model can capture the dependency of generation investment decisions and the related impacts of Demand Flexibility on the electricity market design and the subsequent strategic response of the self-interested generation company.
-
incorporating Demand Flexibility in strategic generation investment planning
International Conference on the European Energy Market, 2018Co-Authors: Temitayo Oderinwale, Dimitrios Papadaskalopoulos, Goran StrbacAbstract:The envisaged decarbonization of electricity systems has attracted significant interest around the role and value of Demand Flexibility. However, the impact of this Flexibility on generation investments in the deregulated electricity industry setting remains a largely unexplored area, since previous relevant work neglects the time-coupling nature of Demand shifting potentials. This paper addresses this challenge by proposing a strategic generation investment planning model expressing the decision making process of a self-interested generation company and accounting for the time-coupling operational characteristics of Demand Flexibility. This model is formulated as a multi-period bi-level optimization problem, which is solved after converting it to a Mathematical Program with Equilibrium Constraints (MPEC). Case studies with the proposed model demonstrate that Demand Flexibility reduces the total generation capacity investment, enhances investments in baseload generation and yields significant economic benefits in terms of total system costs and Demand payments.
-
decentralized participation of flexible Demand in electricity markets part ii application with electric vehicles and heat pump systems
IEEE Transactions on Power Systems, 2013Co-Authors: Dimitrios Papadaskalopoulos, Pierluigi Mancarella, Goran Strbac, Marko Aunedi, V StanojevicAbstract:Realizing the significant Demand Flexibility potential in deregulated power systems requires its suitable integration in electricity markets. Part I of this work has presented the theoretical, algorithmic and implementation aspects of a novel pool market mechanism achieving this goal by combining the advantages of centralized mechanisms and dynamic pricing schemes, based on Lagrangian relaxation (LR) principles. Part II demonstrates the applicability of the mechanism, considering two reschedulable Demand technologies with significant potential, namely electric vehicles with flexible charging capability and electric heat pump systems accompanied by heat storage for space heating. The price response sub-problems of these technologies are formulated, including detailed models of their operational properties. Suitable case studies on a model of the U.K. system are examined in order to validate the properties of the proposed mechanism and illustrate and analyze the benefits associated with the market participation of the considered technologies.
-
decentralized participation of flexible Demand in electricity markets part i market mechanism
IEEE Transactions on Power Systems, 2013Co-Authors: Dimitrios Papadaskalopoulos, Goran StrbacAbstract:In the deregulated power systems setting, the realization of the significant Demand Flexibility potential should be coupled with its integration in electricity markets. Centralized market mechanisms raise communication, computational and privacy issues while existing dynamic pricing schemes fail to realize the actual value of Demand Flexibility. In this two-part paper, a novel day-ahead pool market mechanism is proposed, combining the solution optimality of centralized mechanisms with the decentralized Demand participation structure of dynamic pricing schemes and based on Lagrangian relaxation (LR) principles. Part I presents the theoretical background, algorithmic approaches and suitable examples to address challenges associated with the application of the mechanism and provides an implementation framework. Non-convexities in reschedulable Demand participants' price response and their impacts on the ability of the basic LR structure to reach feasible market clearing solutions are identified and a simple yet effective LR heuristic method is developed to produce both feasible and high quality solutions by limiting the concentrated shift of reschedulable Demand to the same low-priced time periods.
Roberto Napoli - One of the best experts on this subject based on the ideXlab platform.
-
definitions of Demand Flexibility for aggregate residential loads
IEEE Transactions on Smart Grid, 2016Co-Authors: Intisar Ali Sajjad, Gianfranco Chicco, Roberto NapoliAbstract:Nowadays, enhanced knowledge of the nature of the electricity Demand is achieved through the progressively increasing deployment of smart meters and advanced data analysis techniques. One of the major challenges is to exploit this knowledge to support the introduction of strategies to modify the Demand according to relevant objectives to be achieved, like users’ participation in Demand response programmes. A key point for facing this challenge is to characterize the Demand Flexibility. In spite of many discussions about the concept of Flexibility, the few mathematical definitions of Flexibility available do not address the variation in time of the overall Demand aggregation. This paper starts from the analysis of time-variable patterns of aggregate residential customers, ending up with suitable definitions of expected Flexibility for aggregate Demand. These definitions are based on assessing positive and negative pattern variations and are identified from the analysis of the collective behavior of the aggregate users. A set of results is shown for different numbers of aggregate customers, by considering different values of the averaging time step for load pattern representation.
-
Demand Flexibility time intervals for aggregate residential load patterns
IEEE PowerTech Conference, 2015Co-Authors: Intisar Ali Sajjad, Gianfranco Chicco, Roberto NapoliAbstract:This paper deals with the definition of Demand Flexibility time intervals. These intervals are extracted from the binomial probability model of load variation patterns with the two possible categories of increase and non-increase in Demand. These intervals along with the information on the coefficient of variation of the aggregate Demand are used to assess the potential of Demand Flexibility exhibited by the aggregate residential Demand in different periods of the day. The results of the proposed approach are useful for the distribution system operator or an aggregator to effectively set up Demand response programmes in suitable time slots of the day.
P H Nguyen - One of the best experts on this subject based on the ideXlab platform.
-
machine learning for agile and self adaptive congestion management in active distribution networks
International Conference on Environment and Electrical Engineering, 2019Co-Authors: Muhammad Babar, M H Roos, P H NguyenAbstract:Although congestion management via Demand Response (DR) has gain sufficient popularity recently, there are still some fundamental impediments to achieve a trade-off between Demand Flexibility scheduling and Demand Flexibility dispatch for congestion management. To find a solution to the challenge, the paper introduces the concept and design of an Agile Net, which is an agile control strategy for congestion management. The model of Agile Net has triple cores. First, it percepts the network environment by using the concept of Demand elasticity. Second, it possesses an online model-free learning technique for the management of network externality, such as congestion. Third, it enables distributed system scalability. The efficiency of the proposed Agile Net is investigated by extending the simulation tool for DR paradigm for a generic low-voltage network of the Netherlands. Simulation results reveal a significant reduction in congestion over a year while confirming expected levels of performance.
-
quantifying Demand Flexibility based on structural thermal storage and comfort management of non residential buildings a comparison between hot and cold climate zones
Applied Energy, 2017Co-Authors: L A Hurtado, P H Nguyen, Joshua D Rhodes, I G Kamphuis, Michael E WebberAbstract:Recently, Demand Flexibility has been highlighted as a promising distributed resource from the customer side, especially from industrial customers like commercial buildings, capable of providing grid support services. However, the quantification of Demand Flexibility is a complex process that requires a methodology including the requirements of both the grid operators and the customers. This paper proposes a novel approach to quantify the available Demand Flexibility of individual buildings, while taking into account the underlying building energy physics. The proposed approach constructs on the operational Flexibility concept from the power systems, and extends it to include a comfort domain, identifying different Flexibility parameters with the aim of giving a better insight into the Flexibility potential of commercial buildings. This method includes a development of building energy simulations to assess the effects of weather variations, construction types, and comfort constrains on Demand Flexibility. The proposed quantification method has been validated using 15 different office building models and two different climate zones, i.e., the Netherlands and Texas, US. The results presented in this paper suggest that buildings located in a hot climate could offer higher Flexibility potential during shorter time ranges, while buildings in a cold climate could offer lower Flexibility potential but during longer time ranges. Determining these differences could potentially facilitate the dispatch of flexible Demand resources, to assess their real potential, and to schedule Demand Flexibility between stakeholders.
-
real time congestion management in active distribution network based on dynamic thermal overloading cost
Power Systems Computation Conference, 2016Co-Authors: A N M M Haque, P H Nguyen, D S Shafiullah, F W BliekAbstract:The rapid proliferation of distributed energy resources (DERs) leads to capacity challenges, i.e. network congestions, in the low-voltage (LV) distribution networks. Different types of control strategies are being developed to tackle the challenges with direct switching actions such as load shedding or power curtailment. Alternatively, Demand Flexibility from the large number of DERs is being considered as a potential approach by influencing the individual end-users with various Demand response (DR) programs. However, most of the DR-based solutions focus on scheduling phase, thus having a limitation to handle network issues in real-time grid operation. In order to improve DR's capability, besides a proper incentive scheme for involved actors, the DR-based approach needs to integrate network constraints and quantify this real-time information in its control process. In this paper, a novel method for real-time congestion management is proposed, which focuses on resolving the congestion problem at the MV/LV transformer. Detail models for different loads and thermal overloading of the MV/LV transformer are developed to realize the benefits of the Demand Flexibility. The overall performance of the integrated approach for the congestion management has been verified by a simulation with a typical LV network of the Netherlands.
Pierluigi Siano - One of the best experts on this subject based on the ideXlab platform.
-
optimal bidding strategy for a der aggregator in the day ahead market in the presence of Demand Flexibility
IEEE Transactions on Industrial Electronics, 2019Co-Authors: Marialaura Di Somma, Giorgio Graditi, Pierluigi SianoAbstract:The penetration of distributed energy resources (DER), including distributed generators, storage devices, and Demand response (DR) is growing worldwide, encouraged by environmental policies and decreasing costs. To enable DER local integration, new energy players as aggregators appeared in the electricity markets. This player, acting toward the grid as one entity, can offer new services to the electricity market and the system operator by aggregating flexible DER involving both DR and generation resources. In this paper, an optimization model is provided for participation of a DER aggregator in the day-ahead market in the presence of Demand Flexibility. This player behaves as an energy aggregator, which manages energy and financial interactions between the market and DER organized in local energy systems (LES), which are in charge to satisfy the multienergy Demand of a set of building clusters with flexible Demand. A stochastic mixed-integer linear programming problem is formulated by considering uncertainties of intermittent DER facilities and day-ahead market price, to find the optimal bidding strategies while maximizing the expected aggregator's profit. Numerical results show that the method is efficient in finding the bidding curves in the day-ahead market through the optimal management of Flexibility requests sent to clusters, as well as of DER in LES and interactions among LES.
-
a framework for incorporating Demand response of smart buildings into the integrated heat and electricity energy system
IEEE Transactions on Industrial Electronics, 2019Co-Authors: Changzheng Shao, Pierluigi Siano, Yi Ding, Zhenzhi LinAbstract:The electricity output of combined heat and power (CHP) units is constrained by their heat output corresponding to customers’ heat Demand, which makes it difficult for the CHP units to frequently adjust their electricity output. Therefore, additional balancing power is required to integrate the variable wind power in the CHP-based heat and electricity integrated energy system (HE-IES). This paper expands the Demand response (DR) concept to the HE-IES. A comprehensive DR strategy combining energy substitution and load shifting is first developed to exploit the Demand Flexibility of smart buildings. Besides electric balancing power, heat balancing power is also provided to relax the production constrains of CHP units. Moreover, a real-time DR exchange (DRX) market is developed where the building aggregators are stimulated to adjust buildings’ energy consumption behaviors and provide the required balancing power. Compared with the existing day-ahead DRX market, the real-time DRX market can balance the very short-term wind power fluctuation and reduce price spikes. Additionally, a novel optimum feasible region method is proposed to achieve the fast clearing of the DRX market to meet the higher requirement for clearing speed in the real-time market. Simulation results verify the advantages of the proposed technique.