The power grid has become a critical infrastructure,
which modern society cannot do without. It has always been a
challenge to keep power supply and demand in balance; the more
so with the recent rise of intermittent renewable energy sources.
Demand response schemes are one of the counter measures,
traditionally employed with large industrial plants. This paper
suggests to consider data centres as candidates for demand
response as they are large energy consumers and as they are
able to adapt their power profile sufficiently well. To unlock
this potential, we suggest a system of contracts that regulate
collaboration and economic incentives between the data centre
and its energy supplier (GreenSDA) as well as between the
data centre and its customers (GreenSLA). Several presented use
cases serve to validate the suitability of data centers for demand
The penetration of dc networks for different applications in power systems is increasing. This paper presents a novel methodology for security-constrained optimal power flow (SCOPF) operation of a power system, such as a smart grid or a supergrid, with an embedded dc network. The methodology demonstrates that dc networks can be operated to provide support to ac systems, increasing its security of supply and resilience in case of outages, while reducing operational costs. Moreover, the outage management support can be achieved via a preventive SCOPF – i.e. the combined network stays N-1 secure after outages without need for further control action – or via a corrective SCOPF, by using the fast controls of the ac-dc converters to react to the contingencies. The methodology relies on the construction of a binary outage matrix and optimizes only the control variables of the ac and dc networks. It was successfully tested in system with 12 buses and in the IEEE30 network with 35 buses. Operational savings of up to 1% and 0.52% were obtained for the first and second networks, respectively, while network violations for the N-1 contingency scenarios were completely eliminated in the first and reduced by 70% in the former.
Kampouropoulos, K.; Andrade, F.; Sala, E.; Garcia, A.; Romeral, L. IEEE Transactions on Smart Grid Vol. PP, num. 99, p. 1-9 DOI: 10.1109/TSG.2016.2609740 Data de publicació: 2016-09-14 Article en revista
This paper presents a novel method for the energy optimization of multi-carrier energy systems. The presented method combines an adaptive neuro-fuzzy inference system, to model and forecast the power demand of a plant, and a genetic algorithm to optimize its energy flow taking into account the dynamics of the system and the equipment’s thermal inertias. The objective of the optimization algorithm is to satisfy the total power demand of the plant and to minimize a set of optimization criteria, formulated as energy usage, monetary cost and environmental cost. The presented method has been validated under real conditions in the car manufacturing plant of SEAT in Spain in the framework of an FP7 European research project.
A key challenge for inverted-based microgrids working in islanded mode is to maintain their own frequency and voltage to a certain reference values while regulating the active and reactive power among distributed generators and loads. The implementation of frequency and voltage restoration control policies often requires the use of a digital communication network for real-time data exchange (tertiary control covers the coordi- nated operation of the microgrid and the host grid). Whenever a digital network is placed within the loop, the operation of the secondary control may be affected by the inherent properties of the communication technology. This paper analyses the effect that properties like transmission intervals and message dropouts have for four existing representative approaches to secondary control in a scalable islanded microgrid. The simulated results reveals pros and cons for each approach, and identifies threats that properly avoided or handled in advance can prevent failures that otherwise would occur. Selected experimental results on a low- scale laboratory microgrid corroborate the conclusions extracted from the simulation study.
This paper presents the design of a low complexity Fuzzy Logic Controller of only 25-rules to be embedded in an Energy Management System for a residential grid-connected microgrid including Renewable Energy Sources and storage capability. The system assumes that neither the renewable generation nor the load demand is controllable. The main goal of the design is to minimize the grid power profile fluctuations while keeping the Battery State of Charge within secure limits. Instead of using forecasting-based methods, the proposed approach uses both the microgrid energy rate-of-change and the battery SOC to increase, decrease or maintain the power delivered/absorbed by the mains. The controller design parameters (membership functions and rule-base) are adjusted to optimize a pre-defined set of quality criteria of the microgrid behavior. A comparison with other proposals seeking the same goal is presented at simulation level, whereas the features of the proposed design are experimentally tested on a real residential microgrid implemented at the Public University of Navarre.
Gavriluta, C.; Candela, J.; Luna, A.; Gomez-Exposito, A.; Rodriguez, P. IEEE Transactions on Smart Grid Vol. 6, num. 3, p. 1502-1510 DOI: 10.1109/TSG.2014.2365854 Data de publicació: 2015-05-01 Article en revista
This paper proposes a hierarchical control architecture designed for an arbitrary high voltage multiterminal dc (MTDC) network. In the proposed architecture, the primary control of the MTDC system is decentralized and implemented using a generalized droop strategy. Design criteria for dimensioning the primary control parameters, including voltage limits, are offered by analyzing the transients appearing in the system. The proposed secondary control is centralized and regulates the operating point (OP) of the network so that optimal power flow (OPF) is achieved. Compared to previous works, this paper further elaborates, both analytically and through simulations, on the coordination between the primary and secondary control layers. This includes how local primary controllers have to be driven by the centralized controller in order to ensure a smooth transition to the optimal OP.
An optimization model is proposed to manage a
residential microgrid including a charging spot with a vehicle-togrid
system and renewable energy sources. In order to achieve a
realistic and convenient management, we take into account: (1)
the household load split into three different profiles depending
on the characteristics of the elements considered; (2) a realistic
approach to owner behavior by introducing the novel concept of
range anxiety; (3) the vehicle battery management considering
the mobility profile of the owner and (4) different domestic
renewable energy sources. We consider the microgrid operated
in grid-connected mode. The model is executed one-day-ahead
and generates a schedule for all components of the microgrid.
The results obtained show daily costs in the range of 2.82eto
3.33e; the proximity of these values to the actual energy costs
for Spanish households validate the modeling. The experimental
results of applying the designed managing strategies show daily
costs savings of nearly 10%.
Atzeni, I.; Garcia, L.; Scutari, G.; Palomar, D.P.; R. Fonollosa, Javier IEEE Transactions on Smart Grid Vol. 4, num. 2, p. 866-876 DOI: 10.1109/TSG.2012.2206060 Data de publicació: 2013-06 Article en revista
Demand-side management, together with the integration of distributed energy generation and storage, are considered increasingly essential elements for implementing the smart grid concept and balancing massive energy production from renewable sources. We focus on a smart grid in which the demand-side comprises traditional users as well as users owning some kind of distributed energy sources and/or energy storage devices. By means of a day-ahead optimization process regulated by an independent central unit, the latter users intend to reduce their monetary energy expense by producing or storing energy rather than just purchasing their energy needs from the grid. In this paper, we formulate the resulting grid optimization problem as a noncooperative game and analyze the existence of optimal strategies. Furthermore, we present a distributed algorithm to be run on the users' smart meters, which provides the optimal production and/or storage strategies, while preserving the privacy of the users and minimizing the required signaling with the central unit. Finally, the proposed day-ahead optimization is tested in a realistic situation.
Ruiz, A.; Colet Subirachs, A.; Alvarez, F.; Gomis-Bellmunt, O.; Sudria, A. IEEE Transactions on Smart Grid Vol. 3, num. 2, p. 858-865 DOI: 10.1109/TSG.2012.2187222 Data de publicació: 2012-06-01 Article en revista
Bartoli, A.; Hernández-Serrano, J.; Soriano, M.; Dohler, M.; Kountouris, A.; Barthel, D. IEEE Transactions on Smart Grid Vol. 21, num. 4, p. 844-864 DOI: 10.1109/TSG.2011.2162431 Data de publicació: 2011-12 Article en revista
Whilst security is generally perceived as an important constituent of communication systems, this paper offers a viable security-communication-tradeoff particularly tailored to Advanced Metering Infrastructures (AMIs) in Smart Grid systems. These systems, often composed of embedded nodes with highly constrained resources, require e.g. metering data to be delivered efficiently whilst neither jeopardizing communication nor security. Data aggregation is a natural choice in such settings, where the challenge is to facilitate per-hop as well as end-to-end security. The prime contribution of this paper is to propose a secure aggregation protocol that meets the requirements of Smart Grids, and to analyze its efficiency considering various system configurations as well as the impact of the wireless channel through packet error rates. Relying on analysis and corroborative simulations, unprecedented design guidelines are derived which determine the operational point beyond which aggregation is useful as well quantifying the superiority of our protocol w.r.t. non-aggregated solutions.