Deploying the ICT architecture of a residential demand response pilot

The Flemish project Linear was a large scale residential demand response pilot that aims to validate innovative smart grid technology building on the rollout of information and communication technologies in the power grid. For this pilot a scalable, reliable and interoperable ICT infrastructure was set up, interconnecting 240 residential power grid customers with the backend systems of energy service providers (ESPs), flexibility aggregators, distribution system operators (DSOs) and balancing responsible parties (BRPs). On top of this architecture several business cases were rolled out, which require the sharing of metering data and flexibility information, and demand response algorithms for the balancing of renewable energy and the mitigation of voltage and power issues in distribution grids. The goal of the pilot is the assessment of the technical and economical feasibility of residential demand response in real life, and of the interaction with the end-consumer. In this paper we focus on the practical experiences and lessons learnt during the deployment of the ICT technology for the pilot. This includes the real-time gathering of measurement data and real-time control of a wide range of smart appliances in the homes of the participants. We identified a number of critical issues that need to be addressed for a future full-scale roll-out: (i) reliable in-house communication, (ii) interoperability of appliances, measurement equipment, backend systems, and business cases, and (iii) sufficient backend processing power for real-time analysis and control

Computational Intelligence Applications in Smart Grids: Enabling Methodologies for Proactive and Self Organizing Power Systems

This book considers the emerging technologies and methodologies of the application of computational intelligence to smart grids. From a conceptual point of view, the smart grid is the convergence of information and operational technologies applied to the electric grid, allowing sustainable options to customers and improved levels of security. Smart grid technologies include advanced sensing systems, two-way high-speed communications, monitoring and enterprise analysis software, and related services used to obtain location-specific and real-time actionable data for the provision of enhanced services for both system operators (i.e. distribution automation, asset management, advanced metering infrastructure) and end-users (i.e. demand side management, demand response). In this context, a crucial issue is how to support the evolution of existing electrical grids from static hierarchal systems to self-organizing, highly scalable and pervasive networks. Modern trends are oriented toward the employment of computational intelligence techniques for deploying advanced control, protection and monitoring architectures that move away from the older centralized paradigm to systems distributed across the field with an increasing pervasion of intelligence devices. The large-scale deployment of computational intelligence technologies in smart grids could lead to a more efficient tasks distribution amongst energy resources and, consequently, to a sensible improvement of the electrical grid flexibility

Optimising Energy Flexibility of Boats in PV-BESS Based Marina Energy Systems

Implementation of alternative energy supply solutions requires the broad involvement of local communities. Hence, smart energy solutions are primarily investigated on a local scale, resulting in integrated community energy systems (ICESs). Within this framework, the distributed generation can be optimally utilised, matching it with the local load via storage and demand response techniques. In this study, the boat demand flexibility in the Ballen marina on Samsø—a medium-sized Danish island—is analysed for improving the local grid operation. For this purpose, suitable electricity tariffs for the marina and sailors are developed based on the conducted demand analysis. The optimal scheduling of boats and battery energy storage system (BESS) is proposed, utilising mixed-integer linear programming. The marina’s grid-flexible operation is studied for three representative weeks—peak tourist season, late summer, and late autumn period—with the combinations of high/low load and photovoltaic (PV) generation. Several benefits of boat demand response have been identified, including cost savings for both the marina and sailors, along with a substantial increase in load factor. Furthermore, the proposed algorithm increases battery utilisation during summer, improving the marina’s cost efficiency. The cooperation of boat flexibility and BESS leads to improved grid operation of the marina, with profits for both involved parties. In the future, the marina’s demand flexibility could become an essential element of the local energy system, considering the possible increase in renewable generation capacity—in the form of PV units, wind turbines or wave energy

Price-based and Incentive-based Framework of Demand Response in Portugal

Demand Response is a flexibility tool that can provide several benefits to the electric power system’s operation, namely by providing ancillary services. Although several countries have similar active consumer approaches, the truth is that these methodologies are not always clear or transparent to outsiders, and even sometimes to locals (difficult interpretation of legislation). In this way, the present paper explains Portuguese price-based and incentive-based demand response strategies, and proceed with an analysis and evaluation of the current stage of their implementation. Although the programs exist and are available, their actual use are still very limited.been supported by the European Commission H2020 MSCA-RISE -2014: Marie Skłodowska-Curie project DREAM GO Enabling Demand Response for short and real-time Efficient And Market Based Smart Grid Operation An intelligent and real time simulation approach ref 641794info:eu-repo/semantics/publishedVersio

Smart Grid Energy Flexible Buildings through the use of Heat Pumps in the Belgian context

The management of electricity grids requires the supply and demand of electricity to be in balance at any point in time. To this end, electricity suppliers have to nominate their electricity bids on the day-ahead electricity market such that the forecasted supply and demand are in balance. At the intraday-level, mismatches between the forecasted and actual supply and demand can be compensated for by reserve capacity or by real-time demand response. In this context, there are three ways to minimize the cost of electricity supply. A first one is to predict electricity demand profiles associated to local consumers equipped with smart metering devices as accurately as possible. A second one is to minimize the procurement costs of electricity by shifting flexible loads from peak to off-peak hours. This can be done by offering consumers time-of-use (ToU) variable electricity tariffs as an incentive to shift their demand. A third one is to minimize the imbalance costs resulting from mismatches between forecasted supply and demand, by real-time demand response. Smart control of HVAC equipment with embedded model predictive control (MPC) can be used in that context. They have to be provided with dynamic building simulation models. The first part of this study provides typologies of Smart Grid Energy ready Buildings within the context of the Belgian building stock. A typical new residential building is considered, equipped with an air-to-water heat pump that supplies either radiators or a floor heating system. Different occupancy profiles are considered as well as three heating control strategies guaranteeing equivalent thermal comfort. The flexibility is assessed according to a cost-weighted electricity consumption of the heat pump. The impact of building thermal mass storage on the electricity consumption is also evaluated. A ranking of the building characteristics affecting its flexibility is deduced as well as recommendations to avoid overconsumption associated to energy storage. The second part of this study assesses the flexibility potential of these Smart Grid Energy Ready Buildings within the context of the Belgian day-ahead electricity market. Flexibility will be quantified in terms of load volumes shifted and in terms of procurement costs avoided. The methodology implemented considers both the energy supplier and the end-user. On the electricity suppliers’ side, a ToU-price profile is determined based on an analysis of the day-ahead electricity prices in Belgium (Belpex power exchange, 2008-2012). On the consumers’ side, this ToU-profile serves as an input for the local heat pump controller. This controller uses MPC to determine the heat pump power profile for the next day such that thermal comfort is guaranteed at minimal energy cost. The study will be generalized to the intraday and real time markets in future work

Are building users prepared for energy flexible buildings—A large-scale survey in the Netherlands

Building energy flexibility might play a crucial role in demand side management for integrating intermittent renewables into smart grids. The potential of building energy flexibility depends not only on the physical characteristics of a building but also on occupant behaviour in the building. Building users will have to adopt smart technologies and to change their daily energy use behaviours or routines, if energy flexibility is to be achieved. The willingness of users to make changes will determine how much demand flexibility can be achieved in buildings and whether energy flexible buildings can be realized. This will have a considerable impact on the transition to smart grids. This study is thus to assess the perception of smart grids and energy flexible buildings by building users, and their readiness for them on a large scale. We attempted to identify the key characteristics of the ideal user of flexible buildings. A questionnaire was designed and administered as an online survey in the Netherlands. The questionnaire consisted of questions about the sociodemographic characteristics of the current users, house type, household composition, current energy use behaviour, willingness to use smart technologies, and willingness to change energy use behaviour. The survey was completed by 835 respondents, of which 785 (94%) were considered to have provided a genuine response. Our analysis showed that the concept of smart grids is an unfamiliar one, as more than 60% of the respondents had never heard of smart grids. However, unfamiliarity with smart grids increased with age, and half of the respondents aged 20–29 years old were aware of the concept. Monetary incentives were identified as the biggest motivating factor for adoption of smart grid technologies. It was also found that people would be most in favour of acquiring smart dishwashers (65% of the respondents) and refrigerator/freezers (60%). Statistical analysis shows that people who are willing to use smart technologies are also willing to change their behaviour, and can thus be categorised as potentially flexible building users. Given certain assumptions, 11% of the respondents were found to be potentially flexible building users. To encourage people to be prepared for energy flexible buildings, awareness of smart grids will have to be increased, and the adoption of smart technologies may have to be promoted by providing incentives such as financial rewards

A Consensus-based Distributed Temperature Priority Control of Air Conditioner Clusters for Voltage Regulation in Distribution Networks

High penetration of Photovoltaic (PV) to the distribution network may bring under-voltage and over-voltage issues, limiting the PV hosting capacity. Air conditioners (AC) in grid-interactive buildings can support voltage regulation by manipulating flexible energy consumption. This paper developed a novel voltage control strategy to regulate the AC clusters’ on/off states for distribution network voltage regulation under high PV penetrations. The novelty lies in the distributed formulation of temperature priority-based on/off control (TPC) of AC clusters and the strategic selection and permutation of demand response technologies, including the real-time optimal demand response resources dispatch, distributed sensing of ACs based on average consensus algorithm, and the local implementation of TPC strategy and trial calculation scheme for flexibility capacity estimation. Finally, the distributed TPC is validated to be effective for system rebalancing with no comfort violations and an acceptable ON/OFF switching frequency. The theoretical and numerical analysis also proves its scalability and robustness to communication delays and link failures. It is then incorporated into a novel hierarchical control framework for smart grid voltage control in a four-bus three-phase test grid, considering the voltage sensitivities to power injections in different locations and phases

A Distributed Demand-Side Management Framework for the Smart Grid

This paper proposes a fully distributed Demand-Side Management system for Smart Grid infrastructures, especially tailored to reduce the peak demand of residential users. In particular, we use a dynamic pricing strategy, where energy tariffs are function of the overall power demand of customers. We consider two practical cases: (1) a fully distributed approach, where each appliance decides autonomously its own scheduling, and (2) a hybrid approach, where each user must schedule all his appliances. We analyze numerically these two approaches, showing that they are characterized practically by the same performance level in all the considered grid scenarios. We model the proposed system using a non-cooperative game theoretical approach, and demonstrate that our game is a generalized ordinal potential one under general conditions. Furthermore, we propose a simple yet effective best response strategy that is proved to converge in a few steps to a pure Nash Equilibrium, thus demonstrating the robustness of the power scheduling plan obtained without any central coordination of the operator or the customers. Numerical results, obtained using real load profiles and appliance models, show that the system-wide peak absorption achieved in a completely distributed fashion can be reduced up to 55%, thus decreasing the capital expenditure (CAPEX) necessary to meet the growing energy demand