Demand Response Capability Research Articles

Design and Implementation of a Smart Meter with Demand Response Capabilities

Abstract This paper presents the design of a smart meter (SM) with demand response (DR) capabilities. The SM design is tested in a simulation that implements an advanced measurement infrastructure (AMI), which allows a bidirectional communication between the household smart meters and the distribution management system (DMS). The DMS deploys an energy management system (EMS) that runs a simple demand response program (DRP) based on time of use (TOU), consisting in peak and off-peak rates. Results from the simulation and the data collected from the SM show significant improvements in energy consumption during peak hours thanks to the load curtailment strategies.

Experimental Study of Grid Frequency Regulation Ancillary Service of a Variable Speed Heat Pump

This paper describes an analysis of a variable speed heat pump (VSHP), which responds to direct load control (DLC) signals to provide grid frequency regulation (GFR) ancillary service, while ensuring the comfort of building occupants. A data-driven dynamic model of the VSHP is developed through real-time experimental studies with a time horizon ranging from seconds to hours. The model is simple, yet still sufficiently comprehensive to analyze the operational characteristics of the VSHP. The DLC scheme is then experimentally applied to the VSHP to evaluate its demand response (DR) capability. Two control methods are considered for a practical implementation of the DLC-enabled VSHP and a further improvement of the DR capability, respectively. Additionally, a small-signal analysis is carried out using the aggregated dynamic response of a number of DLC-enabled VSHPs to analyze their contribution to GFR in an isolated power grid. For experimental case studies, a laboratory-scale microgrid is then implemented with generator and load emulators. We show that the DLC-enabled VSHP can effectively reduce grid frequency deviations and required reserve capacities of generators.

Prosumers’ optimal DER investments and DR usage for thermal and electrical loads in isolated microgrids

Recently, driven by the increasing concern regarding electricity supply resiliency, literature has paid attention to microgrids (MGs) and their technical performance to ensure a reliable supply, although few papers have addressed the economic behavior of isolated MGs. Recent European projects have launched the proposal of a local market based approach to operate the isolated MG. One of the main concerns of such an approach is whether the small size of such markets may lead to strategic behaviors, although it depends on the number and size of local market agents. This paper presents a mathematical modeling, formulated as a mix complementarity problem (MCP), of the economic planning and operation of isolated MGs, able to represent the impact of agent's strategic behavior through the explicit consideration of conjectures. Although identifying the value of such conjectures for each particular MG is out of scope of this paper, a case study is conducted to analyze the impact on investments and local prices. Besides, it includes a temperature model for buildings, able to consider its thermal inertia and allowing prosumers to take advantage of its demand response (DR) capabilities regarding its thermal and electricity needs. The paper conducts different case studies to illustrate its impact.

Control and Communication Protocols Based on Packetized Direct Load Control in Smart Building Microgrids

Recent communication, computation, and technology advances coupled with climate change concerns have transformed the near future prospects of electricity transmission, and, more notably, distribution systems and microgrids. Distributed resources (wind and solar generation, combined heat and power) and flexible loads (storage, computing, EV, HVAC) make it imperative to increase investment and improve operational efficiency. Commercial and residential buildings, being the largest energy consumption group among flexible loads in microgrids, have the largest potential and flexibility to provide demand-side management. Recent advances in networked systems and the anticipated breakthroughs of the Internet of Things will enable significant advances in demand-response capabilities of intelligent load networks of power-consuming devices such as HVAC components, water heaters, EV charging stations, and many more. In this paper, a new operating framework, called packetized direct load control (PDLC), is proposed based on the notion of quantization of energy demand. This control protocol is built on top of two communication protocols that carry either complete or binary information regarding the operation status of appliances. We discuss the optimal demand-side operation for both protocols and analytically derive the performance differences between the protocols. We propose an optimal reservation strategy for traditional and renewable energy for the PDLC in both day-ahead and real-time markets. At the end of the paper, we discuss the fundamental tradeoff between achieving controllability and endowing consumer choice and flexibility.

Study on the promotion impact of demand response on distributed PV penetration by using non-cooperative game theoretical analysis

Promoting the penetration of distributed photovoltaic systems (PV) at the end-user side is an important and urgent task. This study aims to evaluate the promotion impact of the response capability of smart home consumers on the distributed PV penetration using non-cooperative game theoretical analysis. In the analysis, the Nash equilibrium can be found for consumers with different levels of demand response capability in an electricity market with real-time pricing (RTP) mechanism under different PV installed capacities and battery capacities. As a case study, 5 levels of consumers’ response capability, 32 combinations of PV installed capacities and battery capacities were analyzed and inter-compared using the developed model. The results show that: (i) the consumers with higher response capability are able to accept larger PV capacity because the marginal revenue of new installed PV for smart consumers decreases much more slowly compared to that of a common consumer; (ii) the consumers with higher response capability need less batteries to promote PV economic acceptability; (iii) the consumers with higher response capability can meet the electricity demand in real-time with least expenditure, so they get more ultimate benefit from the games.

Methods for Adding Demand Response Capability to a Thermostatically Controlled Load with an Existing On-off Controller

A thermostatically controlled load (TCL) can be one of the most appropriate resources for demand response (DR) in a smart grid environment. DR capability can be effectively implemented in a TCL with various intelligent control methods. However, because traditional on-off control is still a commonly used method in a TCL, it is useful to develop a method for adding DR capability to the TCL with an existing on-off controller. As a specific realization of supervisory control for implementing DR capability in the TCL, two methods are proposed - a method involving the changing of a set point and a method involving the paralleling of an identified system without delay. The proposed methods are analyzed through the simulations with an electric heater for different power consumption levels in the on-state. Considerable cost benefit can be achieved with the proposed methods when compared with the case without DR. In addition, the observations suggest that a medium power consumption level, instead of the maximum power, in the on-state should be used for consistently obtaining the cost benefit without severe temperature deviation from the specified temperature range for DR.

Modeling Demand Response Capability by Internet Data Centers Processing Batch Computing Jobs

Electricity cost has become a big concern of commercial cloud service providers with the rapid expansion of network-based cloud computing. Locationally, dispersed large-scale Internet data centers (IDCs) that underpin the cloud have increasing impact on the regional electricity market with their skyrocketing energy consumption. In this paper, the electricity market participation and accordingly the demand response capability of an IDC is defined as its temporally and spatially shiftable electricity demand quantities for processing delay-tolerant central processing unit-intense batch computing jobs. The demand response capability of the IDC is obtained by the proposed electric demand management solution. Price-sensitive and cooling efficiency-enabled batch computing workload dispatch with the objective of minimizing electricity cost is realized by dynamic IDC server consolidation and scheduling with virtual machine live migration technology. Numerical simulations show the effectiveness of the proposed demand management solution in IDC energy consumption and electricity cost reduction.

A market-oriented hierarchical framework for residential demand response

The integration of a great deal of uncertain renewable sources in future grids will require more operational flexibility. Demand response (DR) can provide the load shaping potentials thereby assuaging the need for operational flexibility. To this end, this paper intends to develop a framework focusing on realization of domestic storage space heating DR capability in balancing market. The developed framework consists of two hierarchical stages named energy market stage and balancing power market stage. The first stage deals with customers’ day-ahead decisions in energy market. In this stage, the system operator releases day-ahead energy prices in response to which customers optimize their electricity usage to minimize their energy expenses. The second stage optimizes customers’ intra hour load scheduling decisions in balancing power market. In the second stage, up/down power regulation incentives are offered to customers who, in the hope of achieving monetary gains, modify their promised day-ahead decisions. Performance of the framework is verified through simulations on Finnish case studies. According to the obtained results, the framework allows the customers to make savings in energy expenses as well as the system operator to benefit from DR.

Electric Demand Response Management for Distributed Large-Scale Internet Data Centers

This paper evaluates the electric demand response (DR) management for distributed large-scale Internet data centers (IDCs) via the stochastic optimization approach. The electric DR of IDCs refers to the capability of optimally shifting cloud service tasks among distributed IDCs. Thus, the energy consumption reduction at certain IDC locations could be considered as the DR provision capacity in day-ahead DR programs. Cloud service tasks of IDCs include processing, storage, and computing tasks, which are further categorized into interruptible and non-interruptible tasks. The proposed model determines the optimal hourly DR capabilities of individual IDCs while considering uncertain coming cloud service tasks to individual IDCs. The major contribution of this paper is to rigorously formulate the DR capability of IDCs as changes in the electricity consumption when shifting cloud service tasks among distributed IDCs in different time zones, while considering the energy consumption for providing IT service, cooling, shifting cloud service tasks, environmental impacts, and uncertain coming tasks. The proposed model would enhance the financial situation and improve the environmental impacts of distributed IDCs by participating in day-ahead DR programs. The stochastic optimization adopts scenario-based approach via the Monte Carlo (MC) simulation for minimizing the total electricity cost, which is the expected electricity payment minus the revenue from the DR provision. The proposed model is formulated as a mixed-integer linear programming (MILP) problem and solved by state-of-the-art MILP solvers. Numerical results show the effectiveness of the proposed approach for solving the optimal electric DR management problem for distributed large-scale IDCs.

Demand Response of Thermostatic Loads by Optimized Switching-Fraction Broadcast

Demand response is an important Smart Grid concept that aims at facilitating the integration of volatile energy resources into the electricity grid. This paper considers the problem of managing large populations of thermostat-based devices with on/off operation. The objective is to enable demand response capabilities within the intrinsic flexibility of the population. A temperature distribution model based on Fokker-Planck partial differential equations is used to capture the behavior of the population. To ensure probability conservation and high accuracy of the numerical solution, Finite Volume Method is used to spatially discretize these equations. Next, a broadcast strategy with two switching-fraction signals is proposed for actuating the population. This is applied in an open-loop scenario for tracking a power reference by running an optimization with a multilinear objective.

Cutting Campus Energy Costs with Hierarchical Control: The Economical and Reliable Operation of a Microgrid

in this article, we discuss microgrid objectives and present options for microgrid operations and their monitoring and control in the context of a functional system at the illinois institute of technology (iit) in Chicago. the microgrid represents a multitier hierarchical control of self-sustaining energy infrastructure with islanding and resynchronization, self-healing, and demand response capabilities. the intelligent high-reliability distribution system (HRDS) at iit is equipped with phasor measurement units (PMUs) for real-time monitoring, nondispatchable renewable energy production, as well as conventional and dispatchable energy resources.

Markov model based assessment for redundancy mitigation in high voltage grids using demand response

Demand response (DR) has become a key feature of the future Smart Grid. This paper assesses the potential of DR in mitigating the redundancy requirement of a high voltage (sub-transmission) grid. DR is considered as a redundancy alternative, activated by network contingencies. The end use appliance consumption pattern along with the load disaggregation technique is applied to determine the achievable DR. The comparison of outage cost for future load is adopted as an assessment method; this comparison is between non-investing in the network, and use of DR as a redundancy alternative. In the presence of DR, novel reliability models are developed in order to find the outage cost. The analysis conducted on a typical Finnish sub-transmission network indicates that the redundant capacity of the network proportional to DR capability can be mitigated. The employment of released redundant capacity for the increasing load will escalate network efficiency. As a consequence investments will be avoided

Microgrids for Fun and Profit: The Economics of Installation Investments and Operations

A vision shared by many experts is that future communities (residential and commercial developments, university and industrial campuses, military installations, and so on) will be self-sufficient with respect to energy production and will adopt microgrids. With power generation capacities of 10-50 MW, microgrids are usually intended for the local production of power with islanding capabilities and have capacity available for sale back to macrogrids. A typical microgrid portfolio includes photovoltaic (PV) and wind resources, gas-fired generation, demand-response capabilities, electrical and thermal storage, combined heat and power (CHP), and connectivity to the grid. Advanced technologies such as fuel cells may also be included. This article describes the problems encountered in analyzing prospective microgrid economics and environmental and reliability performance and presents some results from the software tools developed for these tasks.

Decisions on Energy Demand Response Option Contracts in Smart Grids Based on Activity-Based Costing and Stochastic Programming

Smart grids enable a two-way energy demand response capability through which a utility company offers its industrial customers various call options for energy load curtailment. If a customer has the capability to accurately determine whether to accept an offer or not, then in the case of accepting an offer, the customer can earn both an option premium to participate, and a strike price for load curtailments if requested. However, today most manufacturing companies lack the capability to make the correct contract decisions for given offers. This paper proposes a novel decision model based on activity-based costing (ABC) and stochastic programming, developed to accurately evaluate the impact of load curtailments and determine as to whether or not to accept an energy load curtailment offer. The proposed model specifically targets state-transition flexible and Quality-of-Service (QoS) flexible energy use activities to reduce the peak energy demand rate. An illustrative example with the proposed decision model under a call-option based energy demand response scenario is presented. As shown from the example results, the proposed decision model can be used with emerging smart grid opportunities to provide a competitive advantage to the manufacturing industry.

Energy security and renewable electricity trade—Will Desertec make Europe vulnerable to the “energy weapon”?

Solar power imports to Europe from the deserts of North Africa, as foreseen in the Desertec concept, is one possible way to help decarbonising the European power sector by 2050. However, this approach raises questions of threats to European energy security in such an import scenario, particularly in the light of increasing import dependency and Russia's use of the “energy weapon” in recent years. In this paper we investigate the threat of North African countries using the Desertec electricity exports as an “energy weapon”. We develop and use a new model to assess the interdependence – the bargaining power symmetry, operationalised as costs – of a disruption in a future renewable electricity trade between North Africa and Europe. If Europe maintains current capacity buffers, some demand-response capability and does not import much more than what is described in the Desertec scenario, it is susceptible to extortion and political pressure only if all five exporter countries unite in using the energy weapon. Europe is not vulnerable to extortion by an export cut from only one country, as the European capacity buffers are sufficient to restore the power supply: no single exporter country would have sustained bargaining power over Europe.

Purchase-Bidding Strategies of an Energy Coalition With Demand-Response Capabilities

The implementation of demand-response programs (DRP) has gained interest as a means to alleviate energy consumption during peak-hours. Two explanations account for the success of such programs which involve both utilities and electricity consumers, with the latter often organized into coalitions: the system operator meets its goal of reducing the load peak; simultaneously, electricity consumers achieve economic benefits when reducing consumption during peak hours. In this paper, a Monte Carlo-based algorithm has been proposed for the formulation of multiple purchase offers in the day-ahead energy market (DAEM) by coalitions in which consumers vary in their sensitivity to DRP, manifesting different responsiveness to hourly tariffs based on the hourly market clearing prices. Being able to monitor how coalition members use air-conditioning in the presence of variable hourly energy tariffs, the coordinator can then define a purchase-bidding strategy, depending on how price-sensitive the coalition is. Simulation results show that the presence of a price-sensitive demand leads not only to a subsequent reduction in energy prices during peak-hours but also leads to a decrease in their inter-hour volatility.