Development Of Demand Response Research Articles

Integrated Risk Analysis of Aggregators: Policy Implications for the Development of the Competitive Aggregator Industry

One of the important goals of the EU is to ensure a secure, sustainable, and competitive energy system that is less dependent on external energy supply. Greater independence is planned to be achieved by diversifying energy sources, as well as investing in renewables and energy efficiency. One of the mechanisms is the demand response (DR) that provides a high level of energy independence for the consumer. In this paper, we explore perspectives of the development of DR with a mediating effect of the independent aggregators from an EU member state standpoint. We use a hybrid research methodology that combines instruments of strategic analysis, i.e., PESTLE framework and SWOT analysis, along with the integrated risk management framework in order to identify, evaluate and rank prominent risks to which this initiative is exposed. Interdependencies between the identified risk factors are also included and efficient mitigation measures are proposed. The findings of this exploratory research are aimed at developing the policies and strategies for the aggregators’ development in the medium term. The most emphasized risks detected in analysis are the investment risk, the legal risk, the risk of substitute technologies, the consumer behavior risk, the risk of opportunistic behavior and the risk of entry barriers.

Electricity ancillary service market model considering demand response of multi-energy load aggregators

Large-scale access of distributed generations, the increasing interconnection of large DC power grids and the demand fluctuation of loads caused by climate change put forward higher requirements for power system stability. The flexible resources on the demand side can respond quickly to meet the needs of power balance of the system. Under the background of the interconnection of multi-energy networks, multi-energy loads (MELs) have become excellent demand response (DR) resources. Firstly, MEL models are established in this paper, including the models for replaceable load, reducible load, transferable load and translational load. Moreover, considering that DR needs to be supported by the ancillary service market, an ancillary service market clearing model with DR provided by MEL aggregators is proposed. Finally, this paper summarizes and prospects the future development of DR with MEL.

Power system transition in China under the coordinated development of power sources, network, demand response, and energy storage

AbstractChina is transiting its power system towards a more flexible status with a higher capability of integrating renewable energy generation. Demand response (DR) and energy storage increasingly play important roles to improve power system flexibility. The coordinated development of power sources, network, DR, and energy storage will become a trend. This paper examines the significance of source‐network‐demand‐storage coordinated development. Furthermore, an outlook of the power system transition in China is provided by virtue of source‐network‐demand‐storage coordinated planning. The paper also assesses the integration of multiple urban infrastructures in China and its impacts on source‐network‐demand‐storage coordination. Lastly, challenges for achieving the source‐network‐demand‐storage coordination and suggested measures are discussed.This article is categorized under: Energy Research & Innovation > Systems and Infrastructure Energy and Urban Design > Systems and Infrastructure

Practices and Enlightenment of Domestic and Foreign Demand Response in Electricity Market

With the increasing proportion of intermittent power supplies and large capacity generator set, demand response based on excitation and price is widely concerned for improving the flexibility of system operation scheduling. The development of demand response in the electricity market is in the ascendant in the world, and the market mechanism can be better designed by fully drawing on existing experience. This paper comprehensively analyses the released relevant policies, technical standards and implementation of existing pilot projects of domestic and foreign demand response in electricity market, summarizing the research focus in recent years, learning the experience of the existing demand response project and combining the current situation of the power market revolution, then put forward some suggestions to develop the mechanism of demand response in electricity market.

A Hybrid Optimization Approach for Residential Energy Management

In the past few years, the development of demand response (DR) programs for smart grid systems has provided residential customers with a real opportunity to participate in DR-driven projects. One typical DR-related application now available is automated energy scheduling for residential building, which can be used to help reduce energy costs. Residential energy scheduling focuses on saving cost by managing the operation time and energy consumption level of different appliances. Demand Response programs present as NP-hard problems, the equations are non-convex mixed integer non-linear problems (MINLP), for which it is difficult to obtain an optimal solution. In relation to residential DR, we propose a hybrid approach here that is able to solve an MINLP. The problem is decomposed into discrete and continuous variables. The discrete variables are optimized by using a particle swarm optimization (PSO) algorithm, whilst the continuous variables are determined by using a gradient-based deterministic algorithm. The superiority of the proposed algorithm was demonstrated by compared with commercial optimization software and heuristic based algorithm. Furthermore, the effectiveness of the proposed method in residential DR was tested and the results were presented.

Clustering Load Profiles for Demand Response Applications

With the development of smart grid technologies, residential and commercial loads have large potentialities to participate in demand response (DR) programs. This makes the data dimension reduction techniques and classification processing critical for the success of DR development. A novel load profile clustering method is proposed for load data classification which is based on the information entropy, piecewise aggregate approximation, and spectral clustering (SC). The variable temporal resolution technique is presented to model typical daily load datasets, and then an improved SC based on multi-scale similarities of distance and shape characteristics is proposed for clustering to obtain reasonable load classification. A case study with one hundred of commercial heating, ventilation, and air conditioning data analysis illustrates the approach. The results prove that the proposed method is feasible in terms of data dimension reduction, reasonable profile selection and classification, and the operation stability.

Demand-Side Flexibility for Energy Transitions: Ensuring the Competitive Development of Demand Response Options

This report provides an overview of the current debates about demand response development, focusing primarily on Europe, with some comparisons to the United States. ‘Demand response’ includes strategies that involve end-use customers adapting or altering their electricity demand in response to grid conditions or market prices. It is viewed as a multi-purpose power-system resource that enhances the energy system’s capacity to cope with increasing demand, rising costs of conventional transmission and distribution grids, and increasing share of intermittent renewable energy. The report reviews risks, opportunities, potential, consumer engagement market design, and policy and regulation.

Strategic CBDR bidding considering FTR and wind power

The independent system operators (ISOs) usually offer financial transmission right (FTR) as a financial instrument for electricity market participants to hedge against the transmission congestion cost. Meanwhile, the development of demand response (DR) provides load serving entities (LSEs) opportunities to perform coupon based demand response (CBDR) programs, and thus LSEs can behave as strategic bidders in the whole-sale market by adjusting its demand level. In the existing approaches for modelling CBDR, the potential impact of FTR which leads LSEs to obtain the congestion compensation under a high load level is overlooked. Therefore, this study proposes a comprehensive strategic CBDR model in which the LSE's profit is maximised by providing CBDR to customers and the congestion compensation from the LSE bidder's FTR holding is also considered. The proposed model is formulated as a bi-level optimisation problem with the LSE's net revenue maximisation as the upper level and the ISO's economic dispatch considering wind power uncertainty as the lower level problem. The bi-level model is addressed with mathematic program with equilibrium constraints technique and mixed-integer linear programming, which can be solved using available optimisation software tools. In addition, the case studies of an illustrative two bus system, the PJM 5-bus system, and IEEE 39-bus system verify the proposed method.

Time-based pricing and electricity demand response: Existing barriers and next steps

Interest in Demand Response (DR) is increasing due to its potential to improve reliability and save costs for electricity systems. DR can provide a sustainable and cost-effective option for supply balancing, especially in a scenario with more volatile inflows from renewable energy sources. End-users can be incentivized to provide DR through time-based pricing in general and dynamic pricing in particular. This paper provides a theoretic framework and practice-oriented review of the status of DR in Europe, outlining the major challenges currently hampering further DR development. Important challenges involve the split-incentive issue for investments in enabling technologies, traditional market rules for flexibility that favor large generation units and the need for electricity market and network operation coordination.

Assessing long-term effects of demand response policies in wholesale electricity markets

Different policies have been implemented around the world seeking to deliver demand response potential in the electricity markets. Externalities, namely the CO2 externality, have been one of the key concerns in the debate on the effectiveness of different policies regarding demand response development. Although most previous researches have centred on the short-term assessment of different policy choices to tackle the CO2 externality, little work has been focused on the long-term impacts, such as changes in welfare and investment dynamics, in consequence of the implementation of such policies. This paper relies on a long-term market simulation model to examine long-term dynamics of two specific policies presently used by policy makers. The first policy relates to the correction for the externality by setting a CO2 price at a level equal to the social cost of the associated CO2 emissions. The second policy consists in subsidizing carbon-free technologies such as demand response. We test for each policy two different scenarios regarding the possibility of internalization of the CO2 externality. The results show that in the long-run different policies should affect both investments and social costs, a market-driven development of demand response with the internalization of the CO2 externality being the most efficient approach.

Research on Information Interactive Model of Automated Demand Response

This paper analyzed the difficulties when applying and promoting automatic demand response in a wide range under the current development status. Based on the demand of users, a system model and the information model of demand response program were designed. Then, an information interactive model which is suitable for the development of demand response in China was proposed.

Design of Demand Response System Based on OpenADR

The double pressures of resources and environment have brought the global power industry into the era of Smart Grid. In order to better promote the development of Demand Response of Smart Grid and to offer new regulation resources for the safe and stable operation of electric power system, OpenADR, the Open Automated Demand Response Communications Specification, has been discussed in detail, which aims at the problems of energy efficiency and the contradiction between power supply and demand. And a design scheme of Auto-DR system which introduces in detail the system architecture and the communications architecture based on OpenADR was proposed to realize the two-way communications between Utilities and end-users, and the problems such as the peak, the gap between supply and demand and the electricity structure management would be consequently solved. This scheme has a certain reference value to the Demand Side Management under the framework of Smart Grid.

The carbon abatement potential of high penetration intermittent renewables

The carbon abatement potentials of wind turbines, photovoltaics, and concentrating solar power plants were investigated using dispatch simulations over California with 2005–06 meteorological and load data. A parameterization of the simulation results is presented that provides approximations of both low-penetration carbon abatement rates and maximum carbon abatement potentials based on the temporal characteristics of the resource and the load. The results suggest that shallow carbon emissions reductions (up to 20% of the base case) can be achieved most efficiently with geothermal power and demand reductions via energy efficiency or conservation. Deep emissions reductions (up to 89% for this closed system), however, may require the build-out of very large fleets of intermittent renewables and improved power system flexibility, communications, and controls. At very high penetrations, combining wind and solar power improved renewable portfolio performance over individual build-out scenarios by reducing curtailment, suggesting that further reductions may be met by importing uncorrelated out-of-state renewable power. The results also suggest that 90–100% carbon emission reductions will rely on the development of demand response and energy storage facilities with power capacities of at least 65% of peak demand and energy capacities large enough to accommodate seasonal energy storage.