Demand-side Programs Research Articles

Behavior-aware assessment of demand response participation in power systems using causal artificial intelligence

Demand response (DR) is pivotal in enhancing the operational efficiency and reliability of power systems. Understanding prosumers’ behavior and their participation in DR programs is essential for utilities to design effective DR programs. Typically, prosumers are not concurrently exposed to multiple electricity price plans or engaged in distinct DR programs, which make the available data limited and introduces complexity in assessing their DR participation. Causal artificial intelligence offers a solution by enabling causal intervention and counterfactual analysis, facilitating the estimation of prosumers’ responses to demand-side programs without the necessity of experimental and control groups. This paper introduces a framework that integrates causal learning approaches for causal intervention and counterfactual analyses of prosumers’ DR participation and consumption behavior. The proposed framework incorporates domain knowledge of the power system to enhance model accuracy and performance. Simulation results demonstrate the effectiveness of the proposed framework with causal learning models in estimating prosumers’ DR participation and consumption behavior under different prices or DR programs. This capability allows utilities to gain a profound understanding of their prosumers, offering valuable insights for designing DR programs. Ultimately, this knowledge contributes to the reliable and efficient operation of power systems.

A Review on the Applications of PSO-Based Algorithm in Demand Side Management: Challenges and Opportunities

The increase in energy consumption, environmental pollution issues, and low-carbon agenda has grown the research area of demand side management (DSM). DSM programs provide feasible solutions and significantly enhance the efficiency and sustainability of electrical distribution systems. This paper classifies and discusses the broad definition of DSM based on the comprehensive literature study considering demand response and energy efficiency. The implementation of Artificial Intelligence algorithms in DSM applications has been employed in many studies to help researchers make optimal decisions and achieve predictions by analyzing the massive amount of historical data. Owing to its simplicity and consistent performance in fast convergence time, Particle Swarm Optimization (PSO) is widely used as a part of the swarm AI algorithm and has become a prominent technique in the optimization process to exploit the full benefit of the demand-side program. The variants of PSO have been developed to overcome the limitations of the original PSO and solve the high complexity and uncertainty in the DSM optimization process. The proposed PSO-based algorithm can optimize consumers’ consumption curves, reducing the peak demand and hence minimizing the electricity cost when integrated with the DR programs or EE measures. The research works of the PSO algorithm in DSM have seen an increasing trend in the past decade. Therefore, this paper reviewed the application of the PSO-based algorithm in DSM fields with some constraints and discussed the challenges from the previous work. The potential for new opportunities is identified so that PSO methods can be developed for future research.

Assessment of Canada's electricity system potential for variable renewable energy integration

Meeting commitments to the Paris Agreement will necessitate a transition in Canada's power system including increased generation from renewable sources. This study analyzes the Canadian electricity system in terms of its readiness to operationalize decarbonization strategies. More specially, this paper evaluates potential of Canada's electricity system in terms of the flexibility required to integrate variable renewable energies (VREs). To do so, the SILVER production cost model (PCM) is refined to improve its representation in terms of hydro resources, demand response programs and price-setting mechanism. Next, a network-constrained unit commitment (NCUC) of SILVER is built for each of Canada's ten provinces for a one-year period based on 2018 data. The results are used to assess the system flexibility and transmission network sufficiency as well as operational aspects including costs and emissions. The results indicate the SILVER's improved hydro modelling enhances the result of operation model by 4% on average. Also, the results demonstrate high flexibility of Canada's hydro-dominated network side along with free capacity in the transmission network can realize 54% VREs penetration rate on average for VREs curtailment less than 10%. In addition, implementation of demand side programs improves the VREs penetration rate by 2%–6% on average.

A Study on the Effects of Quality, Price, Environmental Value and Perceived Behaviour Control towards Intension to Accept Electricity Demand Side Programs; A case study of Qatar Kahramaa

A prevalent problematic issue spreading nowadays among the global community is the increasing demand of electricity, and Demand Side Management programs are suggested to be the best method for reducing the demand of electricity. Nevertheless, implementing such technologies is still an issue because the behavior of customers is different from one region to another, and the applicability of such technologies largely depends on the perceptions and the acceptance level of that specific region.

Short-term operation of microgrids with thermal and electrical loads under different uncertainties using information gap decision theory

The utilization of an Energy Management System (EMS) for the optimum scheduling of generation units, as well as demand side resources is essential due to the high penetration of Distributed Energy Resources (DERs) in microgrids (MGs), to achieve the desired objectives. As a result of the restructuring of the power systems and increasing the electricity prices during some periods in a day, demand side programs have been highly valuable by electricity customers. In this paper, a Demand Response (DR) model has been proposed to present the behavior of responsive controllable loads in response to the DR calls. Moreover, optimal scheduling of energy resources is developed for a typical MG by considering the presence of both electrical and thermal demands. Combined Heat and Power (CHP) units, boilers, wind turbines, storage devices, demand response resources (DRRs), as well as the power exchange possibility with the upstream wholesale market are the energy resources that have been considered as the portfolio of the decision maker. Furthermore, the uncertainty resources of the wind speeds and electrical load are handled by the Information Gap Decision Theory (IGDT) method. The performance of the proposed framework is comprehensively analyzed on the IEEE 33-bus test system. The advantage of the proposed methodology under the uncertainty conditions is analyzed by the Monte-Carlo simulation method when the different realization of the wind power and electrical load are considered.

Investment planning in energy efficiency programs: a portfolio based approach

The Portuguese energy efficiency programs are usually run through grant awards that support energy efficient technologies, which require the establishment of rational investment plans considering distinct budget level inputs to each program. The current evaluation of energy efficiency programs mainly relies on the economic analysis of demand-side programs and projects. One of the weaknesses of this type of approach is that it cannot capture the complexities of decision-making processes, mainly relying on the device costs targeted for funding. This paper aims at developing a methodological framework to support public authorities in investment planning for energy efficiency programs based on portfolio theory explicitly considering the energy spent in the manufacturing and installation of each energy efficient technology. The applicability of the methodology herein proposed is illustrated by considering the potential investment in distinct portfolios of industrial lighting systems. Finally, a new solution methodology for computing possibly efficient solutions is also suggested which allows exploring distinct types of investment strategies, according to the public investor’s preferences. Our findings suggest that LED lamps and T5 technologies should be considered as a valid option for replacing T8 and HPS technologies. Additionally, despite the investment cost involved in the installation of light control systems, they should be elected for funding. Finally, it is worth mentioning that the substitution of T8 and Halogen lamps with LED lamps has never been considered with the modelling framework used in spite of being effectively selected for public support, highlighting the need of adopting approaches that encompass a life-cycle perspective.

Demand Side Management: Optimal Demand Response in Distribution Networks With Several Energy Retail Companies

AbstractIn this work, a social welfare maximization problem is solved to determine the optimal scheduling of end-user controllable loads, smart appliances, and energy storage. The framework considers multiple retail energy suppliers as well as the AC power flow constraints of the distribution system. The demand side management program is focus on residential and commercial end-users. We have formulated a day-ahead residential bidding/buyback scheme modeled as an optimal power flow problem. This demand side program schedules end-user’s controllable loads or smart appliances and takes advantage of the flexibility of an energy storage system. The demand side management scheme minimizes retail company’s operating costs in the wholesale market, and it also considers distribution network constraints, assuring the appropriate quality of service. We have used a dual decomposition method to decouple some constraints while maximizing social welfare. We have also introduced a demand response call event with the main objective to take into consideration the system operational constraints. Through the coordination via local marginal prices, we have obtained a decentralized and distributed bidding/buyback scheme proposing a demand side management program that preserves the integrity of the private information of the different participants.

Two-stage parallel speed-scaling machine scheduling under time-of-use tariffs

As one of the demand-side programs, time-of-use (TOU) tariffs brings opportunities of maintaining power grid stability for electricity providers and chances of energy conservation for manufacturers, but it also brings challenge for enterprises to optimize scheduling schemes. This paper studies a two-stage parallel machine scheduling problem under TOU to minimize total electricity costs. The two-stage parallel machine system is composed of identical parallel speed-scaling machines at stage 1 and unrelated parallel machines at stage 2. The key issues lie in assigning a group of jobs to a set of parallel machines at each stage and choosing the appropriate processing speed for all jobs at stage 1, and then determining the interval of processing time for jobs on each selected machine. To solve this problem, a new continuous-time mixed-integer linear programming model is formulated. According to the characteristics of this model, a tabu search-greedy insertion hybrid (TS-GIH) algorithm is designed, which realizes job-machine assignment based on load balancing principle, job insertion with greedy mechanism as well as movement and speed adjustment strategies to find more suitable positions for jobs. The effectiveness of the proposed TS-GIH is demonstrated by comparing with CLPEX and improved genetic algorithm (IGA) through real-life and randomly generated instances. The results show that TS-GIH can realize the trade-off between computation time and solution quality. Compared with CLPEX, the computation time of TS-GIH is significantly less, and the solution quality is much better than IGA.

An efficient scheme for residential load scheduling integrated with demand side programs and small-scale distributed renewable energy generation and storage

An efficient scheme for residential load scheduling integrated with demand side programs and small-scale distributed renewable energy generation and storage

Profiling energy efficiency tendency: A case for Turkish households

There is no need to discuss the importance of energy and energy policies in the global agenda. Countries whose electricity demand rises steadily, and depends heavily on fossil fuels and imports, should consider energy efficiency in any aspects. As one of examples such a country, this study investigates the behaviors and attitudes of Turkish households regarding energy efficiency. An online survey of 526 Turkish households in 2014 gathered data on current habits including peak hour use, energy labeling, standby use, willingness for behavioral change, and policy options they would like to see implemented to improve energy efficiency. The results indicate the awareness level of energy efficiency among Turkish households is quite low, and should be promoted by demand side programs. Two-step cluster analysis is used to construct clusters to group households with respect to their policy preferences. Four different clusters are identified and characteristics of these clusters suggest the importance of having unique intervention strategies for successful behavioral change and for the attainment of energy efficiency.

The allocation of rental assistance resources: the paradox of high housing costs and high vacancy rates

ABSTRACTThe United States follows a dual strategy to address housing affordability problems among low-income renter households. The dual strategy is premised on a demand-side programme for soft markets and a supply-side programme for tight markets. An examination of housing markets in the US shows that market conditions do not provide much justification for the supply-side approach. Most markets are simultaneously experiencing high rents with high vacancy rates suggesting that the demand-side, voucher approach is better suited to current needs in these markets. High rents drive affordability problems, but the high rent levels appear to be unrelated to market tightness. The implications are that, in most markets, supply-side programmes are not well suited to current market conditions, that expansion of the stock of housing through supply-side programmes will not bring down rents, and that ample units exist to facilitate the implementation of an expanded demand-side programme.

Assessment of modern contraceptives continuation, switching and discontinuation among clients in Pakistan: study protocol of 24-months post family planning voucher intervention follow up

BackgroundPakistan has the second highest fertility rate in South Asia and its increasing population growth presents a significant challenge for country’s path to progress and development. Modern contraceptive methods only account for a slow-rising 26% of use in Pakistan which is further lowest in the underserved areas (< 20%), with a high unmet need for family planning (20%). The David and Lucile Packard Foundation USA and Pakistan funded two operational research projects from 2012 to 2015, that employed a Demand-side Financing (DSF) approach testing the effectiveness of single and multi-purpose voucher schemes in increasing access and uptake of FP services and products among the women of two-lowest income quintiles in the Punjab province of Pakistan. The present paper presents a study protocol which intends to assess the longer term impact of these two voucher intervention programs among married women of reproductive age (MWRA) who received contraceptive services through vouchers.MethodsThis will be a mixed methods study using qualitative and quantitative approaches. A quantitative cross sectional survey will measure the contraceptive uptake among voucher users, included in the endline survey and to examine the attitudes and behaviour of women with respect to contraceptive continuation, switching and discontinuation 24 months post intervention in two districts of Chakwal and Faisalabad in Punjab province of Pakistan. Qualitative in-depth interviews will be conducted with FP service providers operating in intervention areas and with key policy makers in the public sector to examine and document the service provider perspective on sustainability on contraceptive practices and behaviour in the post project closure period within the intervention areas.DiscussionGlobally, there is almost negligible direct evidence on the assessment of longer-term impact of a demand-side financing programs using free or subsidized vouchers for family planning services especially during post-intervention period or when donor money runs out. The findings of this study will help fill the knowledge gap in the context of sustainability issues post-intervention and will provide information to policy makers to develop and plan contraceptive services in the target area to sustain the positive behaviour change in the population.

Toward a sustainable modern electricity grid: The effects of smart metering and program investments on demand-side management performance in the US electricity sector 2009-2012

Building a sustainable modern electricity sector is a key part of the United Nations’ 2030 Sustainable Development Goals. Smart meters are expected to contribute to the achievement of this goal by providing new demand-side management opportunities for utilities. Attempting to address existing gaps in the extant literature, this paper examines the effects of metering technologies and demand-side management program investments using panel data from 87 American electricity utilities for the period 2009–2012. Our model provides strong explanatory power with respect to energy efficiency, and shows that automated meter reading (AMR) devices, advanced metering infrastructure (AMI) devices, direct program costs, and incentive costs all have a positive influence on energy efficiency effects. In contrast, the results for load management are largely insignificant, with the exception of incentive costs that has a small, but significant, negative impact on peak load reductions. We discuss the implications and potential research directions arising from these findings, in particular, the need to consider interactions between different demand-side programs and the influence of different types of information technologies that are emerging as part of the smart grid.

Price elasticities of retail energy demands in the United States: New evidence from a panel of monthly data for 2001–2016

Price elasticities play an important role in energy demand forecasting, which in turn shapes energy policy and investment decisions. However, there is still considerable debate around how responsive customers are to energy prices, and whether investments in metering and consumer education have made them more responsive in recent decades. Using a Generalized Leontief (GL) demand system and a rich panel of monthly data covering 2001–2016 for the lower 48 United States, we estimate own- and cross-price elasticities of retail demand for electricity, natural gas and fuel oil for the three major customer classes: residential, commercial and industrial. These estimates indicate that retail energy demand in the United States was highly price-inelastic over 2001–2016, consistent with historical and current estimates used by many utility planners. Our findings suggest that, with current technologies and behavior, higher energy prices will not induce significant reductions in demand. Hence, energy efficiency standards and utility demand-side programs are still an important strategy for managing energy demand growth, mitigating energy price risk, and reducing the environmental impacts associated with energy use. Finally, while our analysis uses data from the United States, our approach is general and can be readily extended to other countries that have similar data available.

Long-term forecasting of annual peak load considering effects of demand-side programs

The main purpose of this research paper is to investigate the long-term effects of the proposed demand-side program, and its impact on annual peak load forecasting important for strategic network planning. The program comprises a particular set of demand-side measures aimed at reducing the annual peak load. The paper also presents the program simulations for the case study of the Electricity Distribution Company of Belgrade (EDB). According to the methodology used, the first step is to determine the available controllable load of the distribution utility/area under consideration. The controllable load is presumed constant over the analyzed time horizon, and the smart grid (SG) infrastructure available. The saturation of positive effects during intense program application is also taken into account. Technical and economic input data are taken from the real projects. The conducted calculations indicate that demand-side programs can bring about the same results as the energy storage in the grids with a strong impact of distributed generation from variable renewable sources (V-RES). In conclusion, the proposed demand-side program is a good alternative to building new power facilities, which can postpone investment costs for a considerable period of time.

The Emerging Transactive Microgrid Controller: Illustrating Its Concept, Functionality, and Business Case

Microgrids were initially popularized to increase resiliency of real-time electric power systems regarding natural disasters. With the changing electricity industry landscape in recent years associated with cost-effective distributed energy resources (DERs), such as rooftop solar photovoltaic (PV) systems, distributed storage, and increased active demand-side participation, microgrids are finding their place in this landscape as economic transactive agents capable of providing a variety of services to the mutual benefit of the microgrid, the distribution utility, and the power system at large. Presently, microgrids can participate in distribution utility demand response (DR ) and other demand-side programs, provide energy and ancillary services (ASs) to the bulk power system and markets and in some cases provide voltage support and resiliency to neighboring facilities. The emergence of the new distribution system operator (DSO) construct and the transactive energy (TE) paradigm, however, will further enhance a microgrid's capabilities to participate in retail, wholesale, and bilateral markets when operating in a grid-connected mode.

An assessment of the impact of the JSY cash transfer program on maternal mortality reduction in Madhya Pradesh, India

BackgroundThe Indian Janani Suraksha Yojana (JSY) program is a demand-side program in which the state pays women a cash incentive to deliver in an institution, with the aim of reducing maternal mortality. The JSY has had 54 million beneficiaries since inception 7 years ago. Although a number of studies have demonstrated the effect of JSY on coverage, few have examined the direct impact of the program on maternal mortality.ObjectiveTo study the impact of JSY on maternal mortality in Madhya Pradesh (MP), one of India's largest provinces.DesignBy synthesizing data from various sources, district-level maternal mortality ratios (MMR) from 2005 to 2010 were estimated using a Bayesian spatio-temporal model. Based on these, a mixed effects multilevel regression model was applied to assess the impact of JSY. Specifically, the association between JSY intensity, as reflected by 1) proportion of JSY-supported institutional deliveries, 2) total annual JSY expenditure, and 3) MMR, was examined.ResultsThe proportion of all institutional deliveries increased from 23.9% in 2005 to 55.9% in 2010 province-wide. The proportion of JSY-supported institutional deliveries rose from 14% (2005) to 80% (2010). MMR declines in the districts varied from 2 to 35% over this period. Despite the marked increase in JSY-supported delivery, our multilevel models did not detect a significant association between JSY-supported delivery proportions and changes in MMR in the districts. The results from the analysis examining the association between MMR and JSY expenditure are similar.ConclusionsOur analysis was unable to detect an association between maternal mortality reduction and the JSY in MP. The high proportion of institutional delivery under the program does not seem to have converted to lower mortality outcomes. The lack of significant impact could be related to supply-side constraints. Demand-side programs like JSY will have a limited effect if the supply side is unable to deliver care of adequate quality.

A comparison of consumer perceptions towards smart homes in the UK, Germany and Italy: reflections for policy and future research

Smart homes will be a key component of smart grids which can make significant contributions to Europe's transition to a low-carbon energy system. A growing literature on smart meters and demand side programmes focuses on the energy consumption and management services that smart homes offer. However, they can deliver much broader types of services, including assisted living, health and security. By including these non-energy aspects, this paper reveals differences in perceptions of smart homes in a cross-country comparative context to inform the delivery of smart home services. Public perceptions on the role of utilities and government in particular are important factors to be taken into account. The research highlights that policies should leave all paths open due to due to differences in householder preferences and acceptance of smart homes. Further implications for service delivery and planning are highlighted, calling for more interdisciplinary research in this area.

The concept and evaluation of demand side programmes

The concern of utilities about meeting energy demand and the customers' interest in energy efficiency have resulted in the development of the demand side management (DSM) concept. DSM deals with the planning, implementation, and monitoring of those activities that change the time pattern and magnitude of customers' load curve. This is done by adopting efficient technologies and processes that can be directly substituted for less efficient ones and also managerial techniques and alternative energy sources like co–generation resulting in significant overall reductions in energy use. This paper discusses the conceptual framework of DSM and its evaluation for electricity conservation and load management. It identifies the issues by describing the general mechanisms by which DSM programmes effect load shape change and balance the needs of utility and customer.

Modeling Future Life-Cycle Greenhouse Gas Emissions and Environmental Impacts of Electricity Supplies in Brazil

Brazil’s status as a rapidly developing country is visible in its need for more energy, including electricity. While the current electricity generation mix is primarily hydropower based, high-quality dam sites are diminishing and diversification to other sources is likely. We combined life-cycle data for electricity production with scenarios developed using the IAEA’s MESSAGE model to examine environmental impacts of future electricity generation under a baseline case and four side cases, using a Monte-Carlo approach to incorporate uncertainty in power plant performance and LCA impacts. Our results show that, under the cost-optimal base case scenario, Brazil’s GHGs from electricity (excluding hydroelectric reservoir emissions) rise 370% by 2040 relative to 2010, with the carbon intensity per MWh rising 100%. This rise would make Brazil’s carbon emissions targets difficult to meet without demand-side programs. Our results show a future electricity mix dominated by environmental tradeoffs in the use of large-scale renewables, questioning the use tropical hydropower and highlighting the need for additional work to assess and include ecosystem and social impacts, where information is currently sparse.