Demand-side Management Options Research Articles

Reducing carbon dioxide emissions from electricity sector using demand side management

ABSTRACT This paper discusses the Clean Power Plan (CPP) legislation and its repeal on the emissions from electricity generation sources. Demand side management (DSM) is probed to illustrate an alternative technique to achieve lower emissions goals. This work discusses the Climate Action Plan (CAP) corresponding to Fort Collins, Colorado, U.S. and its timeline targets. Therefore, the paper provides a technique for prioritizing DSM options through a Multi-Criteria Decision-Making (MCDM). In that regard, a framework is created to examine several options of DSM in reducing carbon footprints. The algorithm states that affecting Greenhouse Gases (GHG) in electric power system is the main goal and this can be achieved by implementing DSM technologies in distribution systems. MCDM algorithms have been proposed to prioritize alternatives and select the ones that achieve suitable emissions reduction. The findings from Analytic Hierarchy Process (AHP) show that the “communication and intelligence” option has a global priority of 0.341 making it the potential optimal alternative in achieving the goal. The second alternative is “electric stationary storage” with global priority of 0.207. The results obtained from Analytic Network Process (ANP) suggest that “communication and intelligence” is the optimum technology to reach the target with a priority of 0.284.

Evaluation of the Techno-Economic Benefits of Shifting Air Conditioning Loads from Evening and Day Peaks to Off Peak Hours A Case Study

With the development of industries and changes in living standards of the society, demand for electricity is rapidly increasing. In order to maintain the demand supply balance and to provide uninterrupted supply, utilities have to meet electricity demand in the most economical way. Building new power plants is not always the most economical solution. The trend now, is towards reducing and controlling the demand through Demand Side Management (DSM) techniques which lead to almost always economical and environment-friendly solutions. In this paper, Heating, Ventilation and Air Conditioning (HVAC) system of Cinnamon Lakeside Hotel is analysed to identify the potential DSM options that can be implemented. Thermal Energy Storage (TES) was selected as the DSM option to store cooling load during off-peak hours of the day where electricity is fairly cheap and use it during peak and day hours when the electricity is expensive. Technical viability and potential saving that can be achieved through TES in hotel sector of Sri Lanka is further analysed.

Demand side management opportunities, framework, and implications for sustainable development in resource-rich countries: Case study Qatar

Abstract Over the last decades, global consumption of energy and environmental resources have been rapidly increasing due to advances in the production and transportation of goods, as well as reduced barriers to global trade markets. This trend raised sustainable consumption issues because of inefficient and wasteful use of resources, especially in resource-rich countries with high purchasing power and subsidized tariffs offered to residents. It is also well-known that resources abundance tends to lower financial development and limit productivity growth and social development. On the other hand, there is a growing acceptance that supply-side policies need to be complemented by demand-side management to support sustainable cleaner production and remedy aforementioned adverse impacts. In this study, we present the results of an investigation on demand-side management (DSM) opportunities and a framework developed for Qatar as a representative of an emerging resource-rich countries and discuss implications for cleaner production. The rationale behind is that Qatar is a commodity-dependent developing country, who, during the last five years, has experienced a population growth of 35%, and an increase in electricity and water demand of 46% and 35%, respectively. Similarly, during the same period, the national vehicle fleet has grown by more than twofold. These figures have ranked Qatar at the top of the per-capita energy, carbon, and water consumption list in the world and increased environmental vulnerability and reduced climate resilience. To that end, the objectives of this study are to: (1) construct a DSM framework tailored to the needs of resource-rich country like Qatar from economic, social, environmental, and technical aspects; (2) present, analyze, and discuss the results of a survey that reveals the perceptions, attitudes, and responses of local residents towards the applicability of DSM policies; and (3) discuss methods and solutions to achieve cleaner energy consumption. The conducted survey covered electricity, water, and transportation sectors and showed that residents have low awareness about their consumption habits, but they have high willingness to reduce their consumption levels. In the last section, we present the survey results and discussions as a reference for policy-makers to promote the most promising DSM options in Qatar. To the best of authors' knowledge, this is the first survey-based study conducted in the Gulf Cooperation Council region where a significant portion of world's oil and natural gas resources are extracted. Therefore, the results could provide insights to other resource-rich countries with similar characteristics to devise more efficient policies for promoting welfare-enhancing and sustainable consumption behavior.

Heat demand peak shaving in urban integrated energy systems by demand side management - A techno-economic and environmental approach

The integration of variable renewable resources and decentralized energy technologies generates the need for a larger flexibility of the energy demand. In order to fully deploy a demand side management approach, synergies between interconnected energy systems have to be systematically implemented.By taking this standpoint, this study proposes a new approach to explore the potential of multi-energy integrated energy systems. This approach is constituted by two main steps, which are (1) the performance simulation of selected energy infrastructures and (2) the estimation of related techno-economic performance indicators. Step (1) expands the work presented in previous literature, by including a novel co-simulation feature. In step (2), the levelized cost of energy and location-dependent emission factors are used as key performance indicators.In this paper, the presented approach is demonstrated by implementing two demand side management options for heat peak demand shaving. A Swedish residential neighborhood is considered as a case study. The first option explores the potential of storing heat in the thermal mass of residential buildings. The proposed strategies lead to a decrease of up to 70% of primary energy consumption, depending on the indoor comfort requirements. The second option estimates the techno-economic feasibility of a new set of scenarios based on the integration of geothermal distributed heat pumps within a district heating network. The district heating scenario is found to be the most techno-economical convenient. Nevertheless, a moderate penetration of distributed heat pumps (around 20%) is shown to have a good trade-off with the reduction of CO2 emissions.

Impact of renewable energy (hydro) on electricity prices in Ghana: A tale of the short- and long-run

This study examines the dynamic effects of a hydro-based technology on electricity prices in Ghana. As a counterfactual model, this article also examines the dynamic effects of a thermal-based technology on electricity prices. Given the significance of total electricity expenditure in national and household final consumption expenditure, the findings have important implications on economic-wide welfare. To do this, we estimate a dynamic electricity price model based on the autoregressive distributed lag model. The findings reveal that, the effect of hydro on electricity price is dynamic in nature, and the technology provides better cost advantages than the thermal technology, in terms of reducing end-user tariffs. Though there is an associated risk with relying on the former which could impose a higher cost in the short-term, in the long-term, the effect seems to vanish. Further results show that, the positive pass-through effect of interest rate, exchange rate, and crude oil price to electricity price is gradual and materialises in the long-term. In sum, the task of achieving lower electricity tariffs in the country is multifaceted. Investment in a hydro-based renewable technology is critical as well as investment in demand-side management options. Moreover, prudent macroeconomic policies and structural amendments of the automatic price adjustment formulae are also critical.

Modeling Aggregate Hourly Energy Consumption in a Regional Building Stock

Sound estimates of future heat and electricity demand with high temporal and spatial resolution are needed for energy system planning, grid design, and evaluating demand-side management options and polices on regional and national levels. In this study, smart meter data on electricity consumption in buildings are combined with cross-sectional building information to model hourly electricity consumption within the household and service sectors on a regional basis in Norway. The same modeling approach is applied to model aggregate hourly district heat consumption in three different consumer groups located in Oslo. A comparison of modeled and metered hourly energy consumption shows that hourly variations and aggregate consumption per county and year are reproduced well by the models. However, for some smaller regions, modeled annual electricity consumption is over- or underestimated by more than 20%. Our results indicate that the presented method is useful for modeling the current and future hourly energy consumption of a regional building stock, but that larger and more detailed training datasets are required to improve the models, and more detailed building stock statistics on regional level are needed to generate useful estimates on aggregate regional energy consumption.

Demand-Side Flexibility for Energy Transitions: Policy Recommendations for Developing Demand Response

As a follow-up to IRGC's report on demand-side flexibility for energy transitions, this Policy Brief highlights that increasing flexibility in power systems is needed to accommodate higher shares of non-controllable and intermittent renewable generation, and that this requires changes to the market design and regulatory framework, to facilitate the development and deployment of appropriate technologies and market-based instruments (e.g. taxes and subsidies). The Policy Brief focuses on demand response (DR), since it is emerging as a powerful demand-side energy management option to deliver flexibility. Specifically, DR can contribute to reducing overall electricity consumption or shifting demand in such a way that consumption better follows generation, particularly intermittent wind and solar.

APPLICATION OF PROMETHEE METHOD FOR DEMAND SIDE MANAGEMENT (DSM) OPTIONS RANKING

Demand Side Management (DSM) is a method used to modify the electrical load profile of a consumer to reduce its electricity bill. There are various types of DSM options available but mostly involve costs to be incurred by consumers. Moreover, the effectiveness of a DSM option depends on various factors including investment cost, saved energy, payback period and more. Multi Criteria Decision Analysis (MCDA) is a tool that can be applied to make decision when a lot of factors to be taken into account. In DSM, Analytical Hierarchy Process (AHP) is one MCDA technique that is widely used in ranking the DSM options. However, AHP requires additive aggregation that may cause lost in detailed information. This paper presents another MDCA method; Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) to perform the ranking of DSM options. PROMETHEE (I and II) were used in a case study and the results shows that PROMETHEE give the same result as AHP. PROMETHEE has an advantage over AHP as it does not require additive aggregation even the problem is multi-dimensional and could provide visual analysis.

Modeling and disaggregating hourly electricity consumption in Norwegian dwellings based on smart meter data

By area-wide implementation of smart metering, large amounts of individual electricity consumption data with a high temporal resolution become available. We use multiple regression models for hourly electricity consumption in Norwegian dwellings, based on panel data consisting of hourly smart meter data, weather data, and response data from a household survey. Two models based on daily and hourly mean values of outdoor temperature, respectively, are compared and discussed. Our results indicate that daily mean outdoor temperature – represented by heating degree day – can serve as weather-related input variable for modeling aggregate hourly electricity consumption. The regression models are further used to break down hourly electricity consumption into two components, representing modeled consumption for space heating and other electric appliances, respectively. Thus, without submetering electric heating equipment an estimate for heating energy consumption is available, and can be used for evaluating different demand side management options, e.g. fuel substitution or load control. Moreover, the models can be used for forecasting aggregate regional electricity consumption in the Norwegian household sector with a high temporal resolution, as e.g. changes in regional climatic conditions, dwelling structure, and demographic factors can be taken into account.

Acceleration strategies of Benders decomposition for the security constraints power system expansion planning

Nowadays the power generation and transmission are substantial elements for the society, and will definitely play a more important role in the future. In this paper a modeling framework is presented to analyze security constrained composite generation and transmission expansion planning problem in power systems. Despite of the traditional expansion planning approaches where only supply side options are considered, the proposed approach accounts for both supply and demand side management (DSM) options simultaneously. DSM options are incorporated to correct the shape of the load duration curve in terms of peak clipping and load shifting programs. A mixed integer non-linear programming model is developed to find the optimal location and timing of electricity generation/transmission as well as DSM options while the effect of transmission losses are also taken into account. Nonlinearity of the transmission loss terms is eliminated using the piecewise linearization. Motivating from the structure of the model, Benders decomposition (BD) algorithm is devised. Three effective strategies named: valid inequalities, multiple generation cuts and strong high density cut are also employed to improve the convergence of the proposed BD algorithm. The performance of the accelerated BD algorithm is validated via applying it to the modified 6, 21, 48, 57, 118 and 300 bus IEEE reliability test systems. The computational experiments ensure the practicality of the proposed BD algorithm in terms of decreasing the number of iterations and CPU times.

Integrated Resource Planning for Long-term Electricity Supply in Selected GMS Countries, Part 1:Energy Efficiency and Renewable Energy

The scarcity of fossil fuel to supply the high growth in energy demand in the selected Greater Mekong Subregion (GMS) is leading to the concern about future electricity supply. The effect of the high fossil fuel price on the global market would lead to limitation in economic development in this region. In 2007, most countries in the selected GMS, namely Cambodia, Laos, Thailand, and Vietnam, used abundant fossil fuels in electricity generation. Fossil fuels used in power generation accounted for 90%, 85%, 60%, and 1.5% in Cambodia, Thailand, Vietnam, and Laos, respectively. This study includes the integrated resource planning (IRP) concept into the long-term power planning. IRP is the most appropriate approach that applied to both demand and supply sides. To curb the high growth in electricity demand, the demand-side management options are taken into account. To reduce the high dependency on imported fossil fuel, the domestic renewable energy resources and reduction in transmission and distribution losses are introduced. Results of this study were analyzed by using the Long-range Energy Alternatives Planning system model. Results reveal that under the IRP concept, the selected GMS countries could save the installed power capacity of 5,780 MW by 2030.

Near real time load shifting control for residential electricity prosumers under designed and market indexed pricing models

This paper presents an event driven model predictive control approach for a local energy management system, enabling residential consumers to the automated participation in demand side management (DSM) programs. We consider a household equipped with smart appliances, a storage unit, electric vehicles and photovoltaic micro-generation. Resources are coordinated according to the needs of maximizing self-consumption and minimizing the cost of energy consumption, in a contractual scenario characterized by designed or market indexed pricing models, with DSM options. The control action (appliances’ start times, the storage charging profile and the IEC 61851 compliant charging profile of the electric vehicles) is updated every time an event triggers the controller, such as a user request, a price/volume signal or the notification of a new forecast of micro-generation from the photovoltaic unit. The control framework is flexible enough to meet the real dynamics of a household and short-term grid requirements, while taking into account user preferences, contractual and technical constraints. A proper set of simulations validates the proposed approach.

Modeling of Demand Side Management Options for Commercial Sector in Maharashtra

There has been an unbalance between demand and supply of electricity in Maharashtra, a shortage of 20% peak power was reported in year 2011-12. Demand side management (DSM) in the commercial sector (consuming about 12% of the state electricity) can help to bridge this gap. In this paper three DSM options namely global temperature adjustment (GTA), chilled water storage (CWS) and variable air volume system (VAVS) are evaluated to give potential energy savings and load shifting. Simulation of GTA model for a sample school building gave 21.3% saving in compressor work for a change of room settings from 23oC, 50% RH to 26oC, 40% RH. Model for CWS was simulated for an office building in Mumbai; the results showed a cooling load shifting of 1638TRh out of 2075TRh was possible with an optimum tank size of 450kl. Simulation of VAVS for a sample school building showed fan energy savings of 68% over CAVS.

An Artificial Neural Network in Short-Term Electrical Load Forecasting of a University Campus: A Case Study

This paper presents an artificial neural network (ANN) for forecasting the short-term electrical load of a university campus using real historical data from Colorado State University. A spatio-temporal ANN model with multiple weather variables as well as time identifiers, such as day of week and time of day, are used as inputs to the network presented. The choice of the number of hidden neurons in the network is made using statistical information and taking into account the point of diminishing returns. The performance of this ANN is quantified using three error metrics: the mean average percent error; the error in the ability to predict the occurrence of the daily peak hour; and the difference in electrical energy consumption between the predicted and the actual values in a 24-h period. These error measures provide a good indication of the constraints and applicability of these predictions. In the presence of some enabling technologies such as energy storage, rescheduling of noncritical loads, and availability of time of use (ToU) pricing, the possible demand-side management options that could stem from an accurate prediction of energy consumption of a campus include the identification of anomalous events as well the management of usage.

Using Information-Gap Decision Theory for Water Resources Planning Under Severe Uncertainty

Abstract Water resource managers are required to develop comprehensive water resources plans based on severely uncertain information of the effects of climate change on local hydrology and future socio-economic changes on localised demand. In England and Wales, current water resources planning methodologies include a headroom estimation process separate from water resource simulation modelling. This process quantifies uncertainty based on only one point of an assumed range of deviations from the expected climate and projected demand 25 years into the future. This paper utilises an integrated method based on Information-Gap decision theory to quantitatively assess the robustness of various supply side and demand side management options over a broad range of plausible futures. Findings show that beyond the uncertainty range explored with the headroom method, a preference reversal can occur, i.e. some management options that underperform at lower uncertainties, outperform at higher levels of uncertainty. This study also shows that when 50 % or more of the population adopts demand side management, efficiency related measures and innovative options such as rainwater collection can perform equally well or better than some supply side options The additional use of Multi-Criteria Decision Analysis shifts the focus away from reservoir expansion options, that perform best in regards to water availability, to combined strategies that include innovative demand side management actions of rainwater collection and greywater reuse as well efficiency measures and additional regional transfers. This paper illustrates how an Information-Gap based approach can offer a comprehensive picture of potential supply/demand futures and a rich variety of information to support adaptive management of water systems under severe uncertainty.

Economic and environmental implications of demand-side management options

End-use electricity efficiency improvements offer an inexpensive way to reduce power shortages. The present study estimates the potential of demand-side management efficiency improvement targeted at (1) short-term efficiency improvement (agricultural pump rectification) that can provide immediate relief, and (2) long-term efficiency improvement (appliance standards such as AC and refrigerator, new agricultural pump purchase and pump replacement) for Gujarat state in India. The methodology includes the calculation of cost of conserved energy for each technology, which works out to be (−1.18) US$ cents/kW h for new agriculture pump sets, 1.03 US$ cents/kW h for refrigerators and 5.21 US$ cents/kW h for air conditioners. The price of power varies around 1.13 US$ cents to 12.1 cents/kW h in Gujarat. The annual energy savings from the selected energy-efficient technologies are approximately 8767 GW h over a period of 10 yr, while the estimated peak power savings are about 1814 MW, large enough to eliminate one-fourth of the state's electricity shortages. Also, the estimated CO 2 emissions savings are about 7715 Giga grams (Gg) from implementation of the selected energy efficiency measures over a period of 10 yr.

Improving China’s water resources management for better adaptation to climate change

Challenged by insufficient water resources and by degraded water quality caused by widespread pollution, China faces an imbalance between the supply and the demand of water for supporting the rapid social and economic development while protecting the natural environment and ecosystems. Climate change is expected to further stress freshwater resources and widen the gap between the demand for and supply of water. As a legacy of the earlier planned economy, water resources management has been primarily supply-driven, which largely fails to account for the economic nature of water resources in relation to their natural characteristics. This paper presents a historical perspective on the water resources management policies and practices in China, and recommends demand management and pollution control as key measures for improving water resources management to adapt to climate change based on the current political, socio-economic and water resources conditions. The past and future impacts of climate change on water resources in China and the general adaptation strategies are also presented. How demand management through increasing water use efficiency, improving water rights and rights trade, and effective regulation enforcement, along with pollution control could improve China’s water resources management are discussed in details. Ultimately, China should develop a sustainable water resources management strategy based on both supply- and demand-side management options to make the limited water supplies meet the demands of economic development, social well-being and the conservation of ecosystems in the context of global climate change.

Decision support for assessing demand side management programmes

The structural changes of the energy markets, as well as the energy companies’ obligations to abide by the emission limits have contributed to a shift among the companies’ priorities, giving new impulse to demand side management (DSM) programmes, which can be seen as a way to meet several of the energy companies’ modern objectives. However, appraising the DSM options’ contribution to these objectives is a complex task, considering the imprecision and uncertainty of the related information. The objective of the paper is to present an integrated decision support methodology for the pre-selection of the DSM programmes, using an experts based system, and their evaluation, using the ‘linguistic TOPSIS’ model, so as to identify and assess the DSM contribution to the energy policy objectives. The application of the method to the Greek energy market and the related sensitivity analysis are presented and discussed.

How to select appropriate measures for reductions in negative environmental impact? Testing a screening method on a regional energy system

The aim of this study is to develop a method that allows selecting appropriate measures for reductions in negative environmental impacts on a regional energy system. In this paper a sophisticated screening method based on theoretical and practical basics of decision-making is proposed. The proposed method is applied and tested on the energy system of a typical rural middle-sized region in Latvia. The starting point for energy system analysis was evaluation of DSM (demand side management) options but later authors chose to include also primary energy to evaluate the whole regional energy system. The proposed method foresees different aspects: not only technical and economical possibilities, but also political and social factors that are very important in the decision-making process are taken into account.

A general equilibrium analysis of potential demand side management programs in the household sector in Thailand

PurposeThe purpose of this paper is to examine potential demand side management (DSM) programs in terms of their impacts to the overall economy in Thailand.Design/methodology/approachA multi‐sector computable general equilibrium (CGE) model of Thailand has been developed to accomplish the objectives of this study. The potential DSM program considered refers to replacement of less efficient electrical appliances with their efficient counterparts in the household sector in Thailand.FindingsThe study finds that the economy‐wide impacts of the DSM program (e.g., economic welfare, GDP, international trade) depend on three key factors: the project economics of the DSM option or the ratio of unit cost of electricity savings to price of electricity (CPR); the implementation strategy of the DSM option; and scale or size of the DSM option. This paper shows that the welfare impacts of the DSM programs would improve along with the project economics of the DSM programs. If the DSM program is implemented under the CDM, the welfare impacts would increase along with the price for certified emission reductions units. On the other hand, the welfare impacts would increase up to the optimal size or scale of the program, but would start to deteriorate if the size is increased further.Research limitations/implicationsThe welfare function considered in this paper does not account for benefits of local air pollution reductions. The study provides crucial insights on designing DSM projects in Thailand to ensure that DSM programs are beneficial for the economy as a whole.Originality/valueAnalyses of DSM options under the CDM using CGE models are not available in the literature. This is the first paper in this area.