Demand Side Management Potential Research Articles

Assessing the Demand Side Management Potential and the Energy Flexibility of Heat Pumps in Buildings

The energy demand in buildings represents a considerable share of the overall energy use. Given the significance and acknowledged flexibility of thermostatically controlled loads, they represent an interesting option for the implementation of demand side management (DSM) strategies. In this paper, an overview of the possible DSM applications in the field of air conditioning and heat pumps is provided. In particular, the focus is on the heat pump sector. Three case studies are analyzed in order to assess the energy flexibility provided by DSM technologies classified as energy efficient devices, energy storage systems, and demand response programs. The load shifting potential, in terms of power and time, is evaluated by varying the system configuration. Main findings show that energy efficient devices perform strategic conservation and peak shaving strategies, energy storage systems perform load shifting, while demand response programs perform peak shaving and valley filling strategies.

The value(s) of flexible heat pumps – Assessment of technical and economic conditions

Residential heat pumps are one of the most resource-efficient means for space heating, and their market shares are expected to rise substantially over the next few decades. Through installation of a thermal energy storage, the operation of a heat pump is – to a certain extent – decoupled from heat demand. Such flexibility is frequently claimed to bear a high potential for demand-side management. This study investigates the operational cost savings achievable through the use of such a flexibility option. To this end, a dynamic model of a coupled building and heating system is developed, and several economic model-predictive control strategies for heat-pump operation are derived. These strategies exploit real-time prices and the flexibility of the thermal capacity of the building and/or heat storage. The proposed algorithms are applied using perfect and imperfect foresight. Furthermore, different variations of real-time prices along with several building and storage configurations are investigated. The resulting operational cost savings are contrasted with different paths of investment-cost developments. Results of this investigation demonstrate that investments in flexibility measures (smart-home equipment, thermal storage capacity, etc.) are, for the most part, economically unviable. However, it is also realized that economic feasibility depends greatly on the technical set-up and economic conditions. This study demonstrates that the potential of flexible heat-pump operation is frequently overstated. On the other hand, configurations for which overall system-cost savings could be deemed achievable are also identified.

A means to an industrialisation end? Demand Side Management in Nigeria

Electricity is essential for economic development and industrialisation processes. Balancing demand and supply is a recurrent problem in the Nigerian electricity market. The aim of this work is to assess the technical and economic potential of Demand Side Management (DSM) in Nigeria given different future levels of industrialisation. The paper places industrialisation at the centrefold of the appraisal of DSM potential in Nigeria. It does so by designing industrialisation scenarios and consequently deriving different DSM penetration levels using a cost-optimisation model. Findings show that under the high industrialisation scenario by the year 2050 DSM could bring about 7 billion USD in cumulative savings thanks to deferred investment in new generation and full deployment of standby assets along with interruptible programmes for larger industrial users. The paper concludes by providing policy recommendations regarding financial mechanisms to increase DSM deployment in Nigeria. The focus on DSM serves to shift the policy debate on electricity in Nigeria from a static state versus market narrative on supply to an engagement with the agency and influence on industrial end-users.

Innovation through the effects of solar water heating (SWH) in Africa

Energy is a useful component that has a positive impact to Africa’s socio-economic development. Its effect on households can therefore not be overlooked. Past studies revealed that, the role of the Solar Water Heater is to utilize the energy generated by the sun to heat water. The heating of the water is achieved via the collector. The tubes are filled with water which is heated during the day light hours and this hot water is stored in the main tank. The hot water rises in the tube and is replaced by the cooler water, which is at the lower level of the main tank. This cycle is repeated continuously throughout the day thus heating the water in the main tank. As hot water is drawn from the system, cold water is subsequently supplied. This paper is based on the review of the related literature to show the effects of solar water heating and the usage of innovative technology in residential homes. In particular, the description of SWH product, demand side management potential of solar water heaters, and the innovation diffusion reasons. Then, the conceptual framework as it relates to the innovation diffusion theory will be presented. Lastly, the development of the research problem is outlined. Using a theoretical framework, the paper is able to present the advantages and disadvantages of SWH in Gauteng, South Africa.

Practical and theoretical potential of demand side management in SMEs to balance wind power

In this study, we have investigated both the theoretical and the practical potential of demand side management at small- and medium-enterprises (SMEs) to balance wind power. Our models and experiments indicate that the practical potential for demand side management for this goal is limited. This has several reasons: (i) the willingness and technical potential of SMEs to apply demand side response is limited; (ii) due to the wide variety of processes in SMEs, the application of demand side management demands custom made solutions, which makes large-scale application difficult; (iii) the available potential of demand side management is hardly suitable to follow the electricity production of wind turbines; (iv) the local balancing of wind power results in using more electricity at expensive moments and therefore higher energy costs.

Control of Energy Storage

In the attempt to tackle the issue of climate change, governments across the world have agreed to set global carbon reduction targets. [...]

Optimization-based identification and quantification of demand-side management potential for distributed energy supply systems

A method is presented to identify the potential for demand-side management (DSM) in energy supply systems. Optimization of energy supply systems usually considers energy demands as fixed constraints. Thereby, possible changes on the demand side are neglected. However, demand changes can lead to a better overall solution. Thus, DSM measures should be integrated into the optimization of energy systems.However, integrating optimization of DSM measures generally requires problem-specific process models. To avoid the need for problem-specific process models, we present a generic method applicable to various process domains. The method identifies a merit order of time steps with large potential for DSM and quantifies potential cost savings by DSM. Targets for demand-side measures are provided in a DSM map as guidance for the process engineer.The merits of the novel method are illustrated for an industrial case study. In this study, 9.6% of all time steps are promising for DSM measures since they show a high sensitivity to demand changes. In particular, the method identifies non-intuitive time steps with high cost saving potential through DSM. We identify potential cost savings of more than 10% if DSM measures are implemented.

Demand-side-management by Flexible Generation of Compressed Air

Industrial compressed air systems embrace significant potential for saving both energy and cost due to their share of approximately 7% of the total industrial electricity consumption in Germany. As in electric energy systems based on renewable generation plants supply and demand often do not occur in the same period of time, volatile prices occur and demand side management is gaining importance. Decentralized automation offers opportunities in industrial environments for control of the equipment according to availability of electrical energy. Product-service systems on industrial plants supply manufacturing equipment with compressed air, nitrogen and other technical gases, which partly can be obtained from air by deposition processes. Those systems consist of air compressors, gas separators, reservoirs and lines. With suitable dimensioning and by equipping with automation technology those product-service systems can be used for demand side management purpose. In addition to basic operating parameters like current air pressure and status, those systems can process further information and create, for example, profiles on compressed air consumption over time. By enriching those profiles with data on pressure, volumes, system restrictions and current production requirements, the system control can identify the available potential for demand side management. Evaluation of operational strategies has to optimize conflicting objectives within the triangular relationship of storage design, control of the production according to price prospects and influencing or predicting the use of compressed air.

Experimental determination of demand side management potential of wet appliances in the Netherlands

Abstract The potential of demand side management (DSM) of wet appliances (washing machine, dishwasher and tumble dryer) in households with photovoltaic (PV) systems is studied experimentally focusing on evening peak demand reduction and increase in PV self-consumption. In a sample of 100 Dutch households the electricity demand is monitored for one year at high time resolution. It is found that the dishwasher has the best DSM potential, with a median average peak reduction potential up to 35 W per household on average for all appliances, while PV self-consumption for the median household can be increased with 68 kWh/year per appliance. The tumble dryer and washing machine’s potentials are 30 W and 25 W per household, respectively, for the mean average peak reduction, and 38 kWh and 28 kWh, respectively, per household per year for increase in PV self-consumption per appliance. Further, the median peak reduction potential of a single group of wet appliances ranges from 1% to 5% of the power demand in peak hours, while combined they could add up to 10% of the total peak. The median increase in PV self-consumption is in the range between 1.5% and 4% for separate appliances, while the median total could provide an increase up to 129 kWh per household per year if a household possesses and utilizes the potential of all appliances, which is about 6% of the annual household demand. In conclusion, DSM potential for wet appliances is limited.

The Demand Side Management Potential to Balance a Highly Renewable European Power System

Shares of renewables continue to grow in the European power system. A fully renewable European power system will primarily depend on the renewable power sources of wind and photovoltaics (PV), which are not dispatchable but intermittent and therefore pose a challenge to the balancing of the power system. To overcome this issue, several solutions have been proposed and investigated in the past, including storage, backup power, reinforcement of the transmission grid, and demand side management (DSM). In this paper, we investigate the potential of DSM to balance a simplified, fully renewable European power system. For this purpose, we use ten years of weather and historical load data, a power-flow model and the implementation of demand side management as a storage equivalent, to investigate the impact of DSM on the need for backup energy. We show that DSM has the potential to reduce the need for backup energy in Europe by up to one third and can cover the need for backup up to a renewable share of 67%. Finally, it is demonstrated that the optimal mix of wind and PV is shifted by the utilisation of DSM towards a higher share of PV, from 19% to 36%.

Clean energy utility for multifamily housing in a deregulated energy market

Energy efficiency and renewable energy (EERE) investment in multifamily residences in the United States has not kept pace with investment in resident-owned facilities. Split incentives, where owners cannot benefit economically from energy cost savings for residences and resident investment in EERE is not feasible, have posed a significant barrier. A clean energy utility is posited to circumvent this barrier. This utility would be responsible for power purchase from the grid, ideally as a real-time purchase agent from the grid manager; investment in energy efficiency and renewable energy; and demand management through control of water heating, as well as supply-side management through deployment of stored solar at near-peak grid power purchase cost. A clean energy fee is posed for recovery of costs, in contrast to typical consumption strategies (per kWh).A case study approach is employed to evaluate the feasibility of this type of utility of reducing carbon production in this building sector. Considered in the analysis is a 2008 multifamily facility located in the Midwest of the U.S., with apartment level interval meters for both power and water. Historical data from these meters were used to assess the savings and demand-side management potential from investments in improved efficiency lighting, refrigeration, heat pumps, and water heaters, as well as investments in solar PV and storage for supply-side management. The results show that the packaged retrofit EERE investment could yield costs for residents and profits for energy manager comparable to those in the current residential pricing scheme, while reducing grid-sourced energy by 42%. When solar PV and battery storage are added to the solution, it is shown that a clean energy fee structure can cost-effectively drive savings to over 54%. For new construction, even deeper cost effective savings are realizable. This research demonstrates the potential to drive deep energy savings in the multifamily building sector that can lower costs to residents through the establishment of clean energy utilities which recover investments in energy efficiency, demand management, and solar PV/battery systems through resident clean energy fees rather than consumption fees.

Modeling the Effects of Variable Tariffs on Domestic Electric Load Profiles by Use of Occupant Behavior Submodels

Emerging infrastructure for residential meter communication and data processing carries the potential to control household electrical demand within local power system constraints. Deferral of load control can be incentivized through electricity tariff price structure, which can in turn reshape a daily load profile. This paper presents a stochastic bottom-up model designed to predict the change in domestic electricity profile invoked by consumer reaction to electricity unit price, with submodels comprising user behavior, price response, and dependency between behavior and electric demand. The developed models are used to analyze the demand side management potential of the most relevant energy consuming activities through a simulated German household demonstrating that in the given scenario 8% of the annual electricity demand is shifted, leading to a 35€ annual saving. However, a 7% higher than average peak load results from the structure of the tariff signal modeled herein. A discussion on selected aspects for tariff design for categories of typical household appliances is included.

Development and validation of grey-box models for forecasting the thermal response of occupied buildings

Building thermal wall mass provides a flexible heat capacity which can be effectively used for load shifting, thus enabling demand side management (DSM). The most crucial barrier for a practical application of buildings as short term heat storage is the lack of knowledge about the building physical properties. This study presents a model identification approach for forecasting the building thermal response based on grey-box models. The model parameters are estimated by optimizing the model output to historical data under the consideration of plausible physical constraints. The thermal flexibility of a building and therewith its demand side management potential can be determined based on the assessed model parameters. This study uses measurements from buildings in normal operation to evaluate the thermal prediction of grey-box models despite the stochastic events within the training data. In order to find the best level of model complexity, four grey-box models were compared in their ability to forecast the building indoor temperature behaviour. The analysis revealed that a two-capacity model structure with an additional consideration of the indoor air as a mass-less node (4R2C-model) enables the most accurate qualitative prediction of the indoor temperature. Further, the general validity of the model structure allows for its application on different buildings types.

Smart Factory Meets Smart Grid: Cyber-Physical Compressed Air Systems Enable Demand Side Management in Industrial Environments

In electric energy systems based on renewable generation plants supply and demand often do not occur in the same period of time. Consequently demand side management is gaining importance whereby decentralized automation offers opportunities in industrial environments. Compressed air systems on industrial plants consist of air compressors, compressed air reservoirs and compressed air lines. With suitable dimensioning those industrial compressed-air systems can be used for demand side management purpose. As power consumption of industrial air compressors ranges between a few and several hundred kilowatts each, swarms of communicatively connected air compressors can contribute to the stabilization of power grids. To avoid costly production downtime it is to ensure, that a reliable, non-disruptive supply of compressed air can be maintained at all time. Industrial compressed air systems equipped with automation technology and artificial intelligence, which hereinafter are referred to as Cyber-Physical Compressed Air Systems (CPCAS), allow new business models for utilities, industrial enterprises, compressor manufacturers and service providers. In addition to basic operating parameters like current air pressure and status, those systems can process further information and create, for example, profiles on compressed air consumption over time. By enriching those profiles with data on pressure, volumes, system restrictions and current production requirements (plans), the CPCAS can identify the available potential for demand side management. Ipso facto predictive power on electricity consumption is increasing. By providing the information obtained to the power company or a service provider, savings in electricity costs may be achieved. Expenses within the industrial company may be lowered further as compliance with agreed load limits is being improved by automatic shutdown of air compressors upon reaching the load limit. Within this article the structure of the aforementioned Cyber-Physical Compressed Air Systems is presented in more detail, relations between the major actors are being shown and possible business models are being introduced.

Copolymer-bound phase change materials for household refrigerating appliances: experimental investigation of power consumption, temperature distribution and demand side management potential

This study presents the results of an experimental investigation of the influence of latent thermal heat storage elements on the power consumption as well as the temperature distribution of commercial household refrigerators. Two evaporator types and a standard wire-and-tube condenser are equipped with copolymer-bound phase change materials (PCM) and the performance is determined under standard conditions. The results show that refrigerating appliances equipped with PCM can be optimized through modifications of the control strategy to achieve different targets: (a) Power consumption can be significantly reduced by increasing the evaporator and decreasing the condenser temperature. (b) Temperature fluctuations in the refrigerator's fresh-food compartment during the cooling cycle can be reduced from 4 °C to 0.5 °C. (c) The cooling cycle duration can be tripled without compromising the fresh-food compartment conditions. The latter may help to meet the growing demand for balancing power consumption to stabilize the power grid, e.g. if the share of highly fluctuating, sustainable energy supply is large.

Reducing Household Electricity Consumption through Demand Side Management: The Role of Home Appliance Scheduling and Peak Load Reduction

Abstract One of the key issues arising from extended smart metering roll-out across Europe is how the data obtained from the meters may be used to provide end users with important information on energy-saving advice, which is one of the main principles of demand side management (DSM). The investigation of the potential for demand side management to reduce peak load were evaluated in this study. One four-person household was surveyed with the aim to find out user activities within the house, in particular, the use of appliances. Two appliances – a washing machine and dishwasher - were selected for assessing the potential for load shifting. The derived results show that, as a result of washing machine and dishwasher load shifting, the peak load of a dwelling can be reduced on average by 24% and 13.5%, respectively.

Electric load behaviour and DSM potential of office buildings

Due to the rising use of fluctuating renewable energy production, electricity production curve in the future will not be able to follow the demand curve anymore. Therefore, time-critical, variable charges are likely to be introduced. Whereas large consumers of electricity already have to pay attention to this issue – the peak demand is measured and cost effective for customers with a consumption higher than 100,000kWh or connection power more than 50kW [1] – the topic will become relevant for other customers in the future. Due to the roll-out of smart metres, it is very likely that time-relevant tariffs will become standard for all kinds of users, which means that the moment of electricity consumption will be cost-relevant. This paper deals with the electric load behaviour of office buildings and their potential to use demand side management (DSM) to optimise load behaviour. Because of use during the day, when prices are usually higher than during the night, office buildings mainly demand electrical energy during periods of high prices. By identification and utilisation of DSM potential, considerable sections of the demand can be shifted to hours with lower prices. Concerning integration of photovoltaic systems, two aspects has to be taken into account. When PV is an additional option to reduce electrical energy demand during high prices, on-site produced electricity should be also used on-site and therefore it has to be assured, that demand does not fall below PV-production. Another possibility to shift loads is to use thermal or electrochemical storage systems.

Autonomous optimal control for demand side management with resistive domestic hot water heaters using linear optimization

Electric domestic hot water heaters are well suited for demand side management, as they possess high nominal power ratings combined with large thermal buffer capacities. In this paper, their potential for demand side management via pseudo cost functions is studied. A fully mixed thermal model of the water heater is used to formulate the optimization problem as a binary integer program, whereas a multi-layer model is used to simulate actual system behavior. The current approach requires only one-way communication of a pseudo cost function, which may depend upon factors such as expected electricity prices, local grid load, and expected renewable electricity production. An optimal heating strategy is then determined on-site based on the expected demand and the pseudo cost function. The expected demand is found via a nearest-neighbor data-mining algorithm using historic data. The optimization algorithm is used in conjunction with long-term simulations assuming different user behavior patterns and optimization strategies. The current approach compares favorably with conventional night tariff-switched operation. Assuming typical user behavior and using real spot market electricity prices as the pseudo cost function leads to cost savings of approximately 12% and energy savings of approximately 4%. Higher energy savings of approximately 12% can be attained by setting the pseudo cost function constant resulting in energy-driven optimization.

Simulation of an Air‐to‐Water Heat Pump System to Evaluate the Impact of Demand‐Side‐Management Measures on Efficiency and Load‐Shifting Potential

AbstractIncreasing variable renewable electricity generation in Germany challenges the German electricity supply in terms of mismatch between supply and demand as well as grid stability. Demand side management (DSM), a portfolio of measures to improve the energy system on the consumption side, can contribute to the ability to cope with the upcoming challenges in the future smart power grid.1 Currently, over 500 000 electrical compression heat pumps (HP) provide a potential for DSM in Germany.2, 3, 4 Whereas static load shedding for heat pumps is state‐of‐the‐art, concepts for dynamic load shifting still need to be developed. A variety of heat pump systems (HPS) and control strategies provide different potentials to shift loads. This simulation study has been performed to examine variations of a typical single‐family‐house HPS in terms of efficiency and DSM potential. Six scenarios for 2012 and six scenarios for 2030 are analyzed with varying buffer storage sizes, control strategies, and heat pump capacities. The prior condition for the realization of load shifting through thermal energy storage has been to prevent nominal room temperature changes. The presented results indicate that electrical heat pumps combined with buffer storage are suitable devices for DSM without violating the nominal room temperature. However, the load shifting caused an increased electricity consumption of up to 19 %.

Potential of Demand Side Management to Reduce Carbon Dioxide Emissions Associated with the Operation of Heat Pumps

This work considers the potential reduction in the carbon dioxide emissions associated with the operation of Air Source Heat Pump which could be achieved by using demand side management. In order to achieve significant reductions in carbon dioxide emissions, it is widely envisioned that electrification of the heating sector will need to be combined with decarbonisation of the electrical supply. By influencing the times at when electric heat pumps operate such that they coincide more with electricity generation which has a low marginal carbon emissions factor, it has been suggested that these emissions could be reduced further. In order to investigate this possibility, models of the UK electrical grid based on scenarios for 2020 to 2050 have been combined with a dynamic model of an air source heat pump unit and thermal models of a population of dwellings. The performance and carbon dioxide emissions associated with the heat pumps are compared both with and without demand side management interventions intended to give preference to operation when the marginal emissions factor of the electricity being generated is low. It is found that these interventions are unlikely to be effective at achieving further reductions in emissions. A reduction of around 3% was observed in scenarios based around 2035 but in other scenarios the reduction was insignificant. In the scenarios with high wind generation (2050), the DSM scheme considered here tends to improve thermal comfort (with minimal increases in emissions) rather than achieving a decrease in emissions. The reasons for this are discussed and further recommendations are made.