Demand Side Management Potential Research Articles

Optimization of design and operation of a digestate treatment cascade for demand side management implementation

Sustainable chemical engineering through demand side management (DSM) and renewable feedstock integration e.g. in biorefineries are key to optimizing the use of fluctuating energy resources and minimizing environmental impact while conserving resources. This contribution presents the results of the economic evaluation of integrating DSM into biofuel biorefineries through a dynamic simulation approach. A previously developed decision support tool for DSM implementation was extended to describe the size of intermediate buffer tanks as a function of oversizing up- and downstream processes. Design optimization of the process cascade determined the oversizing that allows the optimal balance of operational cost reduction through flexibility and capital cost increase through oversizing. Scheduling optimization validated the results of the steady-state optimization and show that, by considering interactions between processes, buffer tank capacity can be reduced, while increasing DSM potential.

Informing targeted Demand-Side Management: Leveraging appliance usage patterns to model residential energy demand heterogeneity

The transition towards decentralised and decarbonised electricity systems requires a detailed understanding of residential energy demand to inform effective Demand-Side Management (DSM) strategies. Current modelling approaches predominantly rely on socio-demographic factors to capture occupant behaviour heterogeneity, potentially overlooking critical household energy usage variability essential for low-voltage grid analysis.Alternatively, we propose a methodology centred on temporal and intensity patterns of appliance usage. Specifically, we develop an activity-based energy demand model that establishes pattern-dependent links between occupants' activity schedules and appliance switch-on events. Furthermore, we evaluate our approach's ability in estimating the distribution of DSM potential within the population, comparing it with conventional approaches based on socio-demographic classes.By examining laundry and dishwashing as case studies, the results demonstrate that our approach provides a more comprehensive characterisation of energy demand heterogeneity compared to conventional socio-demographic-based approaches, offering three key advantages: (i) enabling the identification and targeting of population segments with higher flexibility potential, (ii) determining the optimal contribution of different population segments to various flexibility services, and (iii) informing the design of actionable DSM interventions. Lastly, we propose strategies for operationalizing a pattern-oriented approach in real-world contexts and emphasise the need to integrate different data sources to advance DSM research.

An integrated approach for cost-and emission optimal planning of coastal microgrid with demand-side management

In the realm of sustainable power systems, the pivotal role of demand-side management (DSM) in Microgrids (MGs) design and planning is increasingly recognized. This study accentuates the significance of DSM in improving operational efficiency, economic viability, and environmental sustainability of MGs, focusing on a remote community in the Gulf Al-Aqaba, Sinai Peninsula, Egypt. An innovative four-level approach is proposed for the techno-enviro-economic modelling, simulation, and optimization-based DSM of MGs, addressing the challenges posed by renewable energy integration and fluctuating electricity demands. The research explores three demand scenarios: a base load without DSM (SC-1), load shifting-based DSM (SC-2), and a combined load shifting/peak shaving DSM (SC-3), to demonstrate the adaptability and robustness of MGs under different conditions. The findings reveal significant improvements in MG performance, with peak load reduction from 73.66 kW in SC-1 to 50.82 kW in SC-2 and 44.82 kW in SC-3, highlighting the effectiveness of the applied DSM strategies. These strategies also yield economic benefits, evident in an 8% and 23% decrease in the total life cycle cost for hybrid and 100% renewable MG configurations under SC-2 and SC-3, respectively, compared to SC-1. Particularly noteworthy is the reduction in required capacities of key MG components in the hybrid MG scenario under SC-3, with reductions of 10% for solar photovoltaic, 33% for microturbine generator, and 40% for battery energy storage, implying cost savings and a more efficient MG setup. Additionally, the environmental impact is profound, with an 80.3% decrease in emissions for the hybrid MG setup under SC-3 compared to a standalone 50 kW MTG system under SC-1. This outcome highlights the potential of DSM in contributing to environmental sustainability, particularly in MG configurations involving renewable energy sources. In conclusion, the study provides comprehensive insights into the synergy between DSM and MG optimization, underscoring its essential role in addressing climate change and transitioning to sustainable energy systems.

Economic Model-Predictive Control of Building Heating Systems Using Backbone Energy System Modelling Framework

Accessing the demand-side management potential of the residential heating sector requires sophisticated control capable of predicting buildings’ response to changes in heating and cooling power, e.g., model-predictive control. However, while studies exploring its impacts both for individual buildings as well as energy markets exist, building-level control in large-scale energy system models has not been properly examined. In this work, we demonstrate the feasibility of the open-source energy system modelling framework Backbone for simplified model-predictive control of buildings, helping address the above-mentioned research gap. Hourly rolling horizon optimisations were performed to minimise the costs of flexible heating and cooling electricity consumption for a modern Finnish detached house and an apartment block with ground-to-water heat pump systems for the years 2015–2022. Compared to a baseline using a constant electricity price signal, optimisation with hourly spot electricity market prices resulted in 3.1–17.5% yearly cost savings depending on the simulated year, agreeing with comparable literature. Furthermore, the length of the optimisation horizon was not found to have a significant impact on the results beyond 36 h. Overall, the simplified model-predictive control was observed to behave rationally, lending credence to the integration of simplified building models within large-scale energy system modelling frameworks.

Decision support tool to determine the suitability of demand side management implementation in continuously operated processes – A biorefinery case study

AbstractThe time‐dependent adjustment of a system's power demand simultaneously with current power generation is commonly referred to as demand side management (DSM). DSM strategies are based on the flexibility to purchase electricity at times when prices are low, which can result in monetary benefits. One option to increase the flexibility of continuously operated processes is to oversize them. From an economic point of view, this leads to an increased investment. DSM only serves an economic purpose if the monetary benefits exceed this increase in capital costs. The main goal of this contribution is to develop a decision support tool to help evaluate unit operations regarding their feasibility for DSM implementation. In a case study, the decision support tool was applied to show its functionality on a biomethane production plant. The results show that with the help of the decision support tool, evaluating unit operations concerning their economic DSM potential is possible.

Artificial-Neural-Network-Based Autonomous Demand Response Controller for Thermostatically Controlled Loads

Thermostatically controlled loads (TCLs) possess an inherent potential for demand-side management (DSM). Space heating (SH) demands offer added flexibility due to their heat-storing capability and fast response times that may be unnoticed, but it has significant value for DSM. In this article, a communication-free demand response (DR) controller has been presented that harnesses the heat-storing capacity of residential buildings by utilizing TCLs. The proposed controller addresses customer voltage violations, comfort constraints, and energy savings. The DR controller attempts to control the TCLs by relying on voltage and voltage-to-load sensitivity. By deploying an artificial-neural-network-based model, the proposed control scheme ensures that the SH loads connected at spatially distributed nodes in the power system participate fairly to mitigate the residential grid voltage violations. Simulation results verify the proposed controller's performance to revamp the system voltage profiles while maintaining the desired comfort of end users. The controller is successfully tested with distributed generation integration, system reconfiguration, severe ambient temperature, and noise in the measured signals.

How flexible are energy flexibilities? Developing a flexibility score for revenue and risk analysis in industrial demand-side management

With rising and increasingly volatile energy prices, demand-side management (DSM) is becoming attractive within industry to optimize flexible electricity demand and to remain competitive. Despite economic and ecological benefits for companies, DSM implementation is not yet widespread. High effort in flexibility audits and complex optimization models to quantify DSM’s economic potentials represent initial barriers in practice, raising the question whether there is a simple way to analyze economic DSM potential as an initial indicator of successful DSM implementation that requires little data on flexibility characteristics. To address this need, this study develops a flexibility score that describes the degrees of freedom of individual energy flexibility measures (EFMs), i.e. how flexible a flexibility measure is. The flexibility score is tested and validated in a risk-return analysis on 46 real-world industrial EFMs from Germany optimized with integer linear programming (ILP). Analyzing Germany’s Day-Ahead and Intraday markets, the results show an increase in expected revenues and a simultaneous decrease in revenue risk with an increasing flexibility score, outlining DSM investments as attractive. Due to its ease of use, we see industrial companies, aggregators, energy service providers, and (energy) consultancy agencies as target users of the flexibility score. Policymakers can use the flexibility score to identify and design subsidies for energy flexibility investments.

Optimization of Energy Storage Systems and Demand Side Management to Maximize Water Utility Savings: A Hawaii Case Study

Abstract Energy conservation is a concern in many industries, and consequently, facility operators are turning to various efficiency measures or alternative power sources to reduce electricity costs. With the expanding use of intermittent resources, energy storage systems (ESSs) and demand side management (DSM) options are also gaining interest to maximize potential energy savings. Here, we study the potential of ESSs versus DSM for water utilities through a case study of the National Energy Laboratory of the Hawaii Authority (NELHA). NELHA is a multizone water utility in which most of its electricity usage is dedicated to pumping water. In this study, the optimization of the overall electricity charges for NELHA, using both ESSs or DSM via pump load shifting and optimization of pump house output is investigated. An optimization algorithm is created to determine the optimal size of the batteries for installation considering the water demand and energy costs in each zone. An extended approach of considering the characteristics of individual pumps on each pump house in the optimization model is applied to provide insight into the proper optimization framework for dispatching pumps depending on the current zonal load, given pump efficiencies, and maximum flowrates from each pump. The outcome from mathematical models using general quadratic pump efficiency functions and a simplified linear version of pump efficiency is compared to determine the significance of this difference in modeling methodology in estimations and evaluations. Additionally, the effect of increasing solar power on electricity purchased is analyzed. This work will help to establish the role of ESS and DSM in energy savings for water utility industry as well as show what methods should be used for evaluation of the potential of ESS and DSM interventions.

Assessing the demand side management potential in biofuel production; A theoretical study for biodiesel, bioethanol, and biomethane in Germany

AbstractMinimizing the emissions produced during the processing of biofuel, one aim is to reduce or completely replace the amount of the required fossil fuels used for internal process energy. For the transition of process energy from fossil to renewable energy sources, such as solar and wind, the energy demand of biomass processing must be adjustable to the fluctuating electricity supply. The flexible adjustment of a system's power demand to follow the current power generation is commonly referred to as demand side management (DSM). This contribution shows the results of a study on the implementation of DSM in biofuel biorefineries. By identifying reference concepts that could represent biofuel production plants, the specific mass and energy consumption for the individual process steps in these reference concepts was analyzed through a literature study. The annual throughput and energy consumption of process steps in biofuel production could then be calculated, enabling the identification of the most energy‐consuming process steps. Subsequently, possible flexible operating load ranges of the respective process steps in biofuel production were identified. These findings allowed an assessment of the potential for different process units of biorefinery systems concerning the quantitative adaptability of the electricity load – the theoretical DSM potential. An approximate theoretical DSM potential of 146 MW has been identified for biofuel production in Germany. This cumulated theoretical DSM potential in biofuel production was compared to that of other industrial processes, demonstrating the magnitude and importance of the implementation of DSM in biofuel production. © 2022 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

Systematic Review of Demand-Side Management Strategies in Power Systems of Developed and Developing Countries

Balancing electricity demand and supply remains a significant challenge for the power systems in developing countries, such as Nigeria. In Nigeria, there is a shortage of adequate power supply, and demand-side management (DSM) plays a minor role in the power balancing mechanism with load shedding being widely used. The paper aims to review and compare various existing and emerging DSM strategies in developing countries. An extensive and systematic review was conducted to evaluate potential solutions using DSM to increase the overall energy efficiency in the Nigerian electricity market. This study found that, although the technical and economic potentials of DSM vary in developed countries, the uptakes of DSM have been severely hampered hence preventing the full exploitation and utilisation of the full potential of DSM. The initiatives of a DSM model in Nigeria and other developing countries can play a significant role in addressing demand and supply challenges but an upgrade of the energy infrastructures, a reform of the market structure and the provision of financial incentives are required to allow for wide implementations of DSM strategies in developing countries.

Provision of Demand-Side Flexibility through the Integration of Power-to-Gas Technologies in an Electric Steel Mill

EAF steelmaking based on renewable electricity allows for low-CO2 steel production. However, the increased integration of volatile renewable energies into the energy system requires the provision of flexibility options. In view of the substantial oxygen consumption in the steel mill, flexible on-site generation and storage holds a significant potential for demand-side management. The utilization of by-product oxygen from an electrolysis plant not only contributes to load flexibility but also generates a climate-neutral fuel. In the present study, different process layouts are developed based on state-of-the-art technologies. The proposed supply systems for oxygen, hydrogen, and synthetic natural gas are subjected to design and operational optimization and assessed with respect to the overall demand-side flexibility, carbon dioxide emission reduction, and economic viability.

Evaluation of the financial benefits of a ground-source heat pump pool with demand side management: Is smart profitable for real estate?

• The profitability of smart electricity control for real estate owners. • The climate mitigation potential of demand side management. • An energy model for building heating using hourly-level data. • Power peak shaving of a heat pump pool. • Real estate owner motives. • New cash flows. Adoption of various smart control-compatible heating systems is increasing in the heating market. Simultaneously, smart electricity control, often referred to as demand side management (DSM), has raised interest as a core enabler of future sustainable cities. The technological viability of DSM is increasingly researched, but its profitability for real estate has remained unclear. This study examines the economics and environmental implications of DSM by analyzing an energy model using hourly-level energy consumption data in Finland. Accordingly, this study observes new cash flows generated after a daily 2-hour peak shaving of a ground-source heat pump pool in the Helsinki region. Although, DSM decreased the pool's peak electricity consumption, the economic potential of smartness was only 0.03 €/sqm/year, equaling 1% of savings in the energy costs. Furthermore, DSM generated surprisingly low (i.e., 0.02%) reduction in carbon emissions. Despite of the current minor benefits for the real estate owners in the Finnish power market, the end-user smart electricity control likely has a crucial role in the future electricity system with large quantities of intermittent renewable production. Thus, engaging real estate owners in DSM through alternative (monetary) incentives, and other strategic benefits, is essential to support the future energy system decarbonization.

Assessing the electric demand-side management potential of Helsinki's public service building stock in ancillary markets

• Feasibility assessment of demand respose in a Nordic building stock. • Ventilation fans are the most prominent electric ancillary market loads of buildings. • Upscaling demand response is limited by the inhomogeneity of buildings. With demand response (DR), a building may contribute to balancing the electric grid by amending its consumption according to the grid's momentary need. DR has its origin in industrial processes. As most buildings consume far less energy than industrial sites, several buildings must be bundled together for a comparable effect; however, because of the diversity among the buildings and their use, performing a realistic assessment of their DR potential is not a straightforward task. In this paper, the DR potential of a large group of buildings is assessed using a novel method based on construction time building codes. The method is applied to the public service building stock of the city of Helsinki, which comprises approximately one thousand buildings. The result is an estimate of the economic value generated in the ancillary demand-response market. This paper contributes to the academic society by being one of the first such assessments concerning buildings in northern climatic zones, where district heating and heating in general have predominance over chillers and cooling.

Flexibility analysis for demand-side management in large-scale chemical processes: An ethylene oxide production case study

The increasing generation of electricity from renewables requires the stabilization of the grid but also offers the opportunity to reduce operating costs for electricity consumers. Chemical processes are favorable participants of this energy evolution due to their localized, high electricity demands. Large-scale continuous processes that do not have electricity as a primary feedstock are not commonly utilized as consumers. However, coupling these processes with fast-responding upstream processes that employ electricity as major feedstock can offer great potential for demand-side management (DSM). This research work provides a framework to assess DSM potentials tested on the ethylene oxide production process. Complex process modeling and simulation were employed. The conventional flexibility analysis approach was rethought to simultaneously perform system flexibility assessment and operating window optimization. Moreover, the detection of critical parameters was possible, which can be exploited to increase process flexibility. This work sets the basis for a flexible DSM optimization procedure.

A probabilistically constrained extension to the generation expansion problem

This paper presents a probabilistic modeling approach to the generation expansion problem, where the energy manager of a firm aims at minimizing the investment costs of an energy park subject to the stochastic supply-demand balance constraint. We consider a reliability-based framework, where the energy manager determines robust generation expansion by imposing a probabilistic guarantee on the demand coverage distribution, specifying the required system reliability. We compare two solution methodologies to solve the probabilistically constrained generation expansion problem, i.e. (i) the sample approach and (ii) the sample average approximation. Applicability of the model is demonstrated in the use case, where the two renewable energy sources wind and solar technology are considered. We recover the energy manager's efficient frontier characterizing the optimal level of investment in renewable energy technologies as a function of the ex-ante imposed level of reliability, which quantifies the substitution rate of investment and reliability. The portfolio selection depends on the required reliability and is shifted towards a higher share in solar power when required reliability increases. Within the probabilistically constrained framework we demonstrate the potential of Demand Side Management in reducing capital expenditures. With increasing participation in DSM, the energy manager is able to reduce the necessary level of investment to obtain required reliability, thereby mitigating investment risks.

Simulation-based sensitivity analysis of an on-site hydrogen production unit in Hungary

This article examines the additional profit that can be achieved with the integrated operation of an on-site electrolyser, a hydrogen tank, a photovoltaic system, and a wind power plant based on Hungarian data from 2019. The results of the optimisation show that the system economically reduces the volatility of weather-dependent renewable production, so there is a promising demand-side management potential in coordination. We found that the operating profit is highest in April at EUR 19,416, 18,932 in July, and lowest at EUR 17,075 in January. The production curve of photovoltaic capacities is better matched to fuel demand, so increasing the share of solar energy results in lower balancing activity but higher profits. Increasing the size of the hydrogen storage and electrolyser, with constant hydrogen demand and prices, will cause a convergent increase in profits, however above a 10 kg storage capacity or 350 kW electrolyser capacity there is no substantial profit increase. In the case of the economically optimal asset size, there is a slight competition between the electricity market and the hydrogen distribution activity. The choice between the two activities depends on current electricity and hydrogen prices and the cost of unmet hydrogen demand.

Cost effective energy consumption in a residential building by implementing demand side management in the presence of different classes of power loads

ABSTRACT In the present scenario, in order to meet the growing electricity demand, demand side management (DSM) is one among the various approaches used in smart grid. By applying DSM at the customer side, various benefits such as reduction in electricity cost, reduction in peak demand, and improvement in load factor can be achieved. This paper proposes a new architecture, namely, Intelligent Universal Load Management System (IULMS) to implement DSM based on load shifting approach for a residential building in the presence of different classes of loads. In this work, the objective is to minimize the cost of electricity consumption and there are several constraints imposed by the device types operating in the system and it is solved by Binary Grey Wolf Optimization algorithm. The objective function is non-linear in nature because the price of electricity varies each hour. A real-time system involving residential building users of Agrini Apartment in Madurai, Tamilnadu, India is discussed. Further, the potential of DSM is analyzed. The minimization of electricity consumption cost, peak demand, and Peak to Average Ratio (PAR) are validated for each test case.

A Commercial Building Lighting Demand-Side Management through Passive Solar Design

The commercial sector that comprises of schools, libraries, public and private offices is the third largest energy-consuming sector in South Africa. Lighting is a significant contributor to the overall energy consumption in this sector. The aim of this study is to analyse the indoor daylight illuminance of a passive solar office building and the potential demand-side management. A passive solar building in SolarWatt Park, Alice South Africa was used as a case study. The indoor illuminance that includes electric and day lightings were monitored by two sets of Li-210R photometric sensors. Four cool white fluorescent fittings with each containing two 58W lamps served as the electric lights of the office inner space. The average illuminance of the office space with all electric lights on and without daylight was found to be 460 lux. The indoor average daylighting illuminance was 910 and 170 lux on a typical clear sky and overcast days, respectively. A daily cumulative energy savings of 11.14 kWh on a clear sky day and 0.47 kWh on an overcast day was achieved, assuming the office inner space illuminance was maintained at 300 lux. The monetary savings due to the energy saved was estimated at 1285.36 USD per annum. Based on the findings of the study, daylighting through passive solar design reduces energy consumption without compromising the visual comfort of the occupants. Integration of passive solar design for daylighting with indoor daylight switch controller is recommended for optimum energy savings.

Shifting landscapes: decoupled urban irrigation and greenness patterns during severe drought

Urban outdoor water conservation and efficiency offer high potential for demand-side management, but irrigation, greenness, and climate interlinks must be better understood to design optimal policies. To identify paired transitions during drought, we matched parcel-level water use data from smart, dedicated irrigation meters with high-spatial resolution, multispectral aerial imagery. We examined changes across 72 non-residential parcels using potable or recycled water for large landscape irrigation over four biennial summers (2010, 2012, 2014, and 2016) that encompassed a historic drought in California. We found that despite little change in irrigation levels during the first few years of the drought, parcel greenness deteriorated. Between summers 2010 and 2014, average parcel greenness decreased −61% for potable water irrigators and −56% for recycled water irrigators, providing evidence that vegetation could not reach its vigor from wetter, cooler years as the drought intensified with abnormally high temperatures. Between summers 2014–2016 as drought severity lessened, irrigation rates decreased significantly in line with high drought saliency, but greenness rebounded ubiquitously, on average +110% for potable water irrigators and +62% for recycled water irrigators, demonstrating climate-driven vegetation recovery as evaporation and plant evapotranspiration rates decreased. Transitions were similar for customers with both potable and recycled water; vegetation changes were dominated by the overarching climatic regime. As irrigation cannot always overcome drought conditions, which will become more severe under climate change, to maintain vegetation health, utilities and urban planners should consider the tradeoffs between providing green spaces and water scarcity. This includes evaluating the roles of climate-appropriate landscaping and adaptive reallocation of potable and recycled water resources to enhance water security. By addressing emerging themes in urban water management through analysis of data from forthcoming water metering and aerial imagery technologies, this research provides a unique perspective on water use, greenness, and drought linkages.

Demand side management in district heating networks: A real application

Demand side management is one of the strategies for an optimal management of DH networks. This consists in rescheduling the time the heating systems are switched on and off, or modifying their settings. In this way, the thermal request profile results as changed, with the following effects: 1) additional buildings can be connected to the network without installing new pipelines; 2) a better exploitation of renewable energy sources can be achieved; 3) a reduction of the heat produced by heat-only boilers is obtained. This work shows the potential of demand side management in DH networks in terms of thermal peak shaving. This is done by optimally rescheduling building heating systems. The best rescheduling is evaluated by means of a simulation tool. An experimental test performed on a distribution network shows that a peak reduction of about 5% can be achieved in case of strong limitations on the modifications. Simulations show that a relaxation of limitations leads to a reduction up to about 35% of peak request.