DSM Techniques and Strategies
- Load shifting: Time-of-use pricing, peak shaving, and valley filling
- Demand response: Direct load control, dynamic pricing, and incentive programs
- Energy conservation: Efficiency measures and behavioural changes
Load shifting involves changing the demand for loads from peak hours to off-peak hours by applying filling and clipping strategies. The TOU and storage devices are used in this method with a constant level of total energy consumption.
Demand response: Reduction of peak demand and system load variability is a significant objective of Demand-Side Management (DSM) programs. DSM aims to mitigate the impact of high-demand periods, balance energy supply and demand, and enhance grid stability by actively handling and modifying consumer energy consumption patterns. Here are key approaches employed in DSM to achieve peak demand reduction and load variability management:
- Time-of-Use (TOU) Pricing: Utilities implement time-varying pricing structures, where electricity rates are higher during peak demand periods and lower during off-peak periods.
Consumers are encouraged to shift their energy usage to off-peak hours when electricity rates are lower, reducing demand during peak times.
- Critical Peak Pricing (CPP): CPP involves higher electricity rates during specific critical peak periods when demand is exceptionally high or grid conditions are strained.
Consumers are provided with advance notifications, and those who can curtail their electricity usage during critical peak events receive financial incentives or lower rates.
- Peak Load Shaving: Utilities and consumers collaborate to actively reduce electricity demand during peak periods to avoid grid overload and potential blackouts.
Techniques such as load shifting, where non-essential energy consumption is temporarily postponed or shifted to off-peak hours, are employed.
- Demand Response (DR) Programs: DR programs enable utilities to request voluntary or automated reduction of electricity consumption from consumers during times of high demand.
Consumers may receive signals or incentives to curtail energy usage, adjust thermostat settings, or temporarily limit operation of certain appliances.
- Load Control and Energy Management Systems: Utilities and consumers deploy load control and energy management systems to optimize energy usage based on grid conditions and demand forecasts.
These systems enable automated control or scheduling of energy-intensive processes, appliances, or equipment to reduce peak demand.
- Energy Storage Integration: The integration of energy storage technologies, such as batteries, allows excess electricity to be stored during off-peak periods and discharged during peak demand, reducing strain on the grid.
Stored energy can be utilized to meet peak demand or provide ancillary grid services to enhance grid reliability.
DSM initiatives help flatten the demand curve, reduce peak loads, and manage load variability by implementing these strategies and programs. These efforts result in a more stable and efficient grid, avoiding the need for costly infrastructure upgrades and improving overall grid resilience. Also, the reduction of peak demand supports the integration of renewable energy sources and contributes to environmental sustainability by minimizing the reliance on fossil fuel-based power generation during high-demand periods.
Customers’ energy expenses are reduced through demand response, an optional alteration to the load pattern in response to a change in the electricity tariff. However, it may create inconvenience during appliance waiting periods. Price-based and incentive-based DR policies are the two categories. The split and subdivision of the incentive-based DR are shown in Fig. 2.
Impact of DSM on Grid Operations
The impact of DSM on grid operations is reviewed from the perspectives of the electricity market, system load variability, environment and power system operation and reliability.
- Reduction of peak demand and system load variability: From FY17 to FY20, the peak demand grew from 10.6 GW to 14.3 GW i.e., 34.9%. It is estimated that peak demand grows by 38.3 % from 13.17 GW in FY 21 to 18.22 GW in FY25. The estimated peak demand in FY 30 is 24.85 GW.
- Enhancement of grid reliability and stability: The analysis of power system reliability is divided into three Hierarchical Levels (HLs). HL1 involves the analysis of the generation facility, HL2 considers the analysis of the generation and transmission facilities and HL3 considers the analysis of an additional distribution facility. Only HL1 and HL2 studies are regularly performed given that complete HL3 studies are highly complex because of their large problem scale. Thus, the distribution network is normally analysed individually and separately from the generation and transmission systems.
- Integration of renewable energy sources: Many studies have assessed the intermittency of renewable energy sources either at the supply side as bulk units or at the demand-side as medium units. DSM has been used to integrate the growing number of renewable energy sources in Portugal.
Economic Implications of DSM
Economic implications of Demand-Side Management (DSM) programs comprehend both costs and benefits for consumers, utilities, and society as a whole. Here are some key economic considerations related to DSM:
- Cost Savings for Consumers: DSM programs can lead to straight cost savings for consumers by reducing their energy bills. Consumers can lower their electricity consumption and shift usage to lower-cost periods through energy efficiency measures and load management strategies.
Time-Of-Use (TOU) pricing and dynamic pricing structures allow consumers to adjust their energy usage patterns to take advantage of off-peak rates, resulting in potential cost savings.
- Reduced Infrastructure Costs for Utilities: Load reduction during peak periods helps alleviate stress on the grid, reducing the need for grid expansion.
Utilities can avoid or defer costly investments in new power generation plants, transmission lines, and distribution infrastructure by actively managing and optimizing demand.
Challenges and Limitations
Executing Demand-Side Management (DSM) programs several technical and infrastructural barriers may hinder their effective deployment. These barriers can vary depending on characteristics of the electricity grid. Here are some common technical and infrastructural challenges associated with DSM implementation:
- Outdated Metering Infrastructure: Legacy metering systems lacking advanced metering capabilities can pose challenges in collecting accurate and timely consumption data required for effective DSM programs.
Upgrading to Advanced Metering Infrastructure (AMI), such as smart meters, may be necessary to enable real-time monitoring and communication between utilities and consumers.
- Communication and Data Management: Establishing vigorous communication networks and data management systems is crucial for effective DSM implementation. Reliable communication channels are required to exchange information, relay price signals, and coordinate demand response actions between utilities and consumers.
- Limited Grid Flexibility: To accommodate variable or reduced demand resulting from DSM measures some electricity grids may have limited flexibility.
Aging infrastructure, transmission constraints, or inadequate distribution systems can limit the grid’s ability to effectively manage load fluctuations and integrate demand response actions.
- Technical Compatibility and Interoperability: Ensuring compatibility and interoperability among various DSM technologies and systems can be challenging.
Integration of different energy management systems, smart devices, and control platforms may require standardization efforts to enable seamless communication and coordination.
- Lack of Consumer Awareness and Engagement: Low consumer awareness and engagement can impede the successful adoption of DSM programs.
Educating consumers about the benefits, incentives, and behavioural changes associated with DSM is essential for achieving meaningful participation and energy conservation.
Technical and infrastructural barriers to DSM implementation.
Emerging Trends and Future Directions
- Smart grid technologies and their impact on DSM: Smart grid technologies play a crucial role in enabling and enhancing the implementation of Demand-Side Management (DSM) programs. These advanced technologies provide real-time data, automation capabilities, and improved communication between utilities and consumers. Here are some key smart grid technologies and their impact on DSM:
- Advanced Metering Infrastructure (AMI): AMI, including smart meters, enables two-way communication between utilities and consumers, facilitating real-time monitoring and data exchange.
Smart meters provide detailed information on energy consumption patterns, load profiling, enabling more accurate billing and identification of energy-saving opportunities.
With AMI, utilities can implement Time-Of-Use (TOU) pricing, Critical Peak Pricing (CPP), and other dynamic pricing structures to encourage load shifting and demand response.
- Home Energy Management Systems (HEMS): HEMS provide real-time energy usage information, enabling consumers to make up-to-date decisions and adjust their energy consumption patterns.
Consumers can set energy-saving preferences, receive energy usage alerts, and remotely control appliances, optimizing their participation in DSM programs.
The integration of these smart grid technologies like real-time data, automation, and improved communication enable more precise load monitoring, accurate billing, consumer engagement, and integration of demand response actions. These technologies empower consumers to actively participate in energy management and enable utilities to optimize grid operations, reduce peak demand, and improve overall system efficiency, reliability and stability.
- Policy and regulatory considerations for advancing DSM: Advancing Demand-Side Management (DSM) requires supportive policy and regulatory frameworks that incentivize and facilitate the implementation of DSM programs. Here are (below) some key policy and regulatory considerations to promote and accelerate the adoption of DSM.
- Tariff Structures and Pricing Mechanisms: To implement time-of-use (TOU) pricing and dynamic pricing structures that reflect the actual cost of electricity production and encourage load shifting and demand response.
Provide incentives to consumers who participate in DSM programs or reduce their peak demand.
- Performance-Based Regulation: Implement performance-based regulations that reward utilities for achieving energy efficiency targets and reducing overall system peak demand.
Establish mechanisms that allow utilities to recover costs associated with DSM program investments and performance incentives.
- Energy Efficiency Standards and Targets: Set energy efficiency standards and targets for various sectors, including buildings, appliances, and industrial processes, to drive energy conservation and encourage DSM measures.
Provide financial incentives, rebates, or tax credits for energy-efficient upgrades and technologies to incentivize consumers and businesses to adopt DSM practices.
- Demand Response Programs and Standards: Develop and promote demand response programs that allow utilities to request load reductions from consumers during peak demand periods.
Establish standards and guidelines for demand response participation, ensuring consistency, transparency, and reliability across different market participants.
- Data Privacy and Security: Establish clear guidelines and regulations to protect consumer data privacy and ensure the secure handling of energy usage data collected for DSM purposes.
Define data access and sharing protocols to enable effective coordination between utilities, third-party aggregators, and technology providers.
- Grid Interconnection and Integration: Streamline the process of grid interconnection for Distributed Energy Resources (DERs), such as rooftop solar, energy storage, and demand response resources.
Develop technical standards and protocols to facilitate the seamless integration of DSM technologies with the existing grid infrastructure.
- Consumer Engagement and Education: Develop public awareness campaigns and educational programs to inform and engage consumers about the benefits of DSM and energy conservation.
Provide resources and tools to help consumers understand their energy usage, participate in DSM programs, and make informed decisions about energy efficiency upgrades.
- Utility Business Models and Incentives: Align utility business models and financial incentives with DSM objectives to encourage utilities to invest in energy efficiency and demand reduction measures.
Consider performance-based regulation, revenue decoupling, or revenue-sharing mechanisms that reward utilities for achieving DSM targets and delivering energy savings.
Effective policy and regulatory frameworks can provide the necessary incentives, support, and guidelines to accelerate the deployment of DSM programs. By creating an enabling environment, policymakers and regulators can encourage utilities, consumers, and other stakeholders to actively participate in DSM, leading to energy savings, grid optimization, and a more sustainable energy future.
Conclusion
By presenting a comprehensive overview of DSM in the grid, this review article aims to reveal that significant research works have been done to reduce energy bill, minimize the PAR of load curve, and maximize benefits for utilities and savings for consumers. However, the existing techniques lack the capability of entirely considering the user satisfaction while deploying TOU, especially for low-income consumers in economically challenged countries. Furthermore, in case of incline block tariff, the block size needs to be appropriately determined to ensure financial benefits for both consumers and utilities.
It will also contribute to the present pool of knowledge by insights for researchers, policymakers, and industry professionals in energy management and sustainability.
Concluded
Shibna Hussain is pursuing PhD in Dept. of Renewable Energy, RTU Kota. Her research area is Smart Grid Management System.
Dr. Santosh Kumar Sharma is working as an Assistant Professor in Electrical Engg. Dept., Rajasthan Technical University, Kota. He did his PhD from RTU kota. His research areas are power system analysis, PV system, micro grid and renewable energy assessment.
Dr. Shiv Lal is Associate Professor in Mechanical engineering department, Rajasthan Technical University Kota, India. He did his PhD degree from IIT Delhi and holds expertise in energy assessment, buildings passive heating and cooling, energy and exergy analysis, solar chimney power plant, renewable energy, design of thermal systems, heat transfer, IC engine, solar refrigeration etc.
