SCUC With Hourly Demand Response Considering Intertemporal Load Characteristics

2011 ◽  
Vol 2 (2) ◽  
pp. 564-571 ◽  
Author(s):  
Amin Khodaei ◽  
Mohammad Shahidehpour ◽  
Shaghayegh Bahramirad
Keyword(s):  
Demand Response ◽  
Unit Commitment ◽  
Operating Cost ◽  
Peak Load ◽  
Transmission Congestion ◽  
Market Prices ◽  
Carbon Footprints ◽  
Study Results ◽  
Load Characteristics ◽  
System Operating

In this paper, the hourly demand response (DR) is incorporated into security-constrained unit commitment (SCUC) for economic and security purposes. SCUC considers fixed and responsive loads. Unlike fixed hourly loads, responsive loads are modeled with their intertemporal characteristics. The responsive loads linked to hourly market prices can be curtailed or shifted to other operating hours. The study results show that DR could shave the peak load, reduce the system operating cost, reduce fuel consumptions and carbon footprints, and reduce the transmission congestion by reshaping the hourly load profile. Numerical simulations in this paper exhibit the effectiveness of the proposed approach.

scholarly journals Research on Energy Storage Optimization Operation Schedule in an Island System

2021 ◽  
Vol 11 (8) ◽  
pp. 3690
Author(s):  
Yu-Tung Chen ◽  
Cheng-Chien Kuo ◽  
Jia-Zhang Jhan
Keyword(s):  
Unit Commitment ◽  
Storage System ◽  
Operating Cost ◽  
Peak Load ◽  
Mixed Integer ◽  
Reserve Capacity ◽  
Load Case ◽  
Peak Shaving ◽  
Battery System ◽  
Island System

This paper proposes a 24-h ahead unit commitment for a diesel-photovoltaic (PV)-battery system using mixed-integer linear programming (MILP) to minimize the operating cost which includes the power storage system (PSS) in the reserve capacity. Considering the Kinmen island’s winter peak load case of 20MW, and summer peak load case of 60MW, a 24-h schedule for the diesel-PV-battery system island system for these two scenarios was optimized that allows the PSS to perform both as an additional reserve capacity and peak-shaving auxiliary device. The results show that the addition of PSS in the dispatch decision can allow the flexibility of the systems, especially in the reserve allocation, to up to twice the value of the PSS capacity. In this way, the PSS reduces the early startup and late shutdown of high-cost units while maintaining the system reserve, thereby, reducing the operating cost of the system.

Thermal Unit Commitment Problem with Wind Power and Energy Storage System

2013 ◽  
Vol 347-350 ◽  
pp. 1455-1461 ◽  
Author(s):  
Rui Wang ◽  
Yu Guang Xie ◽  
Kai Xie ◽  
Ya Qiao Luo
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Branch And Bound ◽  
Unit Commitment ◽  
Storage System ◽  
Operating Cost ◽  
Peak Load ◽  
Energy Storage System ◽  
Mixed Integer ◽  
Unit Commitment Problem

This paper presents a methodology for solving unit commitment (UC) problem for thermal units integrated with wind power and generalized energy storage system (ESS).The ESS is introduced to achieve peak load shaving and reduce the operating cost. The volatility of wind power is simulated by multiple scenarios, which are generated by Latin hypercube sampling. Meanwhile, the scenario reduction technique based on probability metric is introduced to reduce the number of scenarios so that the computational burden can be alleviated. The thermal UC problem with volatile wind power and ESS is transformed to a deterministic optimization which is formulated as the mixed-integer convex program optimized by branch and bound-interior point method. During the branch and bound process, the best first search and depth first search are combined to expedite the computation. The effectiveness of the proposed algorithm is demonstrated by a ten unit UC problem.

scholarly journals Optimal Operation Of Integrated Energy System Considering Demand Response

2021 ◽  
Vol 2087 (1) ◽  
pp. 012017
Author(s):  
Yan Liang ◽  
Yao Wang ◽  
Hongli Liu ◽  
Peng Wang ◽  
Yongming Jing ◽  
...  
Keyword(s):  
Demand Response ◽  
Operating Cost ◽  
Energy System ◽  
Optimal Operation ◽  
Adaptive Genetic Algorithm ◽  
Load Matching ◽  
Integrated Energy Systems ◽  
Cost Of Energy ◽  
Integrated Energy System ◽  
System Operating

Abstract Due to the high cost of energy storage part in traditional integrated energy systems, the demand response effect is poor. The paper proposes electrolytic water hydrogen production technology and applies it to the optimal operation of integrated energy system. By optimizing the operating cost of the system through adaptive genetic algorithm, we show that when the load matching degree was increased from 50% to 70%, the system operating cost was reduced by about 15.8%, and the carbon displacement was decreased by about 35%. System operating costs, carbon emissions, and the amount of electrolytic water systems involved in the demand response have all decreased.

scholarly journals Multi-Objective Based Optimal Energy Management of Grid-Connected Microgrid Considering Advanced Demand Response

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4142 ◽  
Author(s):  
Hyung-Joon Kim ◽  
Mun-Kyeom Kim
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Operating Cost ◽  
Peak Load ◽  
Management Approach ◽  
Solution Quality ◽  
Peak Period ◽  
Multi Objective ◽  
Optimal Energy ◽  
Optimal Energy Management

This paper proposes an optimal energy management approach for a grid-connected microgrid (MG) by considering the demand response (DR). The multi-objective optimization framework involves minimizing the operating cost and maximizing the utility benefit. The proposed approach combines confidence-based velocity-controlled particle swarm optimization (CVCPSO) (i.e., PSO with an added confidence term and modified inertia weight and acceleration parameters), with a fuzzy-clustering technique to find the best compromise operating solution for the MG operator. Furthermore, a confidence-based incentive DR (CBIDR) strategy was adopted, which pays different incentives in different periods to attract more DR participants during the peak period and thus ensure the reliability of the MG under the peak load. In addition, the peak load shaving factor (PLSF) was employed to show that the reliability of the peak load had improved. The applicability and effectiveness of the proposed approach were verified by conducting simulations at two different scales of MG test systems. The results confirm that the proposed approach not only enhances the MG system peak load reliability, but also facilitates economical operation with better performance in terms of solution quality and diversity.

Demand Response and FERC Mandated Compensation Issues

2012 ◽  
Author(s):  
Donald Lincoln
Keyword(s):  
Energy Efficiency ◽  
Demand Response ◽  
Market Competition ◽  
Peak Load ◽  
Market Price ◽  
Energy Markets ◽  
Local Market ◽  
Wholesale Market ◽  
Market Prices ◽  
Demand Response Programs

This paper describes a Demand Response (DR) pilot event performed at Sandia National Laboratories in August of 2011. This paper includes a description of the planning for the demand response event, sources of energy reduction during the event, the potential financial benefit to Sandia National Laboratories from the event, event implementation issues, and the event results. In addition, this paper presents the implications of the Federal Energy Regulatory Commission (FERC) Order 745, Demand Response Compensation in Organized Wholesale Energy Markets, issued in March 2011. In this order FERC mandates that demand response suppliers must be compensated by the organized wholesale energy markets at the local market price for electricity during the hour the demand response is performed. Energy management in a commercial facility can be segregated into energy efficiency and demand response. Energy efficiency focuses on steady state load minimization. Demand response reduces load for event-driven periods during the peak load. Commercial facility demand response refers to voluntary actions by customers that change their consumption of electric power in response to price signals, incentives, or directions from grid operators at times of high wholesale market prices or when electric system reliability is jeopardized. Demand-response-driven changes in electricity use are designed to be short-term and centered on critical hours during the day when demand is high or when the electricity supplier’s reserve margins are low. Demand response events are typically scheduled between 12:00 p.m. and 7:00 p.m. on eight to 15 days during the hottest period of the year. Analysis has determined that automated demand response programs are more efficient and effective than manually controlled demand response programs due to persistence. FERC has stated that their Order 745 ensures organized wholesale energy market competition and removes barriers to the participation of demand response resources. In Order 745, FERC also directed that the demand response compensation costs be allocated among those customers who benefit from the lower prices for energy resulting from the demand response. FERC has allowed the organized wholesale energy markets to establish details for implementation methods for demand response compensation over the next four years following the final Order issue date. This compensation to suppliers of demand response can be significant since demand response is typically performed during those hours when the wholesale market prices are at their highest levels during the year.

scholarly journals Assessing the Value of Demand Response in Microgrids

2021 ◽  
Vol 13 (11) ◽  
pp. 5848
Author(s):  
Isaías Gomes ◽  
Rui Melicio ◽  
Victor M. F. Mendes
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Energy Storage ◽  
Case Studies ◽  
Demand Response ◽  
Storage Systems ◽  
Computer Application ◽  
Market Prices ◽  
Proper Formulation ◽  
Operation Case

This paper presents a computer application to assist in decisions about sustainability enhancement due to the effect of shifting demand from less favorable periods to periods that are more convenient for the operation of a microgrid. Specifically, assessing how the decisions affect the economic participation of the aggregating agent of the microgrid bidding in an electricity day-ahead market. The aggregating agent must manage microturbines, wind systems, photovoltaic systems, energy storage systems, and loads, facing load uncertainty and further uncertainties due to the use of renewable sources of energy and participation in the day-ahead market. These uncertainties cannot be removed from the decision making, and, therefore, require proper formulation, and the proposed approach customizes a stochastic programming problem for this operation. Case studies show that under these uncertainties and the shifting of demand to convenient periods, there are opportunities to make decisions that lead to significant enhancements of the expected profit. These enhancements are due to better bidding in the day-ahead market and shifting energy consumption in periods of favorable market prices for exporting energy. Through the case studies it is concluded that the proposed approach is useful for the operation of a microgrid.

Energy management of a microgrid using demand response strategy including renewable uncertainties

2021 ◽  
Vol 22 (1) ◽  
pp. 85-100
Author(s):  
Suchitra Dayalan ◽  
Rajarajeswari Rathinam
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Demand Response ◽  
Effective Means ◽  
Operating Cost ◽  
Energy Resources ◽  
Response Strategy ◽  
Distributed Energy ◽  
Real Time Control ◽  
Minimum Operating

Abstract Microgrid is an effective means of integrating multiple energy sources of distributed energy to improve the economy, stability and security of the energy systems. A typical microgrid consists of Renewable Energy Source (RES), Controllable Thermal Units (CTU), Energy Storage System (ESS), interruptible and uninterruptible loads. From the perspective of the generation, the microgrid should be operated at the minimum operating cost, whereas from the perspective of demand, the energy cost imposed on the consumer should be minimum. The main key in controlling the relationship of microgrid with the utility grid is managing the demand. An Energy Management System (EMS) is required to have real time control over the demand and the Distributed Energy Resources (DER). Demand Side Management (DSM) assesses the actual demand in the microgrid to integrate different energy resources distributed within the grid. With these motivations towards the operation of a microgrid and also to achieve the objective of minimizing the total expected operating cost, the DER schedules are optimized for meeting the loads. Demand Response (DR) a part of DSM is integrated with MG islanded mode operation by using Time of Use (TOU) and Real Time Pricing (RTP) procedures. Both TOU and RTP are used for shifting the controllable loads. RES is used for generator side cost reduction and load shifting using DR performs the load side control by reducing the peak to average ratio. Four different cases with and without the PV, wind uncertainties and ESS are analyzed with Demand Response and Unitcommittment (DRUC) strategy. The Strawberry (SBY) algorithm is used for obtaining the minimum operating cost and to achieve better energy management of the Microgrid.

scholarly journals Price Based Demand Response for Optimal Frequency Stabilization in ORC Solar Thermal Based Isolated Hybrid Microgrid under Salp Swarm Technique

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2209
Author(s):  
Abdul Latif ◽  
Manidipa Paul ◽  
Dulal Chandra Das ◽  
S. M. Suhail Hussain ◽  
Taha Selim Ustun
Keyword(s):  
Demand Response ◽  
Frequency Control ◽  
Thermal Power ◽  
Peak Load ◽  
Energy System ◽  
Frequency Stabilization ◽  
Load Frequency Control ◽  
Solar Thermal ◽  
Proportional Integral ◽  
Hybrid Microgrid

Smart grid technology enables active participation of the consumers to reschedule their energy consumption through demand response (DR). The price-based program in demand response indirectly induces consumers to dynamically vary their energy use patterns following different electricity prices. In this paper, a real-time price (RTP)-based demand response scheme is proposed for thermostatically controllable loads (TCLs) that contribute to a large portion of residential loads, such as air conditioners, refrigerators and heaters. Wind turbine generator (WTG) systems, solar thermal power systems (STPSs), diesel engine generators (DEGs), fuel cells (FCs) and aqua electrolyzers (AEs) are employed in a hybrid microgrid system to investigate the contribution of price-based demand response (PBDR) in frequency control. Simulation results show that the load frequency control scheme with dynamic PBDR improves the system’s stability and encourages economic operation of the system at both the consumer and generation level. Performance comparison of the genetic algorithm (GA) and salp swarm algorithm (SSA)-based controllers (proportional-integral (PI) or proportional integral derivative (PID)) is performed, and the hybrid energy system model with demand response shows the supremacy of SSA in terms of minimization of peak load and enhanced frequency stabilization of the system.

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