Analyzing PJM&amp;#x2019;s economic demand response program

Walawalkar, Rahul; Blumsack, Seth; Apt, Jay; Fernands, Stephen

doi:10.1109/pes.2008.4596905

Cited by 14 publications

(15 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The DRP would receive an activation signal and should provide monitoring and verification data as determined in the contact. The "emergency interruptible load service" of ERCOT [25,26] and the "PJM emergency load response program" [27] are examples of this model. In this business model, incentives can be determined by negotiation or by a competitive auction for IL provision and can be in the form of electricity rate discounts or direct payments.…”

Section: Contract-based Reliability Enhancing Servicementioning

confidence: 99%

A review of demand side management business models in the electricity market

Behrangrad

2015

Renewable and Sustainable Energy Reviews

281

116

View full text Add to dashboard Cite

Section: Contract-based Reliability Enhancing Servicementioning

confidence: 99%

A review of demand side management business models in the electricity market

Behrangrad

2015

Renewable and Sustainable Energy Reviews

281

116

View full text Add to dashboard Cite

“…Meanwhile, DSM increases the utilization of generating capacities that would have been otherwise idle during off-peak hours, thus reducing the real cost of renewable integration [11]. The electricity supply side, load-reducing customers and non-load-reducing customers all benefit economically from load reductions [12]- [14]. The deregulation of electricity markets has also motivated more active DSM programs [15]- [19].…”

Section: Nomenclaturementioning

confidence: 99%

A comparison of day-ahead wholesale market: Social welfare vs industrial demand side management

Jiang

Farid

2015

2015 IEEE International Conference on Industrial Technology (ICIT)

View full text Add to dashboard Cite

The intermittent nature of renewable energy has been discussed in the context of the operational challenges that it brings to electrical grid reliability. In contrast, Demand Side Management (DSM) with its ability to allow customers to adjust electricity consumption in response to market signals has often been recognized as an efficient way to mitigate the variable effects of renewable energy. However, the industrial & academic literature have taken divergent approaches to DSM implementation. Academic studies often implement demand side management on the basis of a social welfare maximization. Meanwhile, industrial implementations minimize total system costs where customers are compensated for load reductions from a predefined baseline of electricity consumption that would have occurred without DSM. This paper rigorously compares these two different approaches in a day-ahead wholesale market context using the same system configuration and mathematical formalism. The comparison showed that a proper reconciliation between the dispatchable demand utility function and the load reduction cost function lead to fundamentally the same stochastic netload mitigation and the two DSM models generate the same dispatch results under specific conditions. However, while the social welfare model uses a stochastic net load composed of two terms, the industrial DSM model uses a stochastic net load composed of three terms, and is thus more prone to error and more likely requires more control activity in subsequent layers of enterprise control. NOMENCLATUREGC subscript for dispatchable (controllable) generators (e.g. thermal plants) GS subscript for stochastic generators (e.g. wind, solar photo-voltaic) DC subscript for dispatchable (controllable) demand units (i.e. participating in DSM) DS subscript for stochastic demand units (i.e. conventional load) i index of dispatchable generators j index of dispatchable demand unit k index of stochastic generators l index of stochastic demand unit t index of unit commitment time intervals N GC Number of dispatchable generators N DC Number of dispatchable demand units N GS Number of stochastic generators N DSNumber of stochastic demand units T Number of unit commitment time intervals P GCit dispatched power generation at the i th dispachable generator in the t th time interval P DCjt dispatched power consumption at the j th dispatchable demand unit in the t th time interval P DCjt forecasted power consumption of the j th dispatchable demand unit in the t th time interval P DCjt baseline power consumption of the j th dispatchable demand unit in the t th time interval P GSkt forecasted power generation at the k th stochastic generator in the t th time interval P DSlt forecasted power consumption of the l th stochastic demand unit in the t th time interval P GCi min. capacity of the i th dispatchable generator P DCj min. capacity of the j th dispatchable demand unit R GCi min. ramping capability of the i th dispatchable generator R DCj min. ramping capability of the j th dispatchable demand unit P...

show abstract

“…Traditionally, the market effect caused by demand side reduction in demand response program was evaluated only in economic DR program [7]. Economical effect of DR program is valued and used for determining incentive mechanism in economic DR program.…”

Section: Reliability Based Incentive Paymentmentioning

confidence: 99%

Reliability-based Incentive Mechanism for Demand Response in Electric Power Market

yoo¹,

Lee²,

Lee³

et al. 2011

Journal of International Council on Electrical Engineering

View full text Add to dashboard Cite

-DR(Demand response) is a rising issue in electricity power market by reducing load quantity instead of increasing generation for balancing demand and supply. DR resources are regarded as an extra tool of balancing supply and demand in emergency condition. DR resources usage in normal condition is also possible and used for the purpose of reliability and economic effect. For determining incentive for DR resources in PJM, fixed incentive level was used to reward the effect of market price reduction by DR program. However, since the fixed level of incentive is obtained by historical data, it cannot reflect the continuous change of market well. Furthermore, traditional method only concentrates to economic effect and it hardly concerns about the effect of preventing price variation by DR resources. In this paper, method of evaluating the market price reduction and prevention of price variation by DR is described under reliability considered situation. New mechanism for determining extra incentive is provided. From comparing the situation that DR is not implemented and the situation DR is implemented, novel mechanism can give more rewards to participants who contribute the stabilization of price and the reduction of load. Reward is exponentially increased as the DR resource stabilizes the price variation. On the other hand, reward is exponentially decreased as the DR resource increases price variation. Several cases are showed for checking effects and calculating the extra incentive.

show abstract

Analyzing PJM’s economic demand response program

Cited by 14 publications

References 4 publications

A review of demand side management business models in the electricity market

A review of demand side management business models in the electricity market

A comparison of day-ahead wholesale market: Social welfare vs industrial demand side management

Reliability-based Incentive Mechanism for Demand Response in Electric Power Market

Contact Info

Product

Resources

About