Demand Response In Electricity Market Research Articles

Optimal Reactive Power Dispatch and Demand Response in Electricity Market Using Multi-Objective Grasshopper Optimization Algorithm

Optimal Reactive Power Dispatch (ORPD) is a power system optimization tool that modifies system control variables such as bus voltage and transformer tap settings, and it compensates devices’ Volt Ampere Reactive (VAR) output. It is used to decrease real power loss, enhance the voltage profile, and promote stability. Furthermore, several issues have been faced in electricity markets, such as price volatility, transmission line congestion, and an increase in the cost of electricity during peak hours. Programs such as demand response (DR) provide system operators with more control over how small customers participate in lowering peak-hour energy prices and demand. This paper presents an extensive study on ORPD methodologies and DR programs for lowering voltage deviation, limiting cost, and minimizing power losses to create effective and economical operations systems. The main objectives of this work are to minimize costs and losses in the system and reduce voltage variation. The Grasshopper Optimization Algorithm (GOA) and Dragonfly Algorithm (DA) have been implemented successfully to solve this problem. The proposed technique has been evaluated by using the IEEE-30 bus system. The results obtained by the implementation of demand response systems show a considerable reduction in costs and load demands that benefit consumers through DR considerations. The results obtained from the GOA and DA are compared with those generated by other researchers and published in the literature to ascertain the algorithm’s efficiency.

A robust optimization framework for energy management of CCHP users with integrated demand response in electricity market

Micro-energy grid for CCHP users can make full use of local renewable energy and integrated demand response (IDR) resources to meet the electric, cooling, heating and other load demands in electricity market. In this paper, aiming at the uncertainties of renewable energy output and electric, cooling and heating load in micro-energy grid, a mode of IDR resources flexibly participating in day-ahead scheduling and intra-day real-time regulation stage in micro-energy grid is established, and a two-stage robust scheduling optimization model with IDR considered is constructed. In the model, the cost and constraints of IDR resources participating in two-stages is considered, and the uncertain budget parameter is introduced for regulating economy and robustness of the system. In day-ahead stage, the day-ahead scheduling cost is taken as the goal to determine the output of each unit, energy storage and IDR resource response mode. Based on the optimization results of day-ahead stage, each regulation quantity of the system is determined with the goal of minimizing the real-time regulation cost within a day. Strong duality theory and column constraint generation algorithm is used to transform and solve the robust optimization problem of min–max-min structure. The results show that the robust optimization model can improve the system's ability to resist uncertain risks, and the integrated demand response can improve the economy of the robust optimization model and the self-sufficiency of micro-energy grid.

Impacts of joint operation of wind power with electric vehicles and demand response in electricity market

This paper investigates the impacts of joint operation of wind power producers (WPPs) with electric vehicles (EVs) and demand response (DR) resources as a virtual power plant (VPP) in electricity markets. In particular, this paper aims at answering the question of whether these resources have incentives to voluntarily form a VPP to participate in the electricity market. For this purposes, two stochastic multi-period game models of the day-ahead (DA) electricity market are proposed based on the oligopolistic competition theory. The first model considers when the WPP, EV aggregator (EVA), and DR aggregator (DRA) form a VPP and bid in the DA market in a cooperative way, and the Shapley value method is applied to allocate the VPP's profit among the WPP, EVA and DRA; while the second model focuses on when they bid in the DA market in a non-cooperative way. In both models, the scenario generation and reduction technique is employed to simulate wind speed uncertainties, and a deviation penalty mechanism is applied when the WPP's actual output deviate from its cleared quantity in the market. In addition, the conditional value-at-risk (CVaR) is used to measure financial risks of the WPP and analyze its risk preference. Numerical examples show that the VPP mode can help the WPP to reduce its deviation between its actual output and cleared quantity and improve its competitiveness in the market. In addition, individual profits of the WPP, EVA and DRA will all increase in the VPP mode, which means that the WPP, EVA and DRA have high incentives to voluntarily form a VPP and participate in the electricity market.

Practices and Enlightenment of Domestic and Foreign Demand Response in Electricity Market

With the increasing proportion of intermittent power supplies and large capacity generator set, demand response based on excitation and price is widely concerned for improving the flexibility of system operation scheduling. The development of demand response in the electricity market is in the ascendant in the world, and the market mechanism can be better designed by fully drawing on existing experience. This paper comprehensively analyses the released relevant policies, technical standards and implementation of existing pilot projects of domestic and foreign demand response in electricity market, summarizing the research focus in recent years, learning the experience of the existing demand response project and combining the current situation of the power market revolution, then put forward some suggestions to develop the mechanism of demand response in electricity market.

행위자기반모형을 이용한 선택적 전력요금제의 전력요금 절감효과 분석

우리나라 전력시장에서도 보다 선진화된 요금체계가 도입되어야 한다는 관점에서 가정부문에서의 선택적 전력요금제 도입이 논의되고 있다. 본 연구에서는 고정요금제, 실시간 요금제(RTP), 계시별 요금제(TOU)를 도입하였을 때의 효과를 분석하기 위해 행위자기반모형을 구축하였다. 시간대별 전력소비 유형이 다른 행위자를 설정하였으며, 전력수요와 전력가격을 연동시키기 위해 발전부문도 모형에 도입하였다. 분석 결과, 소비자 유형이 피크부하 때 덜 사용하는 경우에는 실시간 요금제인 RTP나 TOU를 택했을 때의 비용절감 효과가 컸으며, 특히 스마트 계량기 등을 이용하여 전력사용 시간을 최적화할 수 있는 경우에는 그 편익이 더욱 증가한 것으로 나타나 향후 스마트 전력소비를 위한 인프라 구축이 필요함을 알 수 있다. There are growing interests in the introduction of consumer's selective electricity tariff systems in order to enhance demand response in electricity market in Korea. Real time pricing (RTP) and Time of Use (TOU) are typical examples of demand response system through which electricity price is linked to real time demand. This paper adopts an agent-based model to analyze the effects of such demand system on the counsumers' electricity costs. The result shows that real time pricing system is effective to reduce electricity costs of consumers by providing more flexible tariff system, depending on each consumer's demand pattern. This finding could be used as a basis for supporting smart grid system in the presence of responsive demand environment.

The study of CPP programs based on logarithmic model in electricity markets

Providing a suitable model for demand response programs (DRPs) in electricity market is a very important factor. In this regard considerable efforts have been carried out to model demand response in electricity market. By using DRPs some technical and economical characteristic of power system are improved. The DRPs are divided into two categories which are priced-based and incentive-based demand response programs. This paper presents a logarithmic modeling of critical peak pricing programs (CPP) as most prevalent priced-based DRPs. In this way, nonlinear behavioral characteristic of elastic loads is considered which causes to more realistic modeling of demand response to CPP rates. Numerical analysis on the load profile of the peak day of the Iranian power system in 2007 is conducted to examine the proposed model. Hence, different scenarios have also been considered. The results reveal the good performance of proposed models. The results are carried out by using MATLAB software. Keywords: Demand Response programs, Elasticity, Critical peak pricing programs, Electricity market, Iran