Multiple DRPs to maximise the techno-economic benefits of the distribution network

This study addresses a demand response programme (DRP) model considering the price elasticity of demand to determine the peak scheduling for different categories of consumers with the possibility of load shifting. The main objective is to minimise daily energy loss and improvement in the node voltage profile of distribution system along with the economic benefits of different stakeholders. The proposed work helps in appropriate selection of DRP for different feeders/consumers. The investigations are performed on a benchmark 33-bus test distribution system and comprehensive analysis is illustrated through simulation results

A Bi-level Decision Framework for Incentive-Based Demand Response in Distribution Systems

In a growing retail electricity market, demand response (DR) is becoming an integral part of the system to enhance economic and operational performances. This is rendered as incentive-based DR (IBDR) in the proposed study. It presents a bi-level decision framework under the ambit of multiple demand response providers (DRPs) in the retail competition. It is formulated as a multi-leader-multi-follower game, where multiple DRPs, as the DR stakeholders, are strategically interacting to optimize load serving entity cost at the upper level, and individual DRP as the aggregated customers is optimizing its cost at the lower level. The strategic behavior of DRPs is modeled in a game-theoretic framework using a generalized Stackelberg game. Further, the existence and uniqueness of the game are validated using variational inequalities. It is presented as a nonlinear problem to consider AC network constraints. An equilibrium problem with equilibrium constraints is used as a mathematical program to model the multi-leader-multi-follower, bi-level problem, which is simultaneously solved for all DRPs. The diagonalization method is employed to solve the problem. The detailed numerical analyses are conducted on IEEE 33-bus test and Indian-108 bus distribution systems to demonstrate the applicability and scalability of the proposed model and the suggested method.Comment: IEEE Transactions on Energy Markets, Policy and Regulatio

Reliability and Network Performance Enhancement by Reconfiguring Underground Distribution Systems

Contemporary distributions are now going to underground their overhead distribution lines due to techno-social reasons. Reliability and loss reduction are the two prime objectives for distribution system operation. Since failure rates of ungrounded cables are the function of Joules heating besides their physical lengths, the reliability evaluation of undergrounded distribution systems needs to be reviewed. This paper suggested a suitable modification in existing reliability indices in order to make them more appropriate for underground distribution systems. A multi-objective network reconfiguration problem is formulated to enhance the reliability and performance of distribution systems while duly addressing the variability and uncertainty in load demand and power generation from renewables. The application results on a standard test bench shift the paradigm of the well-known conflicting nature of reliability and network performance indices defined for overhead distribution systems

Multi-area environmental economic dispatch with reserve constraints using enhanced particle swarm optimization

In this paper, the multi-area environmental economic dispatch (MAEED) problem with reserve constraints is solved by proposing an enhanced particle swarm optimization (EPSO) method. The objective of MAEED problem is to determine the optimal generating schedule of thermal units and inter-area power transactions in such a way that total fuel cost and emission are simultaneously optimized while satisfying tie-line, reserve, and other operational constraints. The spinning reserve requirements for reserve-sharing provisions are investigated by considering contingency and pooling spinning reserves. The control equation of the particle swarm optimization (PSO) is modified by improving the cognitive component of the particle's velocity using a new concept of a preceding experience. In addition, the operators of PSO are dynamically controlled to maintain a better balance between cognitive and social behavior of the swarm. The effectiveness of the proposed EPSO has been investigated on four areas, 16 generators and four areas, 40 generators test systems. The application results show that EPSO is very promising to solve the MAEED problem.http://www.tandfonline.com/loi/uemp202016-08-31hb2016Electrical, Electronic and Computer Engineerin