2,904 research outputs found
Consensus-based approach to peer-to-peer electricity markets with product differentiation
With the sustained deployment of distributed generation capacities and the
more proactive role of consumers, power systems and their operation are
drifting away from a conventional top-down hierarchical structure. Electricity
market structures, however, have not yet embraced that evolution. Respecting
the high-dimensional, distributed and dynamic nature of modern power systems
would translate to designing peer-to-peer markets or, at least, to using such
an underlying decentralized structure to enable a bottom-up approach to future
electricity markets. A peer-to-peer market structure based on a Multi-Bilateral
Economic Dispatch (MBED) formulation is introduced, allowing for
multi-bilateral trading with product differentiation, for instance based on
consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is
described to solve the MBED in fully decentralized manner. A set of realistic
case studies and their analysis allow us showing that such peer-to-peer market
structures can effectively yield market outcomes that are different from
centralized market structures and optimal in terms of respecting consumers
preferences while maximizing social welfare. Additionally, the RCI solving
approach allows for a fully decentralized market clearing which converges with
a negligible optimality gap, with a limited amount of information being shared.Comment: Accepted for publication in IEEE Transactions on Power System
Review of trends and targets of complex systems for power system optimization
Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107
Real Power Loss Reduction and Voltage Stability Enhancement by Stock Exchange, Product Demand-Availability, Affluent and Penurious Algorithms
In this paper, the Stock Exchange Algorithm (SEA), the Product Demand-Availability (PDA) algorithm, and the Affluent and Penurious (AP) algorithm are proposed to solve the power loss reduction problem. In the SEA approach, selling and buying shares in the stock exchange was imitated to design the algorithm. Stockholders are classified as Privileged, Average or Weak based on their fitness value. The PDA optimization algorithm is based on the consumer demand and availability of a product in the market. The Affluent and Penurious algorithm mimics the social behavior of people. The gap parameter (G) is defined to indicate the growing gap between affluent and penurious people when affluent people increase their wealth. The proposed Stock Exchange Algorithm, Product Demand-Availability optimization algorithm and the Affluent and Penurious optimization algorithm were tested in the IEEE 30 bus system. Real power loss minimization, voltage deviation minimization, and voltage stability index enhancement were successfully attained
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Transmission congestion management by optimal placement of FACTS devices
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 13/09/2010.This thesis describes the implementation of the Flexible AC Transmission Systems
(FACTS) devices to develop a market-based approach to the problem of transmission
congestion management in a Balancing Market. The causes, remedies and pricing
methods of transmission congestion are briefly reviewed.
Balancing Market exists in markets in which most of the trading is done via
decentralized bilateral contracts. In these markets only final adjustments necessary to
ensure secure system operation is carried out at a centralized Balancing Market. Each
market player can participate in the Balancing Market by submitting offers and bids to
increase and decrease its initially submitted active generation output. In this research a
method is proposed to reduce costs associated with congestion re-dispatch in a
Balancing Market by optimal placement of FACTS devices, and in particular Thyristor
Controlled Phase Shifter Transformers (TCPST).
The proposed technique is applicable to both Mixed Integer Linear Programming
(MILP) and Mixed Integer Non-Linear Programming (MINLP). In the MILP a power
system network is represented by a simplified DC power flow under a MILP structure
and the Market participants' offers and bids are also represented by linear models.
Results show that applications of FACTS devices can significantly reduce costs of
congestion re-dispatch. The application of the method based on the MINLP creates a
nonlinear and non-convex AC OPF problem that might be trapped in local sub-optima
solutions. The reliability of the solution that determines the optimal placement of
FACTS devices is an important issue and is carried out by investigation of alternative
solvers. The behavior of the MINLP solvers is presented and finally the best solvers for
this particular optimization problem are introduced.
The application of DC OPF is very common in industry. The accuracy of the DC OPF
results is investigated and a comparison between the DC and AC OPF is presented
Distributed Market Clearing Approach for Local Energy Trading in Transactive Market
This paper proposes a market clearing mechanism for energy trading in a local
transactive market, where each player can participate in the market as seller
or buyer and tries to maximize its welfare individually. Market players send
their demand and supply to a local data center, where clearing price is
determined to balance demand and supply. The topology of the grid and
associated network constraints are considered to compute a price signal in the
data center to keep the system secure by applying this signal to the
corresponding players. The proposed approach needs only the demanded/supplied
power by each player to reach global optimum which means that utility and cost
function parameters would remain private. Also, this approach uses distributed
method by applying local market clearing price as coordination information and
direct load flow (DLF) for power flow calculation saving computation resources
and making it suitable for online and automatic operation for a market with a
large number of players. The proposed method is tested on a market with 50
players and simulation results show that the convergence is guaranteed and the
proposed distributed method can reach the same result as conventional
centralized approach.Comment: Accepted paper. To appear in PESGM 2018, Portland, OR, 201
Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm
This paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature
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