Impact of renewable energy sources on modelling of bidding strategy in a competitive electricity market using improved whale optimization algorithm

Abstract

In a competitive power market, generating utilities can be enhanced to achieve maximum profit by implementing a process of bidding strategy. Now‐a‐days renewable sources like solar and wind have become better alternatives significantly than other sources prior to power generation. These sources have extensive utilisation day‐by‐day in power sector and their impact in developing precise bidding strategies is getting more challenging aspect in the market. Since these renewable sources possess intermittent nature and undergo many uncertainties, the generating utilities encounter an unavoidable problem. Taking these aspects into consideration, attempts have been made using improved whale optimization algorithm to make the bidding strategy model for maximizing the power supplier's profit. Weibull and Beta distribution functions are used for modelling the stochastic characteristics of wind‐speed profile and solar‐irradiation, respectively. The proposed technique is tested and clarified with an IEEE‐30, IEEE‐57 and practical 75‐bus Indian system. The outcomes of this method were taken into comparison with other optimization techniques and found that it has an advantage upon other methods in solving bidding problems. Further, it is observed that the impact of renewable sources on bidding strategy reduces the market clearing price and the generation of thermal power while increases the total bidding power.

Analytical reliability evaluation method of smart micro‐grids considering the cyber failures and information transmission system faults

“…In (31), the mathematical modelling of the PV unit's output power has been demonstrated. The probability of each state could be determined using the appropriate CDF based on recorded statistical data [79,80].…”

“…In (), the mathematical modelling of the PV unit's output power has been demonstrated. The probability of each state could be determined using the appropriate CDF based on recorded statistical data [79, 80]. $$\begin{equation} \def\eqcellsep{&}\begin{array}{l} ES{M}_{PV}\left( {s,1} \right) = \\[6pt] \left\{ { \def\eqcellsep{&}\begin{array}{@{}*{2}{c}@{}} 0&{s = 1:6\tau \;or\;s = 18\tau :24\tau }\\[6pt] {P_{rated}^{PV} \times \left[ \def\eqcellsep{&}\begin{array}{l} \left( {\dfrac{{\bmod \left( {s,\tau } \right)}}{{\left( \tau \right)}} \times (SCI_s^{\max } - SCI_s^{\min })} \right) \\[12pt] +\,\left( {\dfrac{{\left[ {\bmod \left( {s,\tau } \right) - 1} \right]}}{{\left( \tau \right)}} \times (SCI_s^{\max } - SCI_s^{\min })} \right)\, \end{array} \right]}&{s = 6\tau + 1:18\tau } \end{array} } \right.$$…”

Efficient control and multi‐criteria energy scheduling of renewable‐based utility grid via pareto‐metaheuristic optimizers

“…During the optimization phase, both objective functions present a conflicting nature, therefore the bi-objective formulation is presented in Equation (4). Moreover, coupling constraints are respectively detailed in Equation (5).…”

“…The predicted scarcity of fossil fuels and negative environmental effects brought by the compulsive utilization of fossils are the two most prominent concerns of modern energy sector [1,2]. To remedy these concerns, power producers are aggressively embracing the renewable energy, such as wind energy as a probable counterpart to the conventional thermal power [3][4][5][6]. Conversely, the uncontrolled integration of wind energy in the conventional energy system potentially brings many challenges for the system operators [7][8][9].…”

“…Furthermore, the absence of an effective scheduling strategy can lead to unavoidable trigger of fossils powered spinning reserves to accommodate the intermittent wind energy. Therefore, within the paradigm of scheduling optimization, the aggressive inclusion of wind power in the conservative hydrothermal system (HTS) requires a smart strategy to reduce the dependency on fossil fuels as well as to maximize the utilization of hydro power within their permissible limits [5,12].…”