Claims: A processor implemented method (300) for determining optimal decision parameters for a Demand Response (DR) event involving a District Cooling Plant (DCP) serving at least some of a plurality of buildings, wherein the DCP and each of the at least some of the plurality of buildings are configured to participate with an associated electrical utility from a plurality of electrical utilities in the DR event, wherein each of the at least some of the plurality of buildings and the DCP comprises one or more power consuming units, the method (300) comprising the steps of : receiving input parameters from the associated electrical utility, by one or more hardware processors, wherein the input parameters comprise a time interval of the DR event, a total target energy reduction value (R_T) to be achieved after the DR event, an initial supply chilled water temperature value (T_s) of the DCP from a predefined range and an initial demand energy reduction value (R_D^((n) )) of the DCP, wherein an initial value of n is zero and the time interval of the DR event comprises a start time (t) and an end time (t+T) where T is a total time duration of the DR event (302); determining an energy reduction vector (R) comprising an energy reduction value (R_x) for each building (x) of the at least some of the plurality of buildings such that (i) a total thermal discomfort value (?_B¦G_x ) of occupants thereof is minimum, by the one or more hardware processors, wherein the total thermal discomfort value (?_B¦G_x ) of occupants is a sum of a thermal discomfort value (G_x ) of occupants for each building (x) of the at least some of the plurality of buildings and (ii) a sum of energy reduction value (?_B¦R_x ) thereof and the initial demand energy reduction value (R_D^((n) )) of the DCP is greater than or equal to the total target energy reduction value (R_T) (304); identifying, by the one or more hardware processors, a temperature set point (T_SP) and a lighting intensity factor (L_(f )) for each building (x) of the at least some of the plurality of buildings based on an associated energy reduction value (R_x) using a look-up table and by using an inverse mapping technique (306); extracting, by the one or more hardware processors, a cooling load (Q_x (t)) for each building (x) of the at least some of the plurality of buildings and a chilled water mass flow rate? (m?_x (t)) thereof based on an associated temperature set point (T_SP) and an associated lighting intensity factor (L_(f )), using a British Thermal Units (BTU) meter installed in a corresponding building (308); calculating, by the one or more hardware processors, a cooling load ?(Q?_D (t)) of the DCP and a chilled water mass flowrate ?(m?_D (t)) of the DCP by summing cooling loads and chilled water mass flow rates of each building (x) of the at least some of the plurality of buildings respectively (310); estimating, by the one or more hardware processors, an intermediate energy reduction value ( R_D^((*)) ) of the DCP based on the cooling load ?(Q?_D (t)) of the DCP and the chilled water mass flowrate ?(m?_D (t)) of the DCP using a chiller performance curve and a pump performance curve of the DCP (312); determining, by the one or more hardware processors, a new demand energy reduction value ( R_D^((n+1)) ) of the DCP based on the initial demand energy reduction value (R_D^((n) )), the intermediate energy reduction value ( R_D^((*)) ) and a relaxation parameter ß (314); iteratively performing, by the one or more hardware processors, steps (a) through (g) by taking the new demand energy reduction value ( R_D^((n+1)) ) of the DCP as the initial demand energy reduction value (R_D^((n))) of the DCP until a condition ?|R?_D^((n+1))-R_D^((n) ) |