An energy management system (EMS) strategy for combined heat and power (CHP) systems based on a hybrid optimization method employing fuzzy programming

An optimization method, which considers the Combined Heat and Power (CHP) model under uncertainty, has been developed to determine the optimal capacities for the CHP and boiler such that thermal and electrical energy demands can be satisfied with high cost efficiency. The proposed method offers an energy management system (EMS) strategy which employs the fuzzy set theory to account for the uncertainties associated with electrical and thermal energy demands as well as those associated with natural gas and electrical power prices in order to determine the optimum ranges for boiler and CHP capacities which maximize an objective function based on the net present value (NPV). The reduction in operational strategy expenses arising from the monetary cost of the credit attainable by air pollution reduction is also taken into account in evaluation of the objective function. The optimal range for boiler and CHP capacities and the resulting projection for the range of optimal value of the objective function are derived using a hybrid optimization method involving the particle swarm optimization (PSO) and the linear programming algorithms. The viability of the proposed method is demonstrated by analyzing the decision to construct a CHP system for a typical hospital.

► Optimal plant configuration is determined using a hybrid algorithm optimizing operational costs and environmental emission.
► Investment criteria are assessed based on fuzzy programming in light of uncertainties in energy demand and costs.
► The optimization algorithm provides a stable solution space identifying optimum capacity ranges for the CHP and boiler.
► The viability of the proposed method was demonstrated by analyzing the decision to construct a CHP for a typical hospital.