Environmental And Economic Dispatching Of Combined Cooling Heating And Power System Considering The Risk Of Renewable Energy Losses

Due to the fossil fuel crisis contributed by the explosive growth in energy demand, combined cooling heating and power (CCHP) systems which can jointly supply electricity and hot/cold have become the mainstream of energy generation technology. Meanwhile, to promote the sustainable development of renewable energy, a series of renewable incentive mechanisms have been introduced. According to the renewable over and under estimated penalty cost, draw support from conditional value at risk (CVaR), the renewable conditional risk constraints being build. Therefore, the study of the optimal dispatch and the safe and economical operation of CCHP system which consist of fossil fuel and other renewable energy sources is an important research direction to improve energy efficiency and energy saving. The study can not only promote the sustainable development of our country’s economy, but also has a certain reference value and important practical research significance for the development of renewable incentive mechanisms and the theory about loss risk.In this paper, the joint probability distribution of maximum power generation by wind turbines is established based on Copula joint function and marginal probability distribution of wind speed. The economic scheduling model for multi-network CCHP system is proposed to reduce greenhouse gases emission and maximize renewable energy utilization, meanwhile considering the impacts of feed-in tariff (FIT) and tradable green certificate (TGC) schemes on renewable units and secure operation constraints of electricity network and heating/cooling pipe network. After that, in order to solution to the problem of underestimate and overestimate penalty cost expectation of electricity generated by wind is easy to appear the curse of dimensionality and difficult to direct integration, using the sample average approximation method. Finally, one modified 15-bus system is used to analyze and comparison of the effects of two kinds of renewable incentive mechanism to the scheduling results. The results show that in the condition of oligopoly, the tradable green certificate is the better renewable incentive mechanism.Based on the probability distribution of wind speed, the conditional risk constraint of renewable energy loss is then proposed based on the depiction of tail probability by conditional value at risk. And a environment economic dispatching model is proposed for combined cooling heating and power system aiming at minimizing the total generation cost and maximizing the renewable energy utilization, with the security constraints of electricity networks and pipe networks. In order to overcome the computational difficulty, the Rockafeller and Uryasey theory, sampling average approximation, smoothing methods are adopted to equivalently transform the multi-integration conditional risk constraints into non-smooth inequality constraints, which can be then introduced into objective function as a penalty term for function smoothing. For the typical continuous convex optimization problem, the classical primal-dual interior point algorithm is introduced to solve the problem. Finally, one modified IEEE 14-bus system is used to quantitatively evaluate the impacts of the risk confidence level and the Monte Carlo sampling frequency on the scheduling results. The results show that the environment economic dispatching model established in this paper has a great significance for reduce cost, improve efficiency and increase production of renewable energy.