111 results about "Energy hub" patented technology

There is disclosed a system, computer program and method provided for enabling an energy hub for improved management and optimization of energy utilization (consumption, production and storage). In an embodiment, a computer-implemented energy hub management system comprises a micro energy hub configured to communicate with two or more energy components at a premises. An energy optimization engine has an energy component model for each energy component based on each energy component's operating characteristics, the energy optimization engine adapted to receive at least one input from the two or more energy components and an input from an external data source on any external energy utilization restrictions for the micro energy hub. In response to at least one input from the two or more energy components and any external energy utilization restrictions on the micro energy hub, the energy optimization engine is adapted to issue one or more control signals to at least one of the energy components at the premises to optimize energy utilization based on one or more optimization criteria.

An integrated energy hub facility capable of bringing together all aspects of hydrocarbon and other fluid product movement under controlled conditions applicable to the reception, storage, processing, collection and transmission downstream is provided. Input to the energy hub includes natural gas and crude from a pipeline or a carrier, LNG from a carrier, CNG from a carrier, and carrier-regassed LNG, as well as other products from a pipeline or a carrier. Storage can be above surface, in salt caverns or in subterranean formations and cavities, and include petroleum crude, natural gas, LPG, NGL, GTL and other fluids. Transmission downstream may be carried out by a vessel or other type of carrier and / or by means of a pipeline system. Cryogenic fluids are offloaded and sent to the energy hub surface holding tank, then pumped to the energy hub vaporizers and sent to underground storage and / or distribution.

The invention discloses a modeling and optimized dispatching method of an electrical series-parallel system on the basis of an energy center. The modeling and optimized dispatching method comprises the following steps: firstly, establishing an electrical network, a natural gas network and an energy hub model, and coupling the electrical network with the natural gas network through an energy hub to form the electrical series-parallel system; then, taking total energy cost as a target function, and considering various constraint conditions to establish an optimized dispatching mathematic model of the electrical series-parallel system; and carrying out solving by a primal-dual interior-point method, importing a slack variable and a barrier parameter in sequence in a solving process so as to change the model into a model which only contains an equality constraint, then, importing a Lagrange multiplier to obtain a Lagrange function, and solving a non-linear equation set formed by a KKT (Karush-Kuhn-Tucker) condition of the Lagrange function by a Newton method. A constructed example simulation result indicates that an optimization effect on the electrical series-parallel system by the modeling and optimized dispatching method is superior to an independent optimization effect.

The invention provides a coalition game optimization operation method based on a user-side regional integrated energy system, which establishes a multi-objective function, calculates the energy inputquantity and price of the energy hub, converges to the optimal solution through multiple iterations of a double-layer model, and gives the basic conditions of the optimization problem. The invention also discloses a method for optimizing the energy input quantity and price of the energy hub. Each energy hub can trade with other hubs in the alliance and solve the Nash equilibrium solution by establishing the game model and utility function. The three-stage trading scheme of energy hub is designed, and the PSO algorithm is adopted to solve the maximum profit of each alliance, and the optimal operation strategy of the integrated energy system is obtained, and the optimal operation of the integrated energy system is realized. The method strengthens the cooperative relationship among energy hubs, can improve the flexibility of energy system operation, the utilization rate of energy cascade, reduce the waste of intermittent energy such as wind and light waste, and lighten the pressure on theenergy supplier on the user load side.

The invention discloses an energy hub planning method considering integrated demand response resources. The method comprises the following steps that (1) data acquisition, including weather temperature of different seasons, power load, wind power output, candidate capacity of equipment under planning, investment cost and various parameters for normal operation of the system, is performed; (2) concrete classification and model establishment of the demand response technology are performed according to the controllability of various load; (3) modeling of an energy hub is performed according to the coupling transformation relation of various energy in the energy hub and solution is performed by using cplex; and (4) whether the planning result is more superior after participation of various demand responses is judged and the optimal result is outputted. According to the method, the translatable, transferable and cuttable demand response characteristics of various load are fully utilized toparticipate in planning and operation of the energy hub so that model selection and configuration of various types of equipment can be optimized, the total cost of planning and operation of the energyhub can be reduced and the decision support can be provided for the planning work of the energy hub.

For a multi-functional complementary system in the context of the energy Internet, a system operator and a user are viewed as two different behavioral bodies, and a structure of a heat and power combined supply multi-functional complementary system is built based on centrally interconnected energy hubs. Various energy supply, energy storage, and energy-using devices in a park are analyzed, refinedenergy flow models of various types of devices are established, user comfort is considered and detailed scheduling operation strategies are made for electric vehicles, household appliances, hot waterloads and air heat loads. A master-slave game model of the multi-functional complementary system is established. The model takes the minimum user energy consumption cost and maximum operator revenueas goals, and the mutual coordination of the above-mentioned energy supply, energy storage and energy-using devices is comprehensively considered. Through simulation verification, the purposes of fully exploiting the autonomy of the user, effectively taking interests of two parties into account, and realizing the interconnection and mutual benefit of an energy network can be achieved by the established model.

An integrated energy hub facility capable of bringing together all aspects of hydrocarbon and other fluid product movement under controlled conditions applicable to the reception, storage, processing, collection and transmission downstream is provided. Input to the energy hub includes natural gas and crude from a pipeline or a carrier, LNG from a carrier, CNG from a carrier, and carrier-regassed LNG, as well as other products from a pipeline or a carrier. Storage can be above surface, in salt caverns or in subterranean formations and cavities, and include petroleum crude, natural gas, LPG, NGL, GTL and other fluids. Transmission downstream may be carried out by a vessel or other type of carrier and / or by means of a pipeline system. Cryogenic fluids are offloaded and sent to the energy hub surface holding tank, then pumped to the energy hub vaporizers and sent to underground storage and / or distribution.

The invention discloses an optimal scheduling method of an integrated energy system considering the power-to-gas (P2G) running cost, comprising the following steps: establishing an energy hub model containing P2G, analyzing the influence of the P2G running cost on the system economy and the wind power acceptance capacity on the basis of the model, and establishing a multi-objective day-ahead optimal scheduling model; and coordinating the contradictory relation of the multi-objective day-ahead optimal scheduling model through a weighted fuzzy programming method to realize the transformation from multiple objectives to a single objective. The multi-objective model proposed in the invention takes both the system economy and the wind power acceptance capacity into consideration, and diversified choices can be provided for scheduling decision making.

The invention aims at absorbing all renewable energy, realizing peak clipping and value filling of the large power grid, improving economical benefit and adjusting accuracy of an energy hub with CCHP, and reducing the transmission cost of natural gas. An energy hub model with a power to gas function, energy storage, CCHP and electric energy feedback is constructed. Factors including a power to gas commissioning factor of a fuel and purchase based electric charge rate structure and nondeterminacy of self gas utilization and wind power output of the energy hub are taken into consideration, the energy hub model is optimized to make the fuel cost of the energy hub minimal and the energy interaction cost of the main grid minimal, and the effectiveness of the constructed energy hub model is determined.

The invention discloses a distributed comprehensive energy demand response collaborative optimization method for an intelligent building group. The distributed comprehensive energy demand response collaborative optimization method comprises the following steps: establishing a plurality of single-building multi-energy flow energy systems based on an energy hub concept in an energy internet; interconnecting a plurality of single-building multi-energy-flow energy systems through a power transmission line, a heating pipeline and a natural gas pipeline to form a multi-building multi-energy-flow energy interconnection system; establishing a mathematical model of the multi-building multi-energy flow energy interconnection system, wherein the mathematical model comprises a building energy consumption objective function and a building energy consumption constraint condition; and carrying out optimization solution on the mathematical model by utilizing an alternating direction multiplier algorithm to obtain an intelligent building optimal energy utilization strategy. The distributed comprehensive energy demand response collaborative optimization method can effectively reduce the electrical load of a power utilization peak, optimize the energy consumption structure of a user, delay the plan of power supply and distribution equipment upgrading and capacity expansion, reduce the economic pressure of an energy supplier due to relatively high investment cost, promote information privacy protection and local decision autonomy, and greatly improve the overall scheduling decision response speed.

The invention provides a multi-main-body cooperation optimization operation and cost benefit distribution method for comprehensive energy system, and relates to the technical field of integrated energy system economic operation. The method is based on an energy hub concept, and comprises: providing a multi-energy hub cooperative operation mode, and establishing a multi-energy hub economic operation model containing renewable energy power generation and power storage equipment; and analyzing a cost benefit calculation method of each subject participating in cooperation, and distributing the increased cost and benefit for executing a cooperative economic operation strategy on each subject based on a cooperative game theory. According to the method provided by the invention, the characteristics of multi-energy complementation at the energy supply side and load transfer at the energy utilization side of the comprehensive energy system are fully considered. The multi-energy hub optimizationoperation model has economy and effectiveness, the development requirement of a green and low-carbon energy system is met, the cost and benefits of all subjects participating in cooperation are distributed based on a Shapley value method, and a splitting tendency index is designed to verify the enthusiasm of the method for maintaining cooperation stability.

The invention discloses a day-to-day steady state optimization analysis method for an integrated energy system under the participation of energy storage. The method designs energy hubs and energy coupling methods based on multiple types of load requirements. On the basis of energy hubs, the energy station model structure of coupled electric heat, gas, and cold steam subsystems is proposed. Then, the electric energy in the integrated energy system separately. Steady-state mathematical model of gas-cooled steam system are established; and the influence of storage, heat storage and cold storage on the integrated steady-state energy system of grid-connected operation is analyzed; secondly, electricity-containing heat and gas cooling under different load structures are established. The steady-state nonlinear optimization model of the steam subsystem is in the past; the final example analysis verifies the effectiveness of the steady-state optimization calculation and steady-state operation analysis of the integrated energy system. The invention mainly solves the problem of insufficient coordination of various subsystems in the current integrated energy system, and the method can reasonably reflect the operational characteristics of the integrated energy system.

The invention discloses a methane-wind-light full renewable energy system based on an energy hub and a methodthereof. The method comprises the following steps: constructing a full renewable energy system based on a methane-wind energy-solar hub; carrying out detailed modeling on an energy hub containing an energy storage element, processing the energy hub into a linearized matrix which is more adaptive to system optimization scheduling, and then further considering the output uncertainty of wind-solar renewable energy sources; and constructing a day-ahead-real-time two-stage distributed robustoptimization scheduling model based on data driving. According to the invention, the absorption of renewable energy can be promoted, the absorption of biomass energy is promoted, the heat preservation and supply of the biogas digester can be realized in winter, and the stable supply of biogas is guaranteed; and the thermoelectric coupling degree is weakened, the consumption of wind-solar renewable energy sources is effectively promoted, and meanwhile, the comprehensive scheduling cost of the system is reduced.

The invention discloses a park operator energy transaction optimization decision-making method based on supply and demand game interaction. The method comprises the following steps: performing detailed modeling analysis on internal energy equipment of a park comprehensive energy system by adopting the concept of an energy hub, establishing a benefit function by taking the net profit of energy purchasing and selling of a park operator participating in the market as a target, and simulating the benefit function through historical transaction strategy data of an energy supplier and a user; basedon the Stackelberg game theory, considering the initiative of energy suppliers and users at the same time, adopting a power-price curve containing profits and marginal costs and a time-sharing unifiedprice respectively, and providing a park operator supply and demand double-side game interaction framework; based on Nash equilibrium definition, enabling mathematical derivation to prove that the game model has a unique equilibrium solution; on the basis of an inverse induction method, adopting a solving algorithm combining a particle swarm algorithm and a CPLEX solver to solve the model, and the method is reasonable in structure, high in practicability and suitable for popularization.

The invention discloses a three-phase unbalanced dynamic power flow model predictive control method for a distribution network with a smart community. Mainly aiming at the problems of distribution network power flow and optimal control when multi-energy is able to access the distribution network, a method for accessing various kinds of distributed energy to the distribution network in a centralized single-point manner to perform optimal control and solving the dynamic power flow of the distribution network online is provided, Considering the fluctuation of community distributed wind power, photovoltaic output and load, aiming at community economy and environmental protection operation, local consumption of the distributed energy is achieved, and energy interaction with the distribution network is carried out, so as to improve the utilization rate of the distributed energy. According to the distributed power supply and load change conditions of the system, a dynamic power flow analysismethod for the three-phase unbalanced distribution network containing a community multi-energy hub is proposed. A model predictive control technology is used for solving the power flow of the distribution network online in a rolling mode, in line with the real-time characteristics of the system operation, and improvement of the control level and operational safety of the distribution network undermulti-energy coordination is facilitated.

The invention relates to an energy hub modeling method considering a solid oxide fuel cell and electricity-to-gas, which comprises the following steps of: S1, researching an electricity-to-gas model,a hydrogen storage tank model and a solid oxide fuel cell model before respectively establishing models for conversion equipment; S2, constructing an electricity-to-gas conversion model and a hydrogenstorage tank model; S3, for the solid oxide fuel cell model, describing an SOFC power generation mathematical model through the current I flowing out of the galvanic pile and the port voltage U, andthen obtaining an SOFC heating mathematical model by calculating the subtraction between the energy released in the chemical reaction process of the hydrogen supplied by the hydrogen storage tank andthe SOFC power generation amount; and S4, finally, when an energy hub optimization model is constructed, giving a cost calculation formula, meanwhile, establishing a unit model and constraint conditions, and the constraint conditions include power balance constraints, tie line constraints, water abandoning constraints and equipment model constraints. Meanwhile, the conversion efficiency between system energy sources is improved.

The invention discloses a multi-energy flow transaction-oriented energy hub bidding method and system. The method first establishes a multi-energy flow transaction-oriented energy hub master-slave game bidding strategy model; then processes the energy hub master-slave game bidding strategy model , get the mixed integer linear programming model; and according to the mixed integer linear programming model, calculate the bidding strategy and the maximum operating income of the energy hub; hot sale price. Using the method or system provided by the present invention, fully considering the multi-energy flow trading capabilities of energy hubs with combined heat and power storage and combined heat and power generation functions, a bidding strategy for energy hub operators oriented to multi-energy flow transactions is given, and energy hubs are improved. The income of the operating entity in the multi-energy flow trading market.

The present disclosure discloses a method for optimizing equipment capacity and equipment power of an energy hub system. The method includes establishing an energy hub model containing natural gas boilers, electric boilers, coolers and heat pumps, establishing a bilevel optimized upper model to solve the optimal heat pump capacity, and establishing a bilevel optimized lower model to solve the optimal power utilization of each energy device based on the binary search algorithm of the quadratic function solves the upper model by using the multi-objective evolutionary algorithm NSGA-II to solve the lower model. The optimization method of the present invention can solve the multi-objective bilevel model problem without the help of commercial optimization software. Obtaining a reasonable, efficient and green planning scheme makes the total operating cost and total exhaust gas emissions of the energy hub relatively optimal.

The invention discloses a comprehensive energy system risk identification method based on multi-energy flow fault coupling propagation, and relates to the field of comprehensive energy safety analysis, which comprises the following steps: 1) respectively establishing mathematical models of a power system, a thermodynamic system, a natural gas system and electric thermal coupling equipment; 2) designing a risk identification system: putting forward a multi-dimensional risk identification index system for the multi-energy type contained in the comprehensive energy system; 3) calculating and analyzing a load margin optimization model of the electric thermal coupling system by combining a comprehensive energy network power flow optimization algorithm; and 4) based on the risk of load margin loss probability, determining a key branch, a node, a coupling propagation path and a key energy hub for mutual conversion between heterogeneous energy flows of the energy transmission network in the comprehensiveenergy system. The invention provides a comprehensive energy system risk identification method based on multi-energy flow fault coupling propagation. The safety, flexibility and reliabilityof social energy supply are improved.

The invention discloses a multi-energy flow integrated power flow decoupling method based on an energy hub in an integrated energy system. The method comprises the steps of (1) establishing basic models of the energy hub, a power network optimization power flow and a natural gas network optimization power flow, (2) establishing a basic architecture of a multi-energy flow optimal power flow problem, (3) constructing a multi-energy flow mathematical expression based on the energy hub, and (4) giving a specific flow of the multi-energy flow integrated power flow decoupling method. The invention decomposes the multi-energy flow optimal power flow problem into a traditional single-energy flow optimal power flow problem and maintains the characteristics of the synchronization analysis of an integrated energy system, and therefore, the multi-energy flow optimal power flow problem is solved well.

The invention discloses a comprehensive energy power distribution system operation domain modeling method which comprises the following steps: defining an energy hub input side tie line power set provided with an automatic control device as a working point based on geographic separation and energy regulation and control of an energy hub, and proposing a comprehensive energy power distribution system operation domain model; setting a multi-energy network and energy hub operation constraint condition in an operation domain solving process according to a safe operation requirement; and setting aboundary point judgment basis by taking the energy hub as a regulation and control means to solve the operation domain model. According to the comprehensive energy power distribution system operationdomain modeling method, visual display of the maximum operation boundary of the comprehensive energy power distribution system and judgment of the operation state of the working point are realized, and the comprehensive energy power distribution system operation domain modeling method can be applied to monitoring, evaluation and regulation of the operation state of the comprehensive energy power distribution system, and assists a dispatcher to formulate a control scheme.

The invention discloses a multi-point linearized probability energy flow method of an integrated energy system with electricity converting to natural gas. The method includes the following steps: firstly proposing an energy hub model containing wind electricity, thermoelectricity combined supply, and electricity converting to natural gas; then conducting quantitative analysis on precision of linearized energy flow equations of a power grid and a natural gas net, and subsequently making a conclusion that the precision of the linearized energy flow of the natural gas net is explicitly lower than that of the power grid. Based on the conclusion, the invention provides a method for calculating the multi-point linearized energy flow. At the same time, the method takes into consideration of the relativity between electricity, natural gas and thermal load and wind velocity, and based on a probability density distribution function of undetermined energy flow injection, adopts the monte carlo simulation method in generating random samples. For each random sample, the method adopts the multi-point linearization method in calculating the energy flow. According to the invention, the method has high calculation efficiency, and at the same time has linearization errors which are within an acceptance scope.

The invention discloses a standardized construction method of an integrated energy system energy hub model. According to the method, a complex integrated energy system energy hub model is divided into simple integrated energy system energy hub models, coupling matrixes of the simple integrated energy system energy hub model are orderly multiplied, and finally a coupling matrix of the whole complex integrated energy system energy hub model is calculated. In the construction process of the coupling matrix, the energy circulation is taken into consideration by means of adding a limit equation to the integrated energy system energy hub model, and the mismatch of the coupling matrixes of the different simple integrated energy system energy hub models is avoided through adding virtual energy conversion equipment. Meanwhile, in the construction matrix modeling process, the concepts of energy storage equipment location and energy side demand response are extended, thereby enabling the energy storage and energy side demand response of an electric power system to be extended to the integrated energy system.

The invention discloses a multi-user energy sharing method based on an electricity-light-biogas multi-energy coupling system, and the method comprises the following steps: building an electricity-light-biogas multi-energy complementary sharing framework which comprises an energy hub unit, a user energy sharing unit and a market bidding unit; establishing a double-layer planning model based on theelectricity-light-biogas multi-energy complementary sharing framework, the objective function of an upper-layer planning model of the double-layer planning model is the maximum profit of the energy hub unit, and the objective function of a lower-layer planning model of the double-layer planning model is the maximum satisfaction degree of user energy consumption; and formulating optimal schedulingarrangement and optimal pricing by utilizing the double-layer planning model so as to maximize the profit of the energy hub unit. The method solves the problems of waste and low utilization rate of wind energy, light energy, biomass energy and the like, ensures that the energy hub unit can obtain the maximum profit, and realizes win-win of users and the energy hub unit.

The invention discloses a method for solving the optimal energy flow of an electrically interconnected integrated energy system based on a second-order cone optimization algorithm. Firstly, an electrically interconnected integrated energy system model composed of an electric power system, a natural gas system and an energy hub is established. Then, the integrated energy system model is transformedinto a convex model which is easy to solve. Then, cut sets are introduced into power system and natural gas system respectively to ensure that the obtained solution is the optimal solution of the original problem. Finally, an example is given to verify the correctness and effectiveness of the proposed algorithm. The invention obtains an efficient and fast optimization method for solving an optimization model of an integrated energy system, and provides support for the optimization operation of an electrically interconnected integrated energy system.

The invention discloses an interval practical security domain modeling method, which is based on a regional comprehensive energy system containing renewable energy sources, considers the uncertainty of the renewable energy sources, and adopts an interval mathematical method for processing; by combining engineering practice, and based on the N1 security criterion of the regional comprehensive energy system and the load of an energy hub output side pipeline section, the method establishes an interval practical safety domain model of the regional comprehensive energy system containing renewable energy, further establishes an interval practical safety boundary model, and proposes an interval practical safety distance model and an interval maximum energy supply capacity model. On the basis, a system dimension reduction observation method and a full-dimensional observation method are established, and the safety of the regional comprehensive energy system containing renewable energy sources can be accurately and quickly analyzed.

The invention relates to an AC / DC hybrid microgrid topology design method based on an energy router. The design method can separate a plurality of AC / DC submicrogrids, and directionally simulate various microgrid topological structures at present and in the future, so as to meet various requirements of microgrid research, including an urban campus-type microgrid, island-type microgrid, and family-type microgrid. The design and implementation of AC / DC hybrid microgrid, on the one hand, can effectively eliminate the negative characteristics such as intermittency and randomness of renewable energy output, provide reliable power supply to distribution network, and improve the efficiency of energy utilization; On the other hand, facing the future, the microgrid will gradually change from a single regional power supply system based on electric energy conversion, storage and transmission to an energy hub with simultaneous integration of multi-energy conversion and interaction such as naturalgas and thermal energy utilization. The hybrid AC / DC microgrid based on the energy router can integrate multiple types of energy systems, which lays a foundation for this.

The invention relates to a park comprehensive energy system low-carbon operation method based on Q learning. The method comprises the steps: establishing a model PIES of a park comprehensive energy system based on the concept of an energy hub; considering the treatment cost of the PIES carbon dioxide emission, and establishing a mathematical optimization model of a PIES low-carbon economic operation strategy by taking the minimum daily operation cost of the PIES as a target; establishing a Markov decision process MDP corresponding to the optimization model, and correspondingly defining a statespace, an action space and a reward function of an MDP problem; and solving the MDP problem by adopting an improved Q learning algorithm, and carrying out initialization improvement on the Q value table by utilizing a reward function. According to the invention, low-carbon operation of the park comprehensive energy system can be realized.

The invention discloses a construction method of an energy hub planning model considering renewable energy sources and demand response, which is suitable for being executed in computing equipment andcomprises the following steps: acquiring basic parameters; establishing an energy hub planning model considering renewable energy sources and demand response by utilizing an interval method, wherein the model comprises an objective function and constraint conditions; and substituting the basic parameters into the model, solving the model by adopting an improved non-dominated sorting genetic algorithm by taking the minimum investment and operation cost of an operator and the highest utilization rate of renewable energy sources as objectives, and outputting the capacity configuration data and output data of each device in the energy hub and a pricing scheme of electricity.