Economy Function in the Mode of Sustainable Development

To implement the previously formulated principles of sustainable economic development, all solutions of the linear system of equations and inequalities, which are satisfied by the vector of real consumption, are completely described. It is established that the vector of real consumption with the minimum level of excess supply is determined by the solution of some quadratic programming problem. The necessary and sufficient conditions are established under which the economic system, described by the “input-output” production model, functions in the mode of sustainable development. A complete description of the equilibrium states for which markets are partially cleared in the economy model of production “input-output” is given, on the basis that all solutions of system of linear equations and inequalities are completely described. The existence of a family of taxation vectors in the “input-output” model of production, under which the economic system is able to function in the mode of sustainable development, is proved. Restrictions were found for the vector of taxation in the economic system, under which the economic system is able to function in the mode of sustainable development.

Dynamic optimal allocation of energy storage systems integrated within photovoltaic based on a dual timescale dynamics model

Energy storage systems(ESSs)operate as independent market participants and collaborate with photovoltaic(PV)generation units to enhance the flexible power supply capabilities of PV units.However,the dynamic variations in the profitability of ESSs in the electricity market are yet to be fully understood.This study introduces a dual-timescale dynamics model that integrates a spot market clearing(SMC)model into a system dynamics(SD)model to investigate the profit-aware capacity growth of ESSs and compares the profitability of independent energy storage systems(IESSs)with that of an ESS integrated within a PV(PV-ESS).Furthermore,this study aims to ascertain the optimal allocation of the PV-ESS.First,SD and SMC models were set up.Second,the SMC model simulated on an hourly timescale was incorporated into the SD model as a subsystem,a dual-timescale model was constructed.Finally,a development simulation and profitability analysis was conducted from 2022 to 2040 to reveal the dynamic optimal range of PV-ESS allocation.Additionally,negative electricity prices were considered during clearing processes.The simulation results revealed differences in profitability and capacity growth between IESS and PV-ESS,helping grid investors and policymakers to determine the boundaries of ESSs and dynamic optimal allocation of PV-ESSs.

Mathematical Foundations of Sustainable Economy Development

The principles of sustainable economic development are formulated on the basis of the developed concept of description of economic systems. Mathematical algorithms for finding equilibrium states were built and the conditions for complete clearing of the markets were found. The definition of the phenomenon of recession is given and theorems are established that formulate the conditions for the existence of a recession in the economic system. The recession depth parameter is introduced. For the input-output production model, the necessary and sufficient conditions under which the economic system functions in a profitable mode have been established. The conditions for supply vectors of firms for special technological mappings and consumers demand under which complete clearing of markets takes place are found.

Building and Researching the Bidding Model Based on the Costof Power Plant

A bidding model of neural network was presented to pursue the largest benefit according to the policy of separating power plants from network and bidding transaction. This model bases on the cost of power plant and its research object is a power plant in the market. The market clearing price (MCP) can be predicted and an optimized load curve can be decided in this model. The model may provide technical support for the power plant.

A new method on hydrothermal scheduling optimization in electric power market

The hydrothermal scheduling in the electric power market becomes difficult because of introducing competition and considering sorts of constraints. An augmented Lagrangian approach is adopted to solve the problem,which adds to the standard Lagrangian function a quadratic penalty term without changing its dual property,and reduces the oscillation in iterations. According to the theory of large system coordination and decomposition,the problem is divided into hydro sub-problem and thermal sub-problem,which are coordinated by updating the Lagrangian multipliers,then the optimal solution is obtained. Our results for a test system show that the augmented Lagrangian approach can make the problem converge into the optimal solution quickly.

Optimal operation of cascaded hydroelectric power plants in the power market

An improved network flow algorithm, which includes the minimum cost network flow and the same period network flow, is proposed to solve the optimization of cascaded hydroelectric power plants in a competitive electricity market. The typical network flow is used to find the feasible flow and add the discharge water to different cascaded hydroelectric power plants at the same step. The same period network flow is used to find the optimal flow and add the power output at a different step. This new algorithm retains the advantages of the typical network flow, such as simplicity and ease of realization. The result of the case analysis indicates that the new algorithm can achieve high calculation precision and can be used to calculate the optimal operation of cascaded hydroelectric power plants.

Risk-averse Market Clearing for Coupled Electricity, Natural Gas and District Heating System

Multiple energy carriers can be coupled as an Integrated Energy System (IES) through interconnection tech- nologies. Unexpected risks will be transferred with the growing coupling of energy systems, mainly stemming from the uncertain- ties in different energy sectors. It is imperative to coordinate the operation of different energy systems to improve energy efficiency and ensure energy security. With the close integration of different energy systems, it is necessary to couple these different energy markets to achieve the holistic energy supply economy. On the other hand, uncertainties in the energy systems will bring the financial risk for the operator of IES. A risk-averse stochastic market clearing model for the IES is proposed to study the operating strategy aiming at minimizing the operation cost. While the financial risk imposed by the wind power uncertainties is restricted to a predefined level. Simulations results are provided to verify that the proposed model can improve market efficiency and handle the trade-off between cost and risk.

Bi-level optimization based two-stage market clearing model considering guaranteed accommodation of renewable energy generation

The existing electricity market mechanisms designed to promote the consumption of renewable energy generation complicate network participation in market transactions owing to an unfair market competition environment,where the low cost renewable energy generation is not reflected in the high bidding price of high cost conventional energy generation.This study addresses this issue by proposing a bi-level optimization based two-stage market clearing model that considers the bidding strategies of market players,and guarantees the accommodation of renewable energy generation.The first stage implements a dual-market clearing mechanism that includes a unified market for trading the power generations of both renewable energy and conventional energy units,and a subsidy market reserved exclusively for conventional generation units.A re-adjustment clearing mechanism is then proposed in the second stage to accommodate the power generation of remaining renewable energy units after first stage energy allocations.Each stage of the proposed model is further described as a bi-level market equilibrium problem and is solved using a co-evolutionary algorithm.Finally,numerical results involving an improved IEEE 39-bus system dem-onstrate that the proposed two-stage model meets the basic requirements of incentive compatibility and individual rationality.It can facilitate the rational allocation of resources,promote the economical operation of electric power grids,and enhance social welfare.

Local Energy and Planned Ramping Product Joint Market Based on a Distributed Optimization Method

High penetration of renewable energy generation(REG)in the distribution system increases both the power uncertainty at a given interval and the power variation between two intervals.Reserve markets addressing power uncertainty have been widely investigated.However,there is a lack of market mechanisms regarding the power variation of the load and REGs.This paper thus defines a planned ramping(PR)product to follow the net load variation and extends the local energy market to include the trading of PR products.Players are economically compensated for their PR products.Bidding models of dispatchable generators and flexible load aggregators in the joint market are investigated.To solve the market problem in polynomial time,a distributed market clearing method is developed based on the ADMM algorithm.The joint market is tested on a modified IEEE 33-bus system.It verifies that introducing the PR market can encourage flexible loads to provide more PR service to accommodate the net load variation.As such,the ramping cost of dispatchable generators is reduced by 29.09%in the test case.The planned energy curtailment from REG is also reduced.The computational efficiency of the proposed distributed clearing method is validated by comparing it with a centralized method.