Energy　structure　adjustment　is　a　significant　way　to　resolve　constrained　resources　and　environment,　improve　the　security　of　energy　supply,　and　achieve　sustainable　development,　which　is　a　complicated　itself　but　further　challenged　by　existence　of　uncertainties.　In　this　study,　an　inexact　multistage　stochastic　cost-risk　balanced　programming　model　is　developed　for　energy　system　management　under　considering　the　policies　of　coal-consumption　control　and　pollutants　emission　reduction.　The　method　is　an　integration　of　inexact　multistage　stochastic　programming　and　a　risk　management　tools　from　modern　financial　theory,　and　could　tackle　uncertainties　described　as　interval　values　and　probability　distributions.　The　method　could　reflect　energy　system　dynamic　characteristic　in　a　multi-period　problem,　and　provide　an　effective　linkage　between　conflicting　economic　cost　and　the　system　stability.　The　proposed　method　is　applied　to　a　real　case　of　planning　electric　power　structure　adjustment　in　Shandong　province,　China,　where　the　energy　system　is　faced　with　lots　of　difficulties　complexities　in　electric　power　structure　adjustment.　The　impact　of　coal-consumption　control　level　and　pollutants　emission　reduction　scenarios　on　energy　system　structure　adjustment,　and　resources　and　environmental　effect　were　compared　and　analyzed.　The　results　are　valuable　for　supporting　the　adjustment　or　justification　of　the　existing　power　generation　schemes　of　the　complicated　regional　energy　system.　(C)　2017　Elsevier　Ltd.　All　rights　reserved.